Analysis and Simulation of Geomagnetic Map Suitability Based on Vague Set

2016 ◽  
Vol 69 (5) ◽  
pp. 1114-1124 ◽  
Author(s):  
Lihui Wang ◽  
Le Yu ◽  
Nan Qiao ◽  
Desheng Sun
Keyword(s):  
Membership Function ◽  
Evaluation Method ◽  
Score Function ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Vague Set ◽  
Weighted Score ◽  
Optimisation Model ◽  
Optimal Area ◽  
The Membership Function

An evaluation method named vague set is proposed to describe the suitability of a geomagnetic map. It is based on the Fuzzy Decision Making (FDM) method, and overcomes the FDM model's shortcomings that favouring and opposing content cannot be taken into account simultaneously. The membership function and non-membership function are used to define the influence of the geomagnetic map parameters on map suitability, including standard deviation, information entropy, roughness and slope variance. The weight of each geomagnetic map parameter is calculated by establishing an optimisation model. Vague set data are divided into four types after classification, and Weighted Score Function Values (WSFVs) of matching areas are obtained by using the Weighted Score Function (WSF) method. Then, WSFV of each matching area are compared to select an optimal area. Simulation results demonstrate that geomagnetic map suitability is positively proportional to the function value, and matching error is negatively proportional to the WSFV of the matching area.

scholarly journals Dual Extended Hesitant Fuzzy Sets

Symmetry ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 714 ◽  
Author(s):  
José Carlos R. Alcantud ◽  
Gustavo Santos-García ◽  
Xindong Peng ◽  
Jianming Zhan
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Natural Extension ◽  
Score Function ◽  
Hesitant Fuzzy Set ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Hesitant Fuzzy Sets ◽  
Weight Score ◽  
Decision Making Problem

Hesitant fuzzy sets extend fuzzy sets by considering many-valued sets of membership degrees. Real applications validate this model and decision making approaches of various forms permit to act in a flexible manner. If we can avail ourselves of hesitant information on non-membership degrees too, then dual hesitant fuzzy sets provide a natural extension of both hesitant fuzzy sets and intuitionistic fuzzy sets. This article defines the concept of dual extended hesitant fuzzy set as the combination of extended hesitant fuzzy sets with dual hesitant fuzzy sets. Its basic algebraic properties are set forth, and the model is linked to other successful models in the literature. We also define a comparison law for the prioritization of elements described in this new framework. Moreover, we present an algorithm to solve the dual extended hesitant fuzzy decision making problem by a weight score function. Finally, the feasibility of this approach is demonstrated by the evaluation of big data industries with an effectiveness test.

scholarly journals Optimization Model of Fuzzy Rule Based Expert System Using Max-Min Composition and Schema Mapping Translation

INSIST ◽  
2017 ◽  
Vol 2 (1) ◽  
pp. 30 ◽  
Author(s):  
Hartono Hartono ◽  
Tiarma Simanihuruk
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Expert System ◽  
Membership Function ◽  
Fuzzy Rule ◽  
Fuzzy Decision Making ◽  
Schema Mapping ◽  
Fuzzy Decision ◽  
Rule Based ◽  
Knowledge Based

Abstract— Fuzzy Decision Making involves a process of selecting one or more alternatives or solutions from a finite set of alternatives which suits a set of constraints. In the rule-based expert system, the terms following in the decision making is using knowledge based and the IF Statements of the rule are called the premises, while the THEN part of the rule is called conclusion. Membership function and knowledge based determines the performance of fuzzy rule based expert system. Membership function determines the performance of fuzzy logic as it relates to represent fuzzy set in a computer. Knowledge Based in the other side relates to capturing human cognitive and judgemental processes, such as thinking and reasoning. In this paper, we have proposed a method by using Max-Min Composition combined with Genetic Algorithm for determining membership function of Fuzzy Logic and Schema Mapping Translation for the rules assignment.Keywords— Fuzzy Decision Making, Rule-Based Expert System, Membership Function, Knowledge Based, Max-Min Composition, Schema Mapping Translation

scholarly journals A Cultural and Functional Approach to the Assessment of Logical Thinking Ability in English Writing

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Cao Juan
Keyword(s):  
Influencing Factors ◽  
Membership Function ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Fuzzy Mathematics ◽  
Logical Thinking ◽  
English Writing ◽  
Thinking Ability ◽  
And Function ◽  
The Membership Function

The analysis of influencing factors of logical thinking ability in English writing is the key effective factor of evaluating logical thinking ability in English writing. In order to accurately evaluate logical thinking ability in English writing, this paper studies the evaluation method of logical thinking ability in English writing from the perspective of culture and function. This paper analyzes the relationship between the influencing factors of logical thinking ability in English writing. The factors of text structure and language expression reflect the culture and function of logical thinking ability in English writing, respectively, which have a direct impact on logical thinking ability in English writing. From these two aspects, 15 evaluation indexes are selected to construct the evaluation system of logical thinking ability in English writing. Considering the significant fuzziness of logical thinking ability in English writing from the perspective of culture and function, the comprehensive evaluation method of fuzzy mathematics is used for the process, the evaluation criteria are determined, the evaluation matrix is constructed, and the membership function is calculated, to complete the comprehensive evaluation of fuzzy mathematics based on the membership function and weight matrix. The experimental results show that this method can accurately evaluate the logical thinking ability of English writing and can be effectively used in the area of research.

scholarly journals FUZZY DECISION MAKING METHOD BASED ON COCOSO WITH CRITIC FOR FINANCIAL RISK EVALUATION

2020 ◽  
Vol 26 (4) ◽  
pp. 695-724 ◽  
Author(s):  
Xindong Peng ◽  
Haihui Huang
Keyword(s):  
Decision Making ◽  
Risk Evaluation ◽  
Financial Risk ◽  
Score Function ◽  
Fuzzy Decision Making ◽  
Financial Risks ◽  
The Novel ◽  
Fuzzy Decision ◽  
Subjective Preference ◽  
Criteria Importance

The financial risk evaluation is critically vital for enterprises to identify the potential financial risks, provide decision basis for financial risk management, and prevent and reduce risk losses. In the case of considering financial risk assessment, the basic problems that arise are related to strong fuzziness, ambiguity and inaccuracy. q-rung orthopair fuzzy set (q-ROFS), portrayed by the degrees of membership and non-membership, is a more resultful tool to seize fuzziness. In this article, the novel q-rung orthopair fuzzy score function is given for dealing the comparison problem. Later, the and operations are explored and their interesting properties are discussed. Then, the objective weights are calculated by CRITIC (Criteria Importance Through Inter-criteria Correlation). Moreover, we present combined weights that reflects both subjective preference and objective preference. In addition, the q-rung orthopair fuzzy MCDM (multi-criteria decision making) algorithm based on CoCoSo (Combined Compromise Solution) is presented. Finally, the feasibility of algorithm is stated by a financial risk evaluation example with corresponding sensitivity analysis. The salient features of the proposed algorithm are that they have no counter-intuitive case and have a stronger capacity in differentiating the best alternative.

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