Fuzzy Logic With Engineering Applications Third Edition Solution Manual
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A Fuzzy interference system (FIS) is developed to support the decision making process. The developed FIS contains a knowledge base and a fuzzy inference engine. The knowledge base contains information regarding the problem, its domains, its variables, and the possible solution. The fuzzy inference engine is used to compute the interference strength between the input and the various rules in the knowledge base. The developed FIS can be used to find the best possible solution to the problem with respect to its objectives and constraints.
The main objective of this thesis is to provide a novel and efficient approach, in the form of a fuzzy inference system (FIS), for predicting and evaluating the performance of landfill covers. A FIS is proposed for solving the problem of predicting the performance of landfill covers based on the inputs of land use, cover type and cover specification. The FIS employs the fuzzy set theory to model the uncertainty present in the prediction problem. A multi-sensor data fusion method is proposed based on the fuzzy inference system approach to predict the landfill cover performance. The applicability and performance of the FIS is validated using some real data from an actual landfill site and the results are compared with the results obtained from the traditional regression models such as a nonlinear regression model and a feed-forward neural network model.
In this study, the aim is to develop a fuzzy inference system (FIS) as a tool for decision-making in order to design an optimum strategy for waste water management practices. The main issue is to find an optimum strategy to minimize the cost, while decreasing the harmful effects to the environment. The soft computing technique of fuzzy inference system is adopted in this study. The research method used is a proposed hybrid approach of discrete and fuzzy optimization which has been applied in various research areas and is now used in this study. The results of this study have shown the effectiveness of the proposed method and the developed FIS in finding the optimal solution to the problem of waste water management. The developed FIS is found to be useful as an aid to a decision maker.
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