人工神经网络发展回顾与分析

Oleksandr Bilokon
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引用次数: 0

摘要

介绍。如果不了解有关人工神经网络的科学思想的分析和发展过程,就不可能创建智能网络物理系统。本文的主要任务是研究和分析基于人工神经网络的智能技术的概念。关于人工神经网络知识的创造、形成和发展的特性的知识对科学家、开发人员和设计工程师来说是特别重要的。本文由以下部分组成:首先,重点介绍了构建人工大脑功能问题的不同方法,这些方法的观点依次分为单型模型和基因型模型。第二部分是对人工智能系统发展的分析,介绍了人工智能系统发展过程中的一些事实,并对人工神经网络问题的科学观点的特点进行了澄清。考虑了各种概念和观点,借助这些概念和观点,可以再现计算过程,以便更详细地分析和综合智能系统的算法。在关于理论状态的部分,关注的重点是无法获得准确分析答案的研究人员在科学工具包中添加了数字机器或机械模型的实验建模方法。此外,需要注意的是,该模型不是研究的结果,而只是分析其行为的起点。在人工神经网络部分,作者涉及到以下几个概念:McCulloch和Pitts在神经网络中的计算逻辑,分配置信系数的问题,自组织原理,这首先是在计算机模拟的帮助下说明的,竞争学习原理,Kohonen自组织图,考虑径向基函数的直接传播的多层网络,它成为多层感知器,支持向量机的替代方案。作为结论和结果,作者收到了智能系统的起源和人工神经网络技术的完整画面。科学思想的发展过程使我们对人工神经网络构建的智能技术的特点、功能和计算的特点有了清晰的认识。关键词:人工神经网络,感知器,McCulloch-Pitts理论,智能计算机系统,网络物理代理,移动机器人,机器人技术
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Review and Analysis of the Development of Artificial Neural Networks
Introduction. The creation of intelligent cyber-physical systems is impossible without knowledge of the analysis and process of development of scientific thought regarding artificial neural networks. The main task of this article is research and analysis of the concept of intelligent technologies based on artificial neural networks. Knowledge of the peculiarities of the creation, formation, and development of knowledge about artificial neural networks is of particular importance for scientists, developers, and design engineers. The article consists of the following parts: first, different approaches to the problem of building artificial functions of the brain are highlighted, the views of which are, in turn, divided into monotypic and genotypic models. The next part is the analysis of the development of artificial intelligence systems, some facts of the process of the development of the artificial intelligence system are also introduced and the peculiarities of scientific opinion on the issues of artificial neural networks are clarified. Various concepts and views are considered, with the help of which it is possible to reproduce the calculation process for a more detailed analysis and synthesis of algorithms of intelligent systems. In the part about the state of the theory, attention is focused on the fact that researchers who could not get accurate analytical answers add to the scientific toolkit methods of experimental modeling either on digital machines or on mechanical models. In addition, it is noted that the model is not the result of research, but only a starting point for analyzing its behavior. In the part of artificial neural networks, the author touches on the following concepts: the logic of McCulloch and Pitts calculations in neural networks, the problems of assigning confidence coefficients, the principle of self-organization, which were first illustrated with the help of computer simulations, the principle of competitive learning, the Kohonen Self-Organizing Maps, multilayer networks of direct propagation taking into account the radial basis functions, which became an alternative to the multilayer perceptron, the support vector machine. As conclusions and as a result, the author receives a complete picture of the genesis of intelligent systems and the technology of artificial neural networks. The processes of development of scientific thought give a clear understanding of the features of intellectual technologies built with the help of artificial neural networks, features of functioning and calculation. Keywords: artificial neural networks, perceptron, theories of McCulloch-Pitts, intelligent computer systems, cyber-physical agent, mobile robot, robotics.
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