Neural nets are also supposed to learn.
神经网络也可假定为可以学习。
Artificial Neural Nets became a hot topic in research on Artificial Intelligence in the 1980s.
80年代重新兴起的人工神经网络已成为世界人工智能研究的热门课题之一。
Simplifications can be useful, especially when they serve as a model, in this case, for implementing cybernetic neural nets.
在这个例子中，对于实现控制神经网络而言，简化可以是实用的，尤其是当它们被作为模型来使用时。
An artificial neural nets based on-line implementation to enhance power system transient stability by reconstruction is studied.
对如何借助人工神经网络理论在线实施利用改构提高电力系统暂态稳定水平进行了研究。
For example, much of the work in Artificial Intelligence and neural nets would benefit from a closer connection with biological life.
举例说明，人工智能与神经元网络方面的研究可以得益于与生物生命亲密联系方面的研究。
It has the simple structure and definite physics meaning parameters as a regular PID controller, and has the self study ability as neural nets.
该控制器将神经网络和PID控制规律融为一体，既具有常规PID控制器结构简单、参数物理意义明确的优点，又具有神经网络自学习、自适应的能力。
The first step toward understanding neural nets is to abstract from the biological neuron, and to focus on its character as a threshold logic unit (TLU).
理解神经网络的第一步是从对抽象生物神经开始，并把重点放在阈值逻辑单元（TLU）这一特征上。
The structure concept and the three key technologies: sensors, actuators and artificial neural nets, which compose smart structures, are introduced and discussed.
本文对智能结构的概念、意义及组成智能结构的三大关键技术：传感器，执行器与人工神经网络进行了介绍与讨论。
Through analysis of formation cause and taking some actual observation data from a earth-rock dam, a seepage flow monitoring model was set up base on neural nets.
通过对土石坝渗流的成因分析，应用人工神经网络原理，并结合某土石坝的实测资料建立了渗流监控模型。
In many kinds of artificial neural networks, BP neural nets is one of the most pioneer and common models, it is successfully applied to equipment fault diagnosis.
在若干神经网络模型中，BP网络模型是人们认识最早、应用最广泛的一种，它也是在设备故障诊断领域应用最成功的一种神经网络模型。
With deep learning, researchers can feed huge amounts of data into software systems called neural nets that learn to recognize patterns within the vast information faster than humans.
通过深度学习技术，研究人员能够将海量数据输入“神经元网络”软件系统进行处理，该系统能够以人脑完全无法企及的速度，在海量数据中进行学习和模式分析。
This paper gave a brief review on neural nets and neural computers, neuron models, layered network structures, error back-propagation algorithm and its application to geophysical inversion.
本文简要介绍神经网络与神经计算机，神经元模型，层状网络结构，误差逆传播算法及其在地球物理反演中的应用。
A fuzzy neural networks consisting of two nets was applied to chromosome recognition in this paper.
本研究将一类模糊神经网络引入染色体识别中，并采用两级网络结构。
A fuzzy neural networks consisting of two nets was applied to chromosome recognition in this paper.
本研究将一类模糊神经网络引入染色体识别中，并采用两级网络结构。
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