本文应用基于遗传算法的模糊神经网络方法，建立了科研项目立项评审的智能管理系统。
An approach to the technology with fuzzy systems, neural networks and genetic algorithms is given.
此外，通过遗传算法对模糊神经网络的学习速率和惯性系数等进行了优化，为控制系统实现最优控制提供了有力保证。
In addition, the paper makes use of Genetic Algorithms to optimize learning rates and inertia coefficients of Fuzzy-neural network, which can ensure that the controller achieves optimization control.
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.
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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