神经网络计算机能模拟人脑的并行处理方式，具有惊人的自学习、思维、推理、判断和记忆的功能。
Neutral network computer can simulate human brains in parallel information processing manner, with functions of striking self-learning, thinking, reasoning, judging, and memorizing.
神经网络具有自学习，自适应，并行处理的能力，但结构的选择缺乏理论依据。
Neural network have the abilities of self-learning, adapt and parallel management, but the structural selection lacks academic bases.
神经网络则具有非线性映射、自学习能力、分布存储能力及并行处理信息等优点。
The neural networks have many advantages such as nonlinear map, self-learning, distributional memory, parallel processing and so on.
它的潜在并行性及自组织、自适应、自学习的智能特性对于求解多目标优化问题具有巨大的潜力。
Due to its intrinsic parallelism, self-organizing, adaptation and self-learning intelligent properties, evolutionary computation has large potential to solve multiple objectives optimal solutions.
它的潜在并行性及自组织、自适应、自学习的智能特性对于求解多目标优化问题具有巨大的潜力。
Due to its intrinsic parallelism, self-organizing, adaptation and self-learning intelligent properties, evolutionary computation has large potential to solve multiple objectives optimal solutions.
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