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Modelling and Analysis of Neuro Fuzzy Employee Ranking System in the Public Sector^{ †}

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*Fuzzy Systems and Data Mining VIII: Proceedings of FSDM*2022.

## Abstract

**:**

## 1. Introduction

## 2. Related Work and Contributions

## 3. Methodology

#### 3.1. ANFIS

- Layer 1: In the fuzzification layer, every node i in this layer is a square node with a node function:$${O}_{i}^{1}={u}_{{A}_{i}}\left(x\right)$$
- Layer 2: Circle nodes in the normalisation layer multiply the incoming signals and send the product out. This represents the firing strength of a rule.$${w}_{i}={u}_{{A}_{i}}\left(x\right){u}_{{B}_{i}}\left(y\right),i=1,2$$
- Layer 3: Every node in this layer, labelled in Figure 1 with N, calculates the average ratio of the ith rule’s firing strength.$$\overline{w}=\frac{{w}_{i}}{{w}_{1}+{w}_{2}}\phantom{\rule{4.pt}{0ex}}\mathrm{or}\phantom{\rule{4.pt}{0ex}}\mathrm{in}\phantom{\rule{4.pt}{0ex}}\mathrm{a}\phantom{\rule{4.pt}{0ex}}\mathrm{generic}\phantom{\rule{4.pt}{0ex}}\mathrm{form}:\phantom{\rule{4.pt}{0ex}}{O}_{i}^{3}={\overline{w}}_{i}=\frac{{w}_{i}}{{\sum}_{i=1}^{n}{w}_{i}},i=1,\dots ,n$$
- Layer 4: Every node “i” in this layer is a square node with a node function, where ${w}_{i}$ is the normalised firing strength from the output of Layer 3 and ${p}_{i}$, ${q}_{i}$, ${r}_{i}$ are referred to as consequent parameters.
- Layer 5: The final layer represents the overall output y of the network as the summation of all incoming signals:$${O}_{i}^{5}=f=\sum _{i}{\overline{w}}_{l}{f}_{i}=\frac{{\sum}_{i}{w}_{i}{f}_{i}}{{\sum}_{i}{w}_{i}}$$$$f=\frac{{\sum}_{i=1}^{n}{w}_{i}\left({p}_{i}x+{q}_{i}y+{r}_{i}\right)}{{\sum}_{i=1}^{n}{w}_{i}}$$

#### 3.2. Workflow

#### 3.3. Data Preparation

- K1: (academic skills):
- 1.
- The number of seminars related to the current work with a maximum of three $({S}_{1},{S}_{2},{S}_{3})$.
- 2.
- The number of Bachelor’s degrees with a maximum of two $({B}_{1},{B}_{2})$.
- 3.
- The availability of Master’s degrees.
- 4.
- Certification from the National School of Public Administration.
- 5.
- A Ph.D. diploma.

- K2: (work experience in the public sector):
- 1.
- Number of years with a maximum number of 35.
- 2.
- Type of responsibility.
- 3.
- Head of a small department.
- 4.
- Head of the department.
- 5.
- General manager.

- K3: (work experience in the private sector):
- 1.
- Number of years with a maximum number of 35.
- 2.
- Type of responsibility.
- 3.
- Head of a small department.
- 4.
- Head of department.
- 5.
- General manager.

- K4: (age):
- 1.
- Number of years with a range of (20–67). Greek legislation sets the age of 67 years as the limit when working in the public sector.

#### 3.4. Measuring Time

#### 3.5. Defining the Tasks in Public Organisations

#### 3.6. Assessment of Employee Quality

## 4. Experimental Results

## 5. Discussion

#### 5.1. Time Complexity of ANFIS

#### 5.2. Limitations

#### 5.3. Computing Cost and Economic Effectiveness

## 6. Conclusions and Future Work

## Author Contributions

## Funding

## Data Availability Statement

## Conflicts of Interest

## References

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Financial Request | Technical Opinion |
---|---|

Suggestion of new technical document | Draft tender design |

Committee minutes | Design of a national tender |

Primary expense claim | Design of an international tender |

Contract deployment | Implementation of a proposal for inclusion in the NSRF |

Sample No | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|

$T{F}_{PjTk}$ (min) | 149 | 106 | 81 | 319 | 209 | 157 | 208 | 171 | 129 | 138 | 180 | 338 | 197 | 208 | 115 |

$T{F}_{PjTk+1}$ (min) | 1049 | 1185 | 1090 | 739 | 900 | 946 | 1047 | 396 | 909 | 571 | 771 | 734 | 460 | 823 | 623 |

$T{F}_{PjT1}$ (min) | 53 | 74 | 47 | 25 | 21 | 29 | 31 | 44 | 66 | 46 | 54 | 86 | 43 | 63 | 42 |

Task ID | Task Weight | Task | Task ID | Task Weight | Task |
---|---|---|---|---|---|

1 | 1 | Financial request | 6 | 8 | Technical opinion |

2 | 2 | Suggestion of new technical document | 7 | 3.75 | Draft tender design |

3 | 30 | Committee minutes | 8 | 17 | Design of a national tender |

4 | 1.2 | Primary expense claim | 9 | 25 | Design of an international tender |

5 | 2 | Contract deployment | 10 | 12 | Design of a proposal for the NSRF |

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## Share and Cite

**MDPI and ACS Style**

Giotopoulos, K.C.; Michalopoulos, D.; Karras, A.; Karras, C.; Sioutas, S.
Modelling and Analysis of Neuro Fuzzy Employee Ranking System in the Public Sector. *Algorithms* **2023**, *16*, 151.
https://doi.org/10.3390/a16030151

**AMA Style**

Giotopoulos KC, Michalopoulos D, Karras A, Karras C, Sioutas S.
Modelling and Analysis of Neuro Fuzzy Employee Ranking System in the Public Sector. *Algorithms*. 2023; 16(3):151.
https://doi.org/10.3390/a16030151

**Chicago/Turabian Style**

Giotopoulos, Konstantinos C., Dimitrios Michalopoulos, Aristeidis Karras, Christos Karras, and Spyros Sioutas.
2023. "Modelling and Analysis of Neuro Fuzzy Employee Ranking System in the Public Sector" *Algorithms* 16, no. 3: 151.
https://doi.org/10.3390/a16030151