通过利用合理的学习算法进行训练，神经网络对事物和环境具有很强的自学习、自适应和自组织能力。
Carries on the training through the use reasonable study algorithm, the neural network has to the thing and the environment very strong from the study, auto-adapted and from the organization ability.
该方法有效地应用了神经网络的泛化能力以及自组织自适应的学习功能，且通过对网络输入结点的设计，能够很好地解决复杂航迹关联问题。
This algorithm solves the problem of complex correlation by the node's design of neural network's input based on application of extensive ability effectively and effective study ability of itself.
通过利用合理的学习算法进行训练，神经网络对事物和环境具有很强的自学习、自适应和自组织能力。
After training with a proper learning algorithm, NN has a capability of self-learning, adapting and organizing.
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.
应用推荐