Research Paper On Fuzzy Logic

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In this paper, research work done in process modeling and control using conventional techniques, Artificial Neural Networks, Fuzzy Logic and Neuro-Fuzzy paradigms is discussed.

For each control methodology its corresponding limitations are also presented.

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International Journal of Database Theory and Application, 8(1), pp.235-244. This paper presents a review on application of Artificial Neural Network and Fuzzy Logic in process modeling and control.The intelligent control techniques are rapidly replacing the conventional control due to their abilities like learning, function approximation, associative memory, prediction, combinatorial optimization and non-linear system modeling etc. Multiple attribute decision making: Methods and application. A hybrid approach based on SERVQUAL and fuzzy TOPSIS for evaluating banking service quality. Institutional determinants of citizen evaluations of democracy. Bin, Z., Jingsha, H., Na, H., Yixuan, Z., Shiyi, Z. Designs Q Simulations of Multi-factor in Trust Evaluation. Political and gender oppression as a cause of poverty. Methodology/Approach: The methodology is based on fuzzy logic and the degree of similarity to ideal solutions. The information is obtained through the application of a structured survey based on the European Social Survey to the Ecuadorian society. The analysis is based on eight different dimensions of satisfaction, namely: (1) Life; (2) Economy; (3) City Government; (4) Transparency; (5) Education; (6) Health System; (7) Roads; and (8) National Government. Quality of life indices assessment for disabled and elderly people: Case study of Tehran. Findings: The results obtained help different stakeholders to have important insights about how the citizens’ quality of life and satisfaction depend to some extent on important public services that form the pillars of the social welfare, education and health system. A hybrid approach based on SERVQUAL and fuzzy TOPSIS for evaluating transportation service quality.


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