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Quantum Evolutionary Algorithm (QEA) is an optimization algorithm based on the concept of quantum computing and Particle Swarm Optimization (PSO) algorithm is a population based intelligent search technique. Both these techniques have good performance to solve optimization problems. PSEQEA combines the PSO with QEA to improve the performance of QEA and it can solve single objective optimization problem...
This paper proposes a new approach based on Quantum Evolutionary Algorithm (QEA) for effective selection and definition of fuzzy if-then rules to design Fuzzy Logic Controllers (FLCs). The majority of works done on designing FLCs were based on knowledgebase derived from imprecise heuristic knowledge of experienced operators or persons but they were difficult and time consuming to evaluate. The proposed...
In many real-world applications, the accurate number of clusters in the data set may be unknown in advance. In addition, clustering criteria are usually high dimensional, nonlinear and multi-model functions and most existing clustering algorithms are only able to achieve a clustering solution that locally optimizes them. Therefore, a single clustering criterion sometimes fails to identify all clusters...
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