近年来，以模糊控制和神经网络控制相结合的软计算技术获得了广泛关注。
The combination of fuzzy and ANN control as soft computing has gained widely concern in recent years.
粗糙集理论是一种新的处理模糊和不确定性知识的软计算工具，在人工智能及认知科学等众多领域已经得到了广泛的应用。
Rough set theory is emerging as a powerful tool for dealing with vagueness and uncertainty of facts, which has important applications to artificial intelligence and cognitive science.
本论文对包含遗传算法、模糊逻辑控制和神经网络的软计算的智能控制及其几种不同结合方式做了较为系统的研究。
In this thesis, soft computing based control algorithms including genetic algorithms (GA), fuzzy control, neural networks (NN) and their different combinations are discussed systematically.
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