许多其他的人工智能技术也被应用到这类程序中，例如神经网络，遗传算法和协同计算。
There are many other AI techniques that can be implemented and tried in a Chess program, such as neural networks, genetic algorithms, and collaborative computing.
说实话，在计算机科学的一些主要分支学科的命名上就可以看出生物学的影子，譬如人工神经网络，遗传算法和进化计算法等等。
Indeed, the names of major subfields of computer science-such as artificial neural networks, genetic algorithms, and evolutionary computation-attest to the influence of biological analogies.
结果表明，将神经网络和遗传算法用于结构损伤识别是有效的、可行的。
The results show that the NN and GA can be used in structural damage identification system effectively.
根据大坝监测数据在时序上变化特征，应用了神经网络和基于遗传算法的时间序列的非线性预测模型。
Founded on change speciality of series of dam safety monitoring forecast, artificial neural networks and nonlinear models of time series based on genetic algorithms are applied.
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.
用神经网络计算遗传算法的适应度，对结构进行优化。
Using BP neural networks, the fitness of GA was calculated, on the basis of which the mechanical structure was optimized.
将BP神经网络和遗传算法相结合运用于快速设计的结构优化问题。
BP neural networks and GA were applied to the optimal design of mechanical structure.
针对人工神经网络的不足，本研究将遗传算法引入神经网络，实现两种算法的优势互补。
For solving the shortage of ANN, this paper introduces GA into it, USES the two operators alternately, thus accomplishes dominance complement of the two intellect optimization algorithms.
探讨了人工神经网络和遗传算法在酶法提取绿豆渣水溶性纤维素工艺优化方面的应用。
The application of artificial neural network-genetic algorithm in optimization of extraction process of soluble fiber from mungbean residue was studied.
神经网络建模和遗传算法优化是求解工程优化问题的一种行之有效的方法。
It is an efficient method to solve engineering optimization problems with neural networks and genetic algorithms.
由于粗神经网络的误差传递函数不可微，所以采用遗传算法来训练粗神经网络。
Because the error transfer function of rough neural network is not differentiable, genetic algorithms are applied for training the network.
由于粗神经网络的误差传递函数不可微，所以采用遗传算法来训练粗神经网络。
Because the error transfer function of rough neural network is not differentiable, genetic algorithms are applied for training the network.
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