Research

15 pages, 2141 KiB

Open AccessArticle

Adaptive Image Edge Extraction Based on Discrete Algorithm and Classical Canny Operator

by Phusit Kanchanatripop and Dafang Zhang

Symmetry 2020, 12(11), 1749; https://doi.org/10.3390/sym12111749 - 22 Oct 2020

Cited by 15 | Viewed by 2616

In order to improve the accuracy of image edge detection, this paper studies the adaptive image edge detection technology based on discrete algorithm and classical Canny operator. First, the traditional sub-pixel edge detection method is illustrated based on the related literature research. Then, [...] Read more.

In order to improve the accuracy of image edge detection, this paper studies the adaptive image edge detection technology based on discrete algorithm and classical Canny operator. First, the traditional sub-pixel edge detection method is illustrated based on the related literature research. Then, Canny operator is used for detection, the edge model of the quadric curve is established using discrete data, and the adaptive image edge parameters are obtained using one-dimensional gray moment. Experimental results show that the accuracy of feature detection is 99%, which can be applied to the practice of image edge detection to a certain extent. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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14 pages, 1861 KiB

Open AccessArticle

Maritime Autonomous Surface Ship’s Path Approximation Using Bézier Curves

by Anna Miller and Szymon Walczak

Symmetry 2020, 12(10), 1704; https://doi.org/10.3390/sym12101704 - 16 Oct 2020

Cited by 10 | Viewed by 2246

Abstract

This work is devoted to the second order rational Bézier curve coefficients estimation. We present the methodology of unique coefficients for each type of ship computation. In the presented formulas of ship’s length, a draft and angular path combined with a drift path [...] Read more.

This work is devoted to the second order rational Bézier curve coefficients estimation. We present the methodology of unique coefficients for each type of ship computation. In the presented formulas of ship’s length, a draft and angular path combined with a drift path are used. This approach leads to the simplest and most accurate Maritime Autonomous Surface Ships (MASS) path modeling. Three rational curve control points are waypoints (WPT). Using WPTs as curve control points allows integrating a trajectory intuitive for the navigator with a path predicting model used as a reference in the control system. Research was done based on real-time data originating from the MASS autonomous trajectory tracking system. The presented mathematical modeling tool may be treated as the best way of future trajectory prediction due to low computation power required. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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20 pages, 610 KiB

Open AccessArticle

Towards Dynamic Uncertain Causality Graphs for the Intelligent Diagnosis and Treatment of Hepatitis B

by Nan Deng and Qin Zhang

Symmetry 2020, 12(10), 1690; https://doi.org/10.3390/sym12101690 - 15 Oct 2020

Cited by 3 | Viewed by 1763

Abstract

Hepatitis B is a widespread epidemic in the world, but so far no single drug has been shown to kill or eliminate the Hepatitis B virus and heal people with chronic Hepatitis B virus infection. Based on comprehensive investigations to relevant characteristics of [...] Read more.

Hepatitis B is a widespread epidemic in the world, but so far no single drug has been shown to kill or eliminate the Hepatitis B virus and heal people with chronic Hepatitis B virus infection. Based on comprehensive investigations to relevant characteristics of Hepatitis B, a diagnostic modelling and reasoning methodology using Dynamic Uncertain Causality Graph is proposed. The symptoms, physical signs, examinations results, medical histories, etiology, pathogenesis and other factors were included in the diagnosis model. In order to reduce the difficulty of building the model, a modular modeling scheme is proposed, which provides multi-perspectives and arbitrary granularity for the expression of disease causality. The chain reasoning algorithm and weighted logic operation mechanism are introduced to ensure the correctness and effectiveness of diagnostic reasoning under incomplete and uncertain information. In addition, the causal view of the potential interactions between diseases and symptoms visually shows the reasoning process in a graphical way. In the relevant model, the model of the diagnostic process and the model of the therapeutic process are symmetrical. The results show that, even with incomplete observations, the proposed methodology achieves encouraging diagnostic accuracy and effectiveness, providing a promising assistance tool for physicians in the diagnosis of Hepatitis B. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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17 pages, 4832 KiB

Open AccessArticle

A Stochastic Intelligent Computing with Neuro-Evolution Heuristics for Nonlinear SITR System of Novel COVID-19 Dynamics

by Muhammad Umar, Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Muhammad Shoaib, Manoj Gupta and Yolanda Guerrero Sánchez

Symmetry 2020, 12(10), 1628; https://doi.org/10.3390/sym12101628 - 02 Oct 2020

Cited by 118 | Viewed by 3636

Abstract

The present study aims to design stochastic intelligent computational heuristics for the numerical treatment of a nonlinear SITR system representing the dynamics of novel coronavirus disease 2019 (COVID-19). The mathematical SITR system using fractal parameters for COVID-19 dynamics is divided into four classes; [...] Read more.

The present study aims to design stochastic intelligent computational heuristics for the numerical treatment of a nonlinear SITR system representing the dynamics of novel coronavirus disease 2019 (COVID-19). The mathematical SITR system using fractal parameters for COVID-19 dynamics is divided into four classes; that is, susceptible (S), infected (I), treatment (T), and recovered (R). The comprehensive details of each class along with the explanation of every parameter are provided, and the dynamics of novel COVID-19 are represented by calculating the solution of the mathematical SITR system using feed-forward artificial neural networks (FF-ANNs) trained with global search genetic algorithms (GAs) and speedy fine tuning by sequential quadratic programming (SQP)—that is, an FF-ANN-GASQP scheme. In the proposed FF-ANN-GASQP method, the objective function is formulated in the mean squared error sense using the approximate differential mapping of FF-ANNs for the SITR model, and learning of the networks is proficiently conducted with the integrated capabilities of GA and SQP. The correctness, stability, and potential of the proposed FF-ANN-GASQP scheme for the four different cases are established through comparative assessment study from the results of numerical computing with Adams solver for single as well as multiple autonomous trials. The results of statistical evaluations further authenticate the convergence and prospective accuracy of the FF-ANN-GASQP method. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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17 pages, 4961 KiB

Open AccessArticle

A Geometric Accuracy Error Analysis Method for Turn-Milling Combined NC Machine Tool

by Pengzhong Li, Ruihan Zhao and Liang Luo

Symmetry 2020, 12(10), 1622; https://doi.org/10.3390/sym12101622 - 30 Sep 2020

Cited by 7 | Viewed by 2077

Abstract

Turn-Milling Combined NC machine tool is different from traditional machine tools in structure and process realization. As an important means in the design stage, the analysis method of geometric accuracy error is also different from the traditional method. The actual errors and the [...] Read more.

Turn-Milling Combined NC machine tool is different from traditional machine tools in structure and process realization. As an important means in the design stage, the analysis method of geometric accuracy error is also different from the traditional method. The actual errors and the error compensation values are a pair of "symmetry" data sets which are connected by the movement of machine tools. The authors try to make them more consistent through this work. The geometric error terms were firstly determined by topological structure analysis, then based on homogeneous coordinate transformation and multibody system theory, the geometric error model was established. With the interval theory, the function rule of sensitivity of geometric error sources to spatial errors was analyzed in detail, and the global maximum interval sensitivity of nine geometric error sources was extracted, providing a theoretical basis for error compensation and precision distribution. The geometric error sensitivity analysis method proposed in this paper can accurately evaluate the influence weights of each error term on the machining accuracy, and identify the important sensitive error terms with great influence on the machining accuracy from many error terms. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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17 pages, 2655 KiB

Open AccessArticle

An Extended Object-Oriented Petri Net Model for Vulnerability Evaluation of Communication-Based Train Control System

by Ye Zhang, Yatao Wang, Lin Wang and Guoqiang Cai

Symmetry 2020, 12(9), 1474; https://doi.org/10.3390/sym12091474 - 08 Sep 2020

Cited by 2 | Viewed by 1753

Abstract

Communication-based train control systems (CBTCs) have been widely used as crucial systems in urban rail transit networks. CBTCs typically utizes different levels of symmetry structure according to different geographic deployments. While, in practice, CBTCs crashes have destroyed the transportation systems of the whole [...] Read more.

Communication-based train control systems (CBTCs) have been widely used as crucial systems in urban rail transit networks. CBTCs typically utizes different levels of symmetry structure according to different geographic deployments. While, in practice, CBTCs crashes have destroyed the transportation systems of the whole city level for many times. Based on the extended object-oriented Petri net (EOOPN), this paper proposes a vulnerability model and an evaluation procedure, which are capable of considering the vulnerability factors in both inner system level and equipment level. On the system level, it establishes a complex dynamic communication structure model among the distributed subsystems, while on the equipment level, it details the equipment changing state during train operation. The searching algorithm of EOOPN depicts possible failed paths of CBTCs via the token transition among train¬–ground communication EOOPN subnets. The vulnerability calculation is applied to the metro company’s in situ CBTCs to illustrate the effectiveness of the approach. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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19 pages, 336 KiB

Open AccessArticle

A Refinement of the Conjecture on the Pseudo Component Transformation of the Lattice Points in the Simplex

by Bara Kim and Jeongsim Kim

Symmetry 2020, 12(9), 1427; https://doi.org/10.3390/sym12091427 - 28 Aug 2020

Cited by 1 | Viewed by 1211

Abstract

We consider mixture experiments in which the proportions of the components must be non-negative and their sum must equal one. Thus, the experimental region for a mixture of components is a simplex. Li and Zhang (2017) made the conjecture that the pseudo component [...] Read more.

We consider mixture experiments in which the proportions of the components must be non-negative and their sum must equal one. Thus, the experimental region for a mixture of components is a simplex. Li and Zhang (2017) made the conjecture that the pseudo component transformation of the lattice points in the simplex has a special property. In this paper, we show that this conjecture is not true in general. Furthermore, we refine this conjecture and prove the refined conjecture. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

17 pages, 943 KiB

Open AccessArticle

Design of a Predictive Model of Rock Breakage by Blasting Using Artificial Neural Networks

by Jimmy Aurelio Rosales-Huamani, Roberth Saenz Perez-Alvarado, Uwe Rojas-Villanueva and Jose Luis Castillo-Sequera

Symmetry 2020, 12(9), 1405; https://doi.org/10.3390/sym12091405 - 24 Aug 2020

Cited by 8 | Viewed by 4196

Abstract

Over the years, various models have been developed in the stages of the mining process that have allowed predicting and enhancing results, but it is the breakage, the variable that connects all the activities of the mining process from the point of view [...] Read more.

Over the years, various models have been developed in the stages of the mining process that have allowed predicting and enhancing results, but it is the breakage, the variable that connects all the activities of the mining process from the point of view of costs (drilling, blasting, loading, hauling, crushing and grinding). To improve this process, we have designed and developed a computational model based on an Artificial Neural Network (ANN), the same that was built using the most representative variables such as the properties of explosives, the geomechanical parameters of the rock mass, and the design parameters of drill-blasting. For the training and validation of the model, we have taken the data from a copper mine as reference located in the north of Chile. The ANN architecture was of the supervised type containing: an input layer, a hidden layer with 13 neurons and an output layer that includes the sigmoid activation function with symmetrical properties for optimal model convergence. The ANN model was fed-back in its learning with training data until it becomes perfected, and due to the experimental results obtained, it is a valid prediction option that can be used in future blasting of ore deposits with similar characteristics using the same representative variables considered. Therefore, it constitutes a valid alternative for predicting rock breakage, given that it has been experimentally validated, with moderately reliable results, providing higher correlation coefficients than traditional models used, and with the additional advantage that an ANN model provides, due to its ability to learn and recognize collected data patterns. In this way, using this computer model we can obtain satisfactory results that allow us to predict breakage in similar scenarios, providing an alternative for evaluating the costs that this entails as a contribution to the work. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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14 pages, 1065 KiB

Open AccessArticle

Mathematical Modeling for Prediction Dynamics of the Coronavirus Disease 2019 (COVID-19) Pandemic, Quarantine Control Measures

by Din Prathumwan, Kamonchat Trachoo and Inthira Chaiya

Symmetry 2020, 12(9), 1404; https://doi.org/10.3390/sym12091404 - 24 Aug 2020

Cited by 25 | Viewed by 4373

Abstract

A mathematical model for forecasting the transmission of the COVID-19 outbreak is proposed to investigate the effects of quarantined and hospitalized individuals. We analyze the proposed model by considering the existence and the positivity of the solution. Then, the basic reproduction number [...] Read more.

A mathematical model for forecasting the transmission of the COVID-19 outbreak is proposed to investigate the effects of quarantined and hospitalized individuals. We analyze the proposed model by considering the existence and the positivity of the solution. Then, the basic reproduction number

(R_{0})

—the expected number of secondary cases produced by a single infection in a completely susceptible population—is computed by using the next-generation matrix to carry out the stability of disease-free equilibrium and endemic equilibrium. The results show that the disease-free equilibrium is locally asymptotically stable if

R_{0} < 1

, and the endemic equilibrium is locally asymptotically stable if

R_{0} > 1

. Numerical simulations of the proposed model are illustrated. The sensitivity of the model parameters is considered in order to control the spread by intervention strategies. Numerical results confirm that the model is suitable for the outbreak that occurred in Thailand. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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14 pages, 20199 KiB

Open AccessArticle

Hybrid Modelling and Sliding Mode Control of Semi-Active Suspension Systems for Both Ride Comfort and Road-Holding

by Ayman Aljarbouh and Muhammad Fayaz

Symmetry 2020, 12(8), 1286; https://doi.org/10.3390/sym12081286 - 03 Aug 2020

Cited by 20 | Viewed by 4175

Abstract

Rigorous model-based design and control for intelligent vehicle suspension systems play an important role in providing better driving characteristics such as passenger comfort and road-holding capability. This paper investigates a new technique for modelling, simulation and control of semi-active suspension systems supporting both [...] Read more.

Rigorous model-based design and control for intelligent vehicle suspension systems play an important role in providing better driving characteristics such as passenger comfort and road-holding capability. This paper investigates a new technique for modelling, simulation and control of semi-active suspension systems supporting both ride comfort and road-holding driving characteristics and implements the technique in accordance with the functional mock-up interface standard FMI 2.0. Firstly, we provide a control-oriented hybrid model of a quarter car semi-active suspension system. The resulting quarter car hybrid model is used to develop a sliding mode controller that supports both ride comfort and road-holding capability. Both the hybrid model and controller are then implemented conforming to the functional mock-up interface standard FMI 2.0. The aim of the FMI-based implementation is to serve as a portable test bench for control applications of vehicle suspension systems. It fully supports the exchange of the suspension system components as functional mock-up units (FMUs) among different modelling and simulation platforms, which allows re-usability and facilitates the interoperation and integration of the suspension system components with embedded software components. The concepts are validated with simulation results throughout the paper. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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14 pages, 3453 KiB

Open AccessArticle

Discretization Algorithm for Incomplete Economic Information in Rough Set Based on Big Data

by Xiangyang Li and Yangyang Shen

Symmetry 2020, 12(8), 1245; https://doi.org/10.3390/sym12081245 - 28 Jul 2020

Cited by 2 | Viewed by 1875

Abstract

Discretization based on rough sets is used to divide the space formed by continuous attribute values with as few breakpoint sets as possible, while maintaining the original indistinguishable relationship of the decision system, so as to accurately classify and identify related information. In [...] Read more.

Discretization based on rough sets is used to divide the space formed by continuous attribute values with as few breakpoint sets as possible, while maintaining the original indistinguishable relationship of the decision system, so as to accurately classify and identify related information. In this study, a discretization algorithm for incomplete economic information in rough set based on big data is proposed. First, the algorithm for filling-in incomplete economic information based on deep learning is used to supplement the incomplete economic information. Then, based on breakpoint discrimination, the algorithm for discretization in the rough set is used to implement the discretization based on rough set for supplementary economic information. The performance of this algorithm was tested using multiple sets of data and compared with other algorithms. Experimental results show that this algorithm is effective for discretization based on a rough set of incomplete economic information. When the number of incomplete economic information rough candidate breakpoints increases, it still has a higher computational efficiency and can effectively improve the integrity of incomplete economic information, and finally the application performance is superior. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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16 pages, 2946 KiB

Open AccessArticle

An Improved Fast Affine Motion Estimation Based on Edge Detection Algorithm for VVC

by Weizheng Ren, Wei He and Yansong Cui

Symmetry 2020, 12(7), 1143; https://doi.org/10.3390/sym12071143 - 08 Jul 2020

Cited by 9 | Viewed by 3186

Abstract

As a newly proposed video coding standard, Versatile Video Coding (VVC) has adopted some revolutionary techniques compared to High Efficiency Video Coding (HEVC). The multiple-mode affine motion compensation (MM-AMC) adopted by VVC saves approximately 15%-25% Bjøntegaard Delta Bitrate (BD-BR), with an inevitable increase [...] Read more.

As a newly proposed video coding standard, Versatile Video Coding (VVC) has adopted some revolutionary techniques compared to High Efficiency Video Coding (HEVC). The multiple-mode affine motion compensation (MM-AMC) adopted by VVC saves approximately 15%-25% Bjøntegaard Delta Bitrate (BD-BR), with an inevitable increase of encoding time. This paper gives an overview of both the 4-parameter affine motion model and the 6-parameter affine motion model, analyzes their performances, and proposes improved algorithms according to the symmetry of iterative gradient descent for fast affine motion estimation. Finally, the proposed algorithms and symmetric MM-AMC flame of VTM-7.0 are compared. The results show that the proposed algorithms save 6.65% total encoding time on average, which saves approximately 30% encoding time of affine motion compensation. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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12 pages, 2162 KiB

Open AccessArticle

Model and Solution of Complex Emergency Dispatch by Multiple Rescue Centers with Limited Capacity to Different Disaster Areas

by Zaipeng Duan, Yueling Huang, Ping Huang, Jin Guo, Fuqiang Yang and Libi Fu

Symmetry 2020, 12(7), 1138; https://doi.org/10.3390/sym12071138 - 08 Jul 2020

Cited by 2 | Viewed by 1585

Abstract

A disaster emergency consists of many unfavorable factors, such as different disaster areas, the limited capacity of the rescue centers, and complex rescue conditions. After taking into account the resources of the rescue centers, the ability of rescue teams, and the distance between [...] Read more.

A disaster emergency consists of many unfavorable factors, such as different disaster areas, the limited capacity of the rescue centers, and complex rescue conditions. After taking into account the resources of the rescue centers, the ability of rescue teams, and the distance between the rescue centers and the disaster areas, this paper has established a complex model for multiple centers with limited capacity to dispatch teams for emergencies in different disaster areas. The model is solved by the genetic algorithm. Firstly, the paper takes the rescue task as the subunit to perform integer programming. Secondly, a rule is designed according to the symmetry of parents’ crossing. According to the rule, single parent crossover only allows two situations, (1) different rescue mission for the same rescue center and (2) different rescue centers under the same rescue mission. Finally, the performance of parent crossing and symmetric single parent crossing is compared. The results show that the two algorithms can converge to the optimal solution, but each of them has unique advantages in terms of convergence speed and stability. It is suggested that the strategy of the single-parent crossover should be used to deal with local emergency responses and that the two-parent crossover strategy is be used for more complicated global emergency responses. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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13 pages, 2930 KiB

Open AccessArticle

Method for Retrieving Digital Agricultural Text Information Based on Local Matching

by Yue Song, Minjuan Wang and Wanlin Gao

Symmetry 2020, 12(7), 1103; https://doi.org/10.3390/sym12071103 - 02 Jul 2020

Cited by 1 | Viewed by 1473

Abstract

In order to improve the retrieval results of digital agricultural text information and improve the efficiency of retrieval, the method for searching digital agricultural text information based on local matching is proposed. The agricultural text tree and the query tree are constructed to [...] Read more.

In order to improve the retrieval results of digital agricultural text information and improve the efficiency of retrieval, the method for searching digital agricultural text information based on local matching is proposed. The agricultural text tree and the query tree are constructed to generate the relationship of ancestor–descendant in the query and map it to the agricultural text. According to the retrieval method of the local matching, the vector retrieval method is used to calculate the digital agricultural text and submit the similarity between the queries. The similarity is sorted from large to small so that the agricultural text tree can output digital agricultural text information in turn. In the case of adding interference information, the recall rate and precision rate of the proposed method are above 99.5%; the average retrieval time is between 4s and 6s, and the average retrieval efficiency is above 99%. The proposed method is more efficient in information retrieval and can obtain comprehensive and accurate search results, which can be used for the rapid retrieval of digital agricultural text information. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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12 pages, 208 KiB

Open AccessArticle

Organizational Quality Specific Immune Maturity Evaluation Based on Continuous Interval Number Medium Operator

by Qiang Liu, Huiya Hu and Yu Guo

Symmetry 2020, 12(6), 918; https://doi.org/10.3390/sym12060918 - 02 Jun 2020

Cited by 2 | Viewed by 1584

Abstract

This study sets immune theory as breakthrough points, introduces immune theory into organizational quality management scope with a view to evaluating and enhancing organizational quality specific immune maturity symmetrically and permanently. This study establishes an evaluation index system of organizational quality specific immune [...] Read more.

This study sets immune theory as breakthrough points, introduces immune theory into organizational quality management scope with a view to evaluating and enhancing organizational quality specific immune maturity symmetrically and permanently. This study establishes an evaluation index system of organizational quality specific immune maturity and constructs a quality specific immune maturity evaluation and decision-making model based on an immune perspective. Further we used symmetrical methods of a continuous interval number median operator and multiple attribute decision making to carry out empirical analysis. The median idea is introduced, and the points in the 1/2 position of the basic interval monotone function are selected in evaluation and decision-making calculation by continuous interval number medium operator method. Empirical analysis research can avoid the influence of extreme value, provide new ideas and methods for effective evaluation and decision making of organizational quality specific immune maturity. The outcomes of this study have important practical significance for enhancing organizational quality specific immune maturity of equipment manufacturing enterprises. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

13 pages, 1751 KiB

Open AccessArticle

Fault Recovery Path Analysis of a Software Dynamic Image Based on a Fuzzy Control Algorithm

by Tuqian Zhang

Symmetry 2020, 12(6), 897; https://doi.org/10.3390/sym12060897 - 01 Jun 2020

Cited by 1 | Viewed by 1500

Abstract

In order to improve the ability of software dynamic image fault detection, a software dynamic image fault recovery path detection algorithm based on a fuzzy control algorithm is proposed. A software dynamic image fault signal model of a software dynamic image fault was [...] Read more.

In order to improve the ability of software dynamic image fault detection, a software dynamic image fault recovery path detection algorithm based on a fuzzy control algorithm is proposed. A software dynamic image fault signal model of a software dynamic image fault was constructed by adopting an embedded feature extraction and a fuzzy control algorithm, and the dynamic image fault signal of the embedded software under the multi-load was subjected to frequency spectrum decomposition and blind source separation. The method comprises the following steps: (1) carrying out noise reduction processing on a software dynamic image fault signal by adopting a multi-dimensional wavelet decomposition method, (2) carrying out wavelet entropy feature extraction on the software dynamic image fault signal of the noise reduction output, and (3) combining the wavelet structural feature recombination method to carry out the recombination of the software dynamic image fault feature. The high-order spectral characteristic of the software dynamic image fault signal was extracted and the high-order spectral characteristic of the extracted embedded software dynamic image fault recovery path was automatically matched, and the automatic identification and detection of the fault part of the software dynamic image was realized. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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19 pages, 1640 KiB

Open AccessArticle

Revenue Sharing of a TOT Project in China Based on Modified Shapley Value

by Yanhua Du, Jun Fang, Jingxiao Zhang and Jun Hu

Symmetry 2020, 12(6), 882; https://doi.org/10.3390/sym12060882 - 29 May 2020

Cited by 3 | Viewed by 2138

Abstract

In recent years, China’s government has encouraged the adoption of the TOT (Transfer-Operate-Transfer) model to realize the marketization of China’s public service stock projects. The TOT model is a cooperation mechanism through sharing investment, revenue and risks between the government and private partner. [...] Read more.

In recent years, China’s government has encouraged the adoption of the TOT (Transfer-Operate-Transfer) model to realize the marketization of China’s public service stock projects. The TOT model is a cooperation mechanism through sharing investment, revenue and risks between the government and private partner. Therefore, a fair and reasonable revenue sharing method (RSM) is the key to the success of the TOT project. This paper aims to provide a fair and reasonable RSM based on a modified Shapley value with a triangular symmetric fuzzy structure element, which has better motivation, flexibility, forecasting function and dynamic precise distribution function. According to the factors that affect revenue sharing, the Shapley value is improved with initial correction coefficient composed of investment ratio, risk-sharing ratio, execution degree, and fuzzy payment to achieve fairness and reasonableness. The methodology is illustrated by a case study of a TOT project selected from Laohekou city of Hubei province, China. The results testify that the revenue-sharing ratios of participants is positively correlated with the initial correction coefficient, which make the RSM more motivating; and the Shapley value with fuzzy payment by using triangular symmetric fuzzy element function make the RSM more flexible, and it has both forecasting function and precise dynamic distribution function under project revenue uncertainty. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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22 pages, 2083 KiB

Open AccessArticle

Model Reduction for Kinetic Models of Biological Systems

by Neveen Ali Eshtewy and Lena Scholz

Symmetry 2020, 12(5), 863; https://doi.org/10.3390/sym12050863 - 25 May 2020

Cited by 8 | Viewed by 3317

Abstract

High dimensionality continues to be a challenge in computational systems biology. The kinetic models of many phenomena of interest are high-dimensional and complex, resulting in large computational effort in the simulation. Model order reduction (MOR) is a mathematical technique that is used to [...] Read more.

High dimensionality continues to be a challenge in computational systems biology. The kinetic models of many phenomena of interest are high-dimensional and complex, resulting in large computational effort in the simulation. Model order reduction (MOR) is a mathematical technique that is used to reduce the computational complexity of high-dimensional systems by approximation with lower dimensional systems, while retaining the important information and properties of the full order system. Proper orthogonal decomposition (POD) is a method based on Galerkin projection that can be used for reducing the model order. POD is considered an optimal linear approach since it obtains the minimum squared distance between the original model and its reduced representation. However, POD may represent a restriction for nonlinear systems. By applying the POD method for nonlinear systems, the complexity to solve the nonlinear term still remains that of the full order model. To overcome the complexity for nonlinear terms in the dynamical system, an approach called the discrete empirical interpolation method (DEIM) can be used. In this paper, we discuss model reduction by POD and DEIM to reduce the order of kinetic models of biological systems and illustrate the approaches on some examples. Additional computational costs for setting up the reduced order system pay off for large-scale systems. In general, a reduced model should not be expected to yield good approximations if different initial conditions are used from that used to produce the reduced order model. We used the POD method of a kinetic model with different initial conditions to compute the reduced model. This reduced order model is able to predict the full order model for a variety of different initial conditions. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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15 pages, 4115 KiB

Open AccessArticle

Forecasting of Coalbed Methane Daily Production Based on T-LSTM Neural Networks

by Xijie Xu, Xiaoping Rui, Yonglei Fan, Tian Yu and Yiwen Ju

Symmetry 2020, 12(5), 861; https://doi.org/10.3390/sym12050861 - 23 May 2020

Cited by 11 | Viewed by 3259

Abstract

Accurately forecasting the daily production of coalbed methane (CBM) is important forformulating associated drainage parameters and evaluating the economic benefit of CBM mining. Daily production of CBM depends on many factors, making it difficult to predict using conventional mathematical models. Because traditional methods [...] Read more.

Accurately forecasting the daily production of coalbed methane (CBM) is important forformulating associated drainage parameters and evaluating the economic benefit of CBM mining. Daily production of CBM depends on many factors, making it difficult to predict using conventional mathematical models. Because traditional methods do not reflect the long-term time series characteristics of CBM production, this study first used a long short-term memory neural network (LSTM) and transfer learning (TL) method for time series forecasting of CBM daily production. Based on the LSTM model, we introduced the idea of transfer learning and proposed a Transfer-LSTM (T-LSTM) CBM production forecasting model. This approach first uses a large amount of data similar to the target to pretrain the weights of the LSTM network, then uses transfer learning to fine-tune LSTM network parameters a second time, so as to obtain the final T-LSTM model. Experiments were carried out using daily CBM production data for the Panhe Demonstration Zone at southern Qinshui basin in China. Based on the results, the idea of transfer learning can solve the problem of insufficient samples during LSTM training. Prediction results for wells that entered the stable period earlier were more accurate, whereas results for types with unstable production in the early stage require further exploration. Because CBM wells daily production data have symmetrical similarities, which can provide a reference for the prediction of other wells, so our proposed T-LSTM network can achieve good results for the production forecast and can provide guidance for forecasting production of CBM wells. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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11 pages, 2012 KiB

Open AccessArticle

Equilibrium Selection under the Bayes-Based Strategy Updating Rules

by Changheng Zhao and Jiaying Li

Symmetry 2020, 12(5), 739; https://doi.org/10.3390/sym12050739 - 05 May 2020

Cited by 58 | Viewed by 2919

Abstract

In this paper, first, an evolutionary game model for Bayes-based strategy updating rules was constructed, in which players can only observe a signal that reveals a strategy type instead of the strategy type directly, which deviates from the strategy type of players. Then, [...] Read more.

In this paper, first, an evolutionary game model for Bayes-based strategy updating rules was constructed, in which players can only observe a signal that reveals a strategy type instead of the strategy type directly, which deviates from the strategy type of players. Then, the equilibrium selection of populations in the case of the asymmetric game, the Battle of the Sexes (BoS), and the case of a symmetric coordination game was studied where individuals make decisions based on the signals released by each player. Finally, it was concluded that in the BoS game, when the accuracy of the signal is low, the population eventually reaches an incompatible state. If the accuracy of the signal is improved, the population finally reaches a coordinated state. In a coordination game, when the accuracy of the signal is low, the population will eventually choose a payoff-dominated equilibrium. With the improvement of signal accuracy, the equilibrium of the final selection of the population depends on its initial state. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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15 pages, 7298 KiB

Open AccessArticle

Parameter Adjustment Strategy and Experimental Development of Hydraulic System for Wave Energy Power Generation

by Wei Zhang

Symmetry 2020, 12(5), 711; https://doi.org/10.3390/sym12050711 - 02 May 2020

Cited by 66 | Viewed by 3674

Abstract

This paper develops the dynamic response of a hydrolic-transmission system of wave-power devices under random wave conditions. Through theoretical calculation and experiment analysis, the mathematical model of the hydrolic-transmission system was built to make clear which parameters are related to electric-energy output. The [...] Read more.

This paper develops the dynamic response of a hydrolic-transmission system of wave-power devices under random wave conditions. Through theoretical calculation and experiment analysis, the mathematical model of the hydrolic-transmission system was built to make clear which parameters are related to electric-energy output. The working characteristics of the main parameters are developed through the designed experimental platform. The charging pressure of the accumulator, which affects the rigidity of the hydrolic-transmission system, is analyzed. The throttle valve opening and symmetrical electric loads, which affect the stability and efficiency of the electric energy output, are analyzed. Thus, the energy output curve under different parameter regulations is drawn. Through the orthogonal experimental method, the law curve is further modified, the design principle of hydraulic system parameters under the sea level condition is established, and the optimal design scheme and regulation strategy to the hydraulic conversion system of the power generation device is obtained, to solve the problem that the multiparameter coupling cannot be adjusted quickly and effectively. The energy regulation response mechanism of the hydrolic-transmission system in the wave energy power-generation system is proved. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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21 pages, 5866 KiB

Open AccessArticle

Research of Wireless Congestion Control Algorithm Based on EKF

by Hui Wang, Junyong Tang and Bo Hong

Symmetry 2020, 12(4), 646; https://doi.org/10.3390/sym12040646 - 17 Apr 2020

Cited by 4 | Viewed by 2911

Abstract

The random variation of bandwidth in wireless networks causes some significant challenges to the congestion control protocols based on bandwidth estimation. In this paper, a wireless congestion control scheme based on extended Kalman filtering and bandwidth (CSEKB) is proposed. The CSEKB can effectively [...] Read more.

The random variation of bandwidth in wireless networks causes some significant challenges to the congestion control protocols based on bandwidth estimation. In this paper, a wireless congestion control scheme based on extended Kalman filtering and bandwidth (CSEKB) is proposed. The CSEKB can effectively perceive the bandwidth oscillation of wireless networks and distinguish the type of packet loss by establishing a noise perception factor. According to the congestion factor, the congestion control parameters are adjusted to correspondingly improve the performance of the wireless network. Moreover, the variation trend of the size of the congestion window presents a law of similar normal distribution curve, which has a certain degree of local symmetry. The CSEKB was implemented in Network simulator 3 (NS3) and compared with TCP Westwood (TCPW), CUBIC, and extended Kalman filtering-based bandwidth estimation (EBE). Through extensive simulation studies, the proposed CSEKB demonstrated the significant performance in wireless networks. First, the CSEKB can achieve congestion control based on the accurate prediction of available bandwidth, and improve average throughput and link utilization. In addition, the CSEKB has good fairness and friendliness compared with several other well-known congestion control methods. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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14 pages, 741 KiB

Open AccessArticle

Predicting Hidden Danger Quantity in Coal Mines Based on Gray Neural Network

by Hongze Zhao, Qiao He, Zhao Wei and Lilin Zhou

Symmetry 2020, 12(4), 622; https://doi.org/10.3390/sym12040622 - 15 Apr 2020

Cited by 9 | Viewed by 2155

Abstract

The hidden danger is the direct cause of coal mine accidents, and the number of hidden dangers in a certain area not only reflects the current safety situation, but also determines the development trend of safety production in this area to a large [...] Read more.

The hidden danger is the direct cause of coal mine accidents, and the number of hidden dangers in a certain area not only reflects the current safety situation, but also determines the development trend of safety production in this area to a large extent. By analyzing the formation and development law of the hidden dangers and hidden danger accident-induced mechanism in coal mines, it is concluded that there are some objective laws in the process of occurrence, development, weakening, and even stabilization of hidden dangers in a certain area. The development of the number of hidden dangers for a coal mine generally presents the law of similar normal distribution curve, with a certain degree of partial symmetry. Many years of hidden danger elimination in coal mines will accumulate large-scale hidden danger data. In this paper, by using the average value of hidden danger quantity in consecutive months to weaken the oscillation of hidden danger quantity sequence, and combining with gray model (1,1) and the neural network of extreme learning machine, and employing big data of hidden dangers available, a hidden danger quantity prediction model based on the gray neural network was established, and the experimental analysis and verification carried out. The results show that the model can achieve good prediction effect on the number of hidden dangers in a coal mine, which not only reflects the complex gray system behavior of hidden dangers of a coal mine, but also can predict dynamically. The safety management efficiency and emergency capacity of the coal mine enterprise will be greatly improved. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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14 pages, 1294 KiB

Open AccessArticle

Evaluating Performance of Software Durability through an Integrated Fuzzy-Based Symmetrical Method of ANP and TOPSIS

by Suhel Ahmad Khan, Mamdouh Alenezi, Alka Agrawal, Rajeev Kumar and Raees Ahmad Khan

Symmetry 2020, 12(4), 493; https://doi.org/10.3390/sym12040493 - 26 Mar 2020

Cited by 43 | Viewed by 2413

Abstract

Acceptance of any new approach by the organizations depends upon the users’ needs. Currently, reducing the cost and time invested in maintenance is a major challenge for the practitioners. Moreover, symmetrical and optimal maintenance is the need of the hour and it can [...] Read more.

Acceptance of any new approach by the organizations depends upon the users’ needs. Currently, reducing the cost and time invested in maintenance is a major challenge for the practitioners. Moreover, symmetrical and optimal maintenance is the need of the hour and it can be achieved by increasing the durability of software. Many attributes of the quality may affect the durability of the software and identification of durability attributes is a crucial task at the early stage of software development. Thus, it is a problem that contains multi-criteria within it. With the help of quantitative estimation, software durability may be assessed symmetrically and increased. In this row, the authors of this article have attempted to posit an effective technique to assess the durability of software. Based on empirical data through research, the presenters of this article suggest that fuzzy-based symmetrical method of Analytic Network Process (ANP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) would be an accurate methodology for assessing the durability of software. For determining the efficacy of this assessment, the researchers took six alternative software of a University. The results, as presented in this paper, would serve as guidelines for the practitioners who aim at achieving the preferred software durability. Full article

(This article belongs to the Special Issue Mathematical Modeling and Computational Methods in Science and Engineering II)

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