采用神经网络与遗传算法相结合的方法，用黑箱模型计算催化精馏过程，并进行了全局优化；
A method, which combined neural network and genetic algorithms, was employed to simulate the catalytic distillation process by black box model and optimize the operational parameters.
由于动态神经网络结构及权值确定困难，采用二进制与实数编码相结合的联合编码，用遗传算法优化得到神经网络结构及对应权值。
To rise above the difficulty of determining NN's structure and weights, the GA optimization algorithm is used to get them by combining binary encoding with real encoding.
说明用神经网络模型描述微囊制作参数与性能之间的关系，用遗传算法优化微囊制作工艺参数，能设计出性能最佳的微囊制作工艺参数。
The optimum process parameters could be obtained using ANN model to describe relationships between process parameters and performance and GA to optimize process parameters.
由于它们在特性上有许多共同性和互补性，将遗传算法、神经网络与模糊逻辑相结合的研究已成为当前的研究热点之一。
The research on combinations of genetic algorithms, neural network and fuzzy logic is attracting the attention of many researchers because of many common and complementary features among them.
本文与一般的基于遗传算法的神经网络设计相比，提出一个新型算子——BP算子，并对神经网络的权值和结构同时优化。
Compared with general ANN design, this paper puts forward a new operator, BP operator, and optimizes the ANN's initial weights and structure at the same time.
遗传算法、神经网络与模糊控制是当前人工智能中的主要研究领域。
Genetic Algorithms, Neural Network and Fuzzy Control are important research fields in artificial intelligence.
将有限元分析与试验设计、神经网络、遗传算法等结合起来对该变截面梁结构进行了抗撞性优化设计。
The relationships between energy absorption and the proposed variables are revealed and the optimal results are verified through the finite element analysis of thin-walled rail's collision.
将有限元分析与试验设计、神经网络、遗传算法等结合起来对该变截面梁结构进行了抗撞性优化设计。
The relationships between energy absorption and the proposed variables are revealed and the optimal results are verified through the finite element analysis of thin-walled rail's collision.
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