针对交换式工业以太网的数据通信特点，采用遗传算法来寻找其网络划分问题的次优解。
Considering the communication characteristics of switched industrial Ethernet, genetic algorithms are used to find near-optimal solution for its network partition problem.
神经网络对于解决模式识别问题来说，可以实现特征空间较复杂的划分，适合于高速并行处理系统来实现。
To solve the pattern recognition problems, the neural network can achieve the involved demarcate of earmark space, and it cut out for high acceleration and parallel systems to achieve.
针对河流-三角洲储层沉积微相划分问题，提出了一种基于加权模糊推理神经网络的判别方法。
Focusing on the classification of sedimentary microfacies in fluvial delta reservoir, one diagnosis based on weighted fuzzy neural network is proposed.
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