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Knowledge reduction is an important problem in rough set theory. In this paper, an improved measurement is given to measure the roughness of rough set. Based on improved rough entropy, reduction theory and algorithm design are studied. Additionally, appling the weight's idea in fuzzy theory, the conditional attribute weight in the decision table is investigated. Combing the conditional attribute weight...
The gas outburst forecasts model is brought forward in this paper. Firstly, rough set requires discrimination data, considering distributed information of class, and continual condition attributes are discredited adopting information entropy theory. On the basis of that, redundancy attributes are eliminated using rough set reduction algorithm. Reduction attributes and rules are gained. Finally, through...
In this paper, we Use the knowledge of information entropy and mutual information in rough set theory, a new comprehensive evaluation method is proposed which is aimed to improve the decision-making precision of analytic hierarchy process. This method begins with constructing an objective judgement matrix by attribute significance defined by information entropy, and then getting a combinatorial judgement...
A new fuzzy multi-objective decision-making model based on vague set theory and entropy method is presented in this paper. In the proposed model, the alternative schemes are weighted evaluation according to the integrated vague value of its elements relative to the ideal scheme. In order to calculate attributes weights objectively and accurately, a modified entropy weights calculation formula is proposed...
In order to make the design plan better reflecting the user requirement, and change the design manner from experience-driven to performance-driven design of the hydraulic press, a method of calculating the correlation between the user requirement and hydraulic press performance is proposed;Map between them is established by use of rough set theory. The result shows that this method can reflect the...
Because of D-S combination rule has disadvantage in dealing with high confliction between evidences, this paper, from the view of random set, discusses an information decision-making method based on the information entropy. Finally, this paper's method is applied to an example of actual fault diagnosis of wind turbine generating units and compares it with D-S combination rule, validating the feasibility...
Grey cluster decision-making is an important part of grey system theory. And 2-tuple linguistic assessment resolves the calculation problems of the result of expert qualitative linguistic assessment. But both of them not mention how to calculate the weight of index. Based on the definitions of entropy, a method of getting weight is proposed, and considers the character of grey cluster decision-making...
Selection of suppliers is the precondition and foundation of supply chain operation. It is an important aspect to choose the best supplier for supply chain management. This paper is aimed to present a fuzzy decision-making approach to deal with the supplier selection problem in supply chain system. During recent years, how to determine suitable suppliers in the supply chain has become a key strategic...
As the development of knowledge economic, human resource has been the core of the world economic. So searching the reasonable evaluating and managing methods becomes one of the hot issues which have been concerned by people. Traditional evaluating methods of human resource are simple and direct, but they greatly depend on people's subjective judgement and experience. In order to overcome the default,...
Product design case databases contain a lot potential knowledge, which can tell us the relations among parameters and some interesting experience patterns. While designing product, it is supposed to support the designers to make decisions better. Therefore many researchers are trying to find an effective approach to discover the unknown knowledge. In this paper, we presented several algorithms which...
Fault diagnosis is a complex problem that concerns effective decision-making. Carrying out timely system diagnosis whenever a failure symptom is detected would help to reduce system maintenance time and improve the overall productivity. However, with the increased complexity of equipments, the task of fault diagnosis has become increasingly difficult and its complexity almost unmanageable using traditional...
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