Assessment of Rough Set Theory in Relation to Risks Regarding Hydraulic Engineering Investment Decisions
Abstract
:1. Introduction
2. Knowledge Theory Based on the Rough Set
2.1. Information System and Decision Table
2.2. Upper Approximation and Low Approximation
2.3. Reduction and the Core of Attribute
2.4. Knowledge Acquisition
2.5. Dependency of Knowledge
- (1)
- When IND(P) ⊆ IND(Q), knowledge Q depends on knowledge P;
- (2)
- When P⟹ Q and Q⟹P, knowledge P and Q are equal and this is recorded as P≡Q; when P ⟹Q and Q ⟹P are not available at the same time, P and Q are independent. Only when IND(P)⊆IND(Q), P⟹Q. We provide the knowledge dependency measure, k, k = |rp(Q) = posP(Q)|\|U|, and state that Q is k(0 ≤ k ≤ 1), and only depends on P. This is recorded as P. When K = 1, knowledge Q fully depends on knowledge P. When k = 1, knowledge Q does not fully depend on knowledge P. The value of K can be used for deciding the dependency relationship between the decision attribute and the condition attribute. In the concrete application of rough set knowledge theory, some knowledge cannot be completely concluded, but can be measured by the dependency of knowledge [31,32].
3. Application Steps Based on the Knowledge Theory of the Rough Set
- (1)
- Initialize the domain and carry out the defect processing of data and the discrete normalization of attribute values. In the process of generating the decision table T, the division criterions of discrete areas provided by the field experts should be used for selecting the proper break point to divide the spaces formed by the condition attributes so as to reduce the search space, and the decision rule table T(U,A,C,D) [34] is obtained after strict data preprocessing.
- (2)
- Attribute reduction: items with the same attributes are removed, and repeated attribute values are combined into one item.
- (3)
- Relative simplification of knowledge: investigate whether all condition attributes in C cannot be neglected, and after obtaining the new simplification set, investigate whether the condition attributes in it cannot be neglected. Then, all D simplification sets of C can be acquired, and the decision table is simplified according to the different simplification sets.
- (4)
- Arrange and simplify the decision tables. Investigate all decision rules, work out the D simplification of the elementary category of every decision rule, and divide the decision rules into a plurality of decision rules according to differences of D simplification.
- (5)
- Merge members in the decision table after simplification and obtain the decision algorithm.
4. Application and Research of the Theory of the Rough Set
- CNFT1 = (a∨b∨d)∧(a∨b∨c∨d)∧(a∨b∨c∨d)∧(a∨b∨c)∧(a∨b∨c)∧(b∨c)= (a∨b∨d)∧(b∨c)
- CNFT2 = (a∨c∨d)∧(c∨d)∧(a∨b∨c∨d)∧(a∨c∨d)∧(b∨c∨d)∧(a∨b∨c∨d)
- CNF = (a∨c)∧CNFT6 = a∧b∧d
- (1)
- a3d2∨a3d1∨a3b3→e1
- (2)
- a1d1∨b2d1∨b1→e2
- (3)
- d3∨a2b3∨a1d2→e3
- (1)
- When the construction expense of hydraulic engineering or the external influence or construction expense is low but the financial income is high, the investment in the construction project can be selected;
- (2)
- When the expense of the hydraulic construction project is low and the external influence is common or the financial expense is common, if the external influence is low or the financial income is high, the investment can be delayed;
- (3)
- When the construction strategic benefit of hydraulic engineering is low, the financial benefit is common or the construction expense is common, the decision of no investment can be selected.
5. Conclusions
- (1)
- The investment in the construction of hydraulic engineering relates to various uncertain factors, and after being tested, compared with those of other investment methods, the rule acquired based on the method of the rough set for the information excluded from the decision time is hidden; thus, the adaptability is higher, and high precision can be acquired.
- (2)
- To acquire the rule of the investment decision regarding hydraulic engineering, the rough set method relates more condition attributes and the figure-expressing mode cannot be easily formed; thus, its application is not as direct as that of the common figure of investment decisions.
- (3)
- The data processed by the rough set method are discrete. Common methods cannot solve the discrete phenomenon of data and, as a result, are not able to acquire scientific conclusions.
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Investment Project | Construction Expense | Financial Income | Strategy Benefit | External Influence | Investment Decision | |
---|---|---|---|---|---|---|
Project Evaluation Standard | ||||||
a1 | 500 | 200 | 690 | 150 | Delayed investment | |
a2 | 700 | 470 | 650 | 440 | No investment | |
a3 | 300 | 410 | 500 | 280 | No investment | |
a4 | 200 | 455 | 550 | 290 | Investment | |
a5 | 250 | 260 | 490 | 105 | Delayed investment | |
a6 | 510 | 380 | 430 | 130 | Delayed investment | |
a7 | 350 | 550 | 255 | 145 | Investment | |
a8 | 650 | 600 | 570 | 120 | No investment |
A\U | a | b | c | d | e |
---|---|---|---|---|---|
1 | 2 | 1 | 3 | 1 | 2 |
2 | 3 | 2 | 3 | 3 | 3 |
3 | 1 | 2 | 2 | 2 | 3 |
4 | 3 | 2 | 2 | 2 | 1 |
5 | 2 | 1 | 2 | 1 | 2 |
6 | 1 | 2 | 2 | 1 | 2 |
7 | 3 | 3 | 1 | 1 | 1 |
8 | 2 | 3 | 2 | 1 | 3 |
A\U | a | b | d | e |
---|---|---|---|---|
1 | 2 | 1 | 1 | 2 |
2 | 3 | 2 | 3 | 3 |
3 | 1 | 2 | 2 | 3 |
4 | 3 | 2 | 2 | 1 |
5 | 2 | 1 | 1 | 2 |
6 | 1 | 2 | 1 | 2 |
7 | 3 | 3 | 1 | 1 |
8 | 2 | 3 | 1 | 3 |
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Qu, J.; Bai, X.; Gu, J.; Taghizadeh-Hesary, F.; Lin, J. Assessment of Rough Set Theory in Relation to Risks Regarding Hydraulic Engineering Investment Decisions. Mathematics 2020, 8, 1308. https://doi.org/10.3390/math8081308
Qu J, Bai X, Gu J, Taghizadeh-Hesary F, Lin J. Assessment of Rough Set Theory in Relation to Risks Regarding Hydraulic Engineering Investment Decisions. Mathematics. 2020; 8(8):1308. https://doi.org/10.3390/math8081308
Chicago/Turabian StyleQu, Jihong, Xiao Bai, Jiajun Gu, Farhad Taghizadeh-Hesary, and Ji Lin. 2020. "Assessment of Rough Set Theory in Relation to Risks Regarding Hydraulic Engineering Investment Decisions" Mathematics 8, no. 8: 1308. https://doi.org/10.3390/math8081308