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Aiming at the optimal scheduling problem of byproduct gas system in steel industry, a knowledge and mathematical programming-based optimal scheduling method is proposed in this study. On one hand, a fuzzy model is designed to extract the expert scheduling knowledge from the historical data of the industrial process. And then, a great deal of scheduling knowledge is employed to compose a fuzzy rules...
This paper proposes a classification algorithm based on simplified fuzzy rules base combining fuzzy clustering with rough set. Firstly, generates fuzzy rules base using fuzzy clustering from numerical sample dates, and then simplifies the sample attributions using rough set theory, deletes the redundant rules, and gets the simplified fuzzy rules base, in order to make classification decision conveniently...
This paper presents definitions of a fuzzy knowledge system and fuzzy logic formulae. Information entropies of the fuzzy logic formulae and information entropies of fuzzy rules of the fuzzy knowledge system are described, and relative properties of these definitions are discussed. And then, classification and evaluation of the siso fuzzy system are given based on the information entropy. Finally,...
In e-commerce applications, the magnitude of products and the diversity of venders cause confusion and difficulty for common consumers to choose the right product from a trustworthy vender. Although people have recognized the importance of feedbacks and reputations for the trustworthiness of individual venders and products, they still have difficulties when they have to make a shopping decision from...
The method was studied about traffic flow prediction by using subtractive clustering for fuzzy neural network model of phase-space reconstruction. The prediction model of traffic flow must be established to satisfy the intelligent need of high precision through analyzing problems of the existing predicting methods in chaos traffic flow time series and the demand of uncertain traffic system. Based...
Fuzzy interpolative reasoning is an inference technique for dealing with the sparse rules problem in sparse fuzzy-rule-based systems. In this paper, we present a new fuzzy interpolative reasoning method for sparse fuzzy-rule-based systems based on the areas of fuzzy sets. The proposed method uses the weighted average method to infer the fuzzy interpolative reasoning results and has the following advantages:...
This paper presents an assisted living system for elderly people. The assisted living key areas comfort, safety and health are defined and discussed. A strategy is elaborated which mainly uses standard home automation sensors. The solution is based on the transformation of sensor signals by automata and fuzzy rules to detect safety-or health-critical situations. The role of comfort as an enabling...
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