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This work presents a metaheuristic hybrid optimization technique developed to synthesize frequency selective surface (FSS) structures, composed of triangular patch elements and printed on FR-4 dielectric substrates for microwave filtering applications. The optimization technique is based on the combination of genetic algorithm (GA) and Multilayer Perceptron (MLP) artificial neural network (ANN). The...
This paper introduces a hybrid evolutionary optimization algorithm as a tool for training an Artificial Neural Network used for production forecasting of solar energy PV plants. This hybrid technique is developed in order to exploit in the most effective way the uniqueness and peculiarities of two classical optimization approaches, Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). This...
In this paper, a new method has been prospered to generate fuzzy rules using a GA-BP FNN algorithm for seismic reservoir fuzzy rules extraction. This method aims to combine the advantages of FS, ANN, and GA algorithms and to remedy their drawbacks. The hybrid algorithm can optimize not the number of rules but the membership functions of the premise and the outputs layer weighs by adopting multi-encoding...
In order to rapidly optimize superheater model parameters to achieve the required precision, ANN and GA are combined to solve the problem. Since the classic optimization methods are not appropriate for mechanism model in power plant simulator, GA is applied to optimize model parameters. Input data, output data of model and optimized parameters are normalized to make learning sample. After ANN is trained...
Nozzle plays very important role to control the gas flow during the interruption for SF6 circuit breaker (CB). Due to the higher non-linear global mapping relationship between interruption performance of SF6 CB and its nozzle structural parameters, artificial neural network (ANN) and genetic algorithm (GA) were applied to the nozzle parameter optimization of SF6 CB on the basis of the non-linear mapping...
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