UAV Decision-making System Based on the Rough Set theory and the Optimal Genetic Algorithm

Author(s):  
Wendi Sun ◽  
Mingrui Hao
2019 ◽  
Vol 20 (1) ◽  
pp. 61-77
Author(s):  
Li Zhang ◽  
Xulu Xue

Abstract “Rough set” is a theory put forward by the polish scholar Z. Pawlak, which is a useful mathematics tool for dealing with vague and uncertain information. Rough set theory can achieve a subset of all attribute which preserves the discernible ability of original features, by using the data only with no additional information. As a typical system of multi-agent, the decision-making system of soccer robot has the features of multi-layered, antagonism, and cooperation. On the bases of rough set theory, this paper established a decision making system with complete information for soccer robot, and then reduce the condition and decision attributes and their values, to get the simply decision rules. On the otherwise, considering the situation of information loss, we study decision making of imperfect information system, extract the decision rules and calculate the reliability, so that the rules can assist the agent to make right decision in competition. The simulation result shows that the algorithm is correct and effective.


2021 ◽  
Author(s):  
Liting Jing ◽  
Junfeng Ma

Abstract With the advancement of new technologies and diverse customer-centered design requirements, the medical device design decision making becomes challenge. Incorporating multiple stakeholders’ requirements into the medical device design will significantly affect the market competitiveness and performance. The classic design decision making approaches mainly focused on design criteria priority determination and conceptual schemes evaluation, which lack the capacity of reflecting the interdependence of interest among stakeholders and capturing the ambiguous influence on the overall design expectations, leading to the unreliable decision making results. In order to relax these constraints in the medical device design, this paper incorporates rough set theory with cooperative game theory model to develop a novel user-centered design decision making framework. The proposed approach is composed of three components: 1) end/professional user needs identification and classification, 2) evaluation criteria correlation diagram and scheme value matrix establishment using rough set theory; and 3) fuzzy coalition utility model development to obtain optimal desirability considering users’ conflict interests. We used a blood pressure meter case study to demonstrate and validate the proposed approach. Compared with the traditional Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach, the proposed approach is more robust.


Kybernetes ◽  
2016 ◽  
Vol 45 (3) ◽  
pp. 461-473 ◽  
Author(s):  
Sun Bingzhen ◽  
Ma Weimin

Purpose – The purpose of this paper is to present a new method for evaluation of emergency plans for unconventional emergency events by using the soft fuzzy rough set theory and methodology. Design/methodology/approach – In response to the problems of insufficient risk identification, incomplete and inaccurate data and different preference of decision makers, a new model for emergency plan evaluation is established by combining soft set theory with classical fuzzy rough set theory. Moreover, by combining the TOPSIS method with soft fuzzy rough set theory, the score value of the soft fuzzy lower and upper approximation is defined for the optimal object and the worst object. Finally, emergency plans are comprehensively evaluated according to the soft close degree of the soft fuzzy rough set theory. Findings – This paper presents a new perspective on emergency management decision making in unconventional emergency events. Also, the paper provides an effective model for evaluating emergency plans for unconventional events. Originality/value – The paper contributes to decision making in emergency management of unconventional emergency events. The model is useful for dealing with decision making with uncertain information.


2011 ◽  
Vol 14 (04) ◽  
pp. 715-735
Author(s):  
Wen-Rong Jerry Ho

The main purpose of this paper is to advocate a rule-based forecasting technique for anticipating stock index volatility. This paper intends to set up a stock index indicators projection prototype by using a multiple criteria decision making model consisting of the cluster analysis (CA) technique and Rough Set Theory (RST) to select the important attributes and forecast TSEC Capitalization Weighted Stock Index. The projection prototype was then released to forecast the stock index in the first half of 2009 with an accuracy of 66.67%. The results point out that the decision rules were authenticated to employ in forecasting the stock index volatility appropriately.


2018 ◽  
Vol 8 (9) ◽  
pp. 1545
Author(s):  
Noor Rehman ◽  
Syed Shah ◽  
Abbas Ali ◽  
Sun Jang ◽  
Choonkil Park

Decision making is a cognitive process for evaluating data with certain attributes to come up with the best option, in terms of the preferences of decision makers. Conflicts and disagreements occur in most real world problems and involve the applications of mathematical tools dealing with uncertainty, such as rough set theory in decision making and conflict analysis processes. Afterwards, the Pawlak conflict analysis model based on rough set theory was established. Subsequently, Deja put forward some questions that are not answered by the Pawlak conflict analysis model and Sun’s model. In the present paper, using the notions of soft preference relation, soft dominance relation, and their roughness, we analyzed the Middle East conflict and answered the questions posed by Deja in a good manner.


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