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This paper proposes a novel ensemble methodology comprising an auto regressive integrated moving average, artificial neural network, fuzzy inference system model, adaptive neuro fuzzy inference system, support vector regression, extreme machine learning, and genetic algorithm to forecast aggregated, longterm energy demand. The genetic algorithm designs controllers and setpoints by repeated application of a simulator. Download neural networks fuzzy logic and genetic algorithm or read online books in pdf, epub, tuebl, and mobi format. This paper discusses the design of neural network and fuzzy logic controllers using genetic algorithms, for realtime control of flows in sewerage networks. This chapter introduces the basic concepts and concrete methodologies of fuzzy systems, neural networks, and genetic algorithms to prepare the readers for the following chapters.
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