遗传算法在人工神经网络中的应用综述

本文介绍正被逐渐广泛应用的新型的、随机性的全局优化方法－遗传算法,系统地讨论了遗传算法在人工神经网络中的主要应用,实验结果显示了遗传算法快速学习网络权重的能力,并且能够摆脱局部极小点的困扰。     

改进模拟退火算法在模块划分中的研究及应用

模块划分是产品模块化设计的关键技术之一。目前大多采用非数值方法划分模块，数值划分方法主要是使用模拟退火算法或遗传算法。模拟退火算法虽可以一次性得到模块划分最优方案，但是操作困难，效率不高。而遗传算法容易陷入局部最优解。该文在模拟退火算法的基础上，融入遗传算法的种群思想，提出了基于改进模拟退火算法的模块划分方法，研究了其实现的关键技术，并通过VC++6.0将其实现。通过具体的模块划分实例，证实了该方法的高效性和易操作性。     

遗传算法在人工智能领域中的应用

该文介绍了遗传算法的基本概念、基本遗传算法的特点和基本遗传算法的求解步骤,同时也介绍了遗传算法在机器学习、并行处理、人工生命以及遗传算法与进化规则及进化策略的结合的发展动向,最后讨论了基于遗传算法的人工神经网络学习中的应用研究,具体论述了遗传算法在学习神经网络权重和学习神经网络拓扑结构的应用方法。     

模拟退火遗传算法在车间作业调度中的应用

研究车间作业调度系统,使资源达到优化配置.针对提高产品质量,缩短周期,传统遗传算法应用于车间作业调度过程中易出现收敛速度慢、易陷入局部最优,导致作业调度效率极低.为了提高车间作业调度的效率,提出一种模拟退火遗传算法的车间作业调度方法.在遗传算法种群更新过程引入模拟退火机制,防止早熟现象的产生,使种群在更新迭代过程中保持了多样性,加快了收敛速度,克服遗传算法过早收敛的缺陷.采用的SA-GA算法能够在最短时间找作业调度的最优解,对30个车间作业调度标准测试案例进行了仿真.仿真结果表明,使相对平均误差降低了4.6%,极大的提高了车间作业调度效率,验证了在实际生产中应用的可行和优越性.     

人工智能在传感器领域的应用

人工智能作为一门正在迅速发展的学科，已被广泛地应用于传感器领域。人工智能与传感器技术相结合构成新型的智能传感器，提高了传感器的智能水平，是智能传感器发展的一个方向。简要介绍了人工智能的四个分支：模糊逻辑、人工神经网络、专家系统、遗传算法在传感器领域的应用。     

神经网络及遗传算法在径流预报中的应用

提出用遗传算法和BP算法相结合的改进神经网络模型来进行径流预报。即先通过遗传算法对初始权值分布进行优化,在解空间定位出一个较好的搜索空间,然后采用BP算法,在这个较小的解空间中搜索出最优解。使网络收敛速度加快和避免局部极小。作为实例,以清江鸭子口的实测径流资料为样本进行训练并用以预测该水文站的日径流量。结果表明,该方法具有收敛速度快和预测精度高的特点。     

基于小波降噪和LSTM的海参养殖氨氮预测

海参具有极高的营养价值和药用价值,水质环境对其产量有一定的影响。为了更好地调控水质,尽可能使海参生长在最佳状态,采用改进的小波降噪方法处理数据,建立长短期记忆(LSTM)神经网络模型对海参养殖环境中的氨氮浓度进行预测。实验分别采用多影响因素作为模型的输入,氨氮浓度作为输出,建立氨氮浓度与各水质因子之间的关系模型,实现氨氮浓度预测。实验结果表明,改进的小波降噪方法有效减少了噪声,LSTM神经网络模型在海参养殖水质预测中效果显著。所提方法为海参养殖下一步水质调控提供了参考数据,进而可提高海参养殖的质量和产量。     

改进遗传算法在移动机器人路径规划中的应用

研究机器人路径规划问题,传统的遗传算法存在早熟收敛和收敛速度慢,影响路径规划的效率,针对移动机器人路径规划的难题,为了提高路径规划的效率,提出一种基于遗传模拟退火算法的移动机器人最优路径规划方法.应用简化编码长度的技术简化了工作路径编码方式,对于基于遗传算法产生初始路径种群后的各路径的适应值进行评价.经过多次交叉、变异,并借助模拟退火中Metropolis算法的随机移动准则制定了高效的温度更新函数,获得了从起始点到目标点的一条全局最优路径,并在MAlLAB环境中进行了仿真.仿真果证明算法的收敛速度、搜索质量和最优路径规划效率都有了明显的提高.     

基于遗传算法的神经网络控制器在导航系统中的应用

目前广泛运用于神经网络中的误差反向传播训练时间较长,且易陷入局部最优。该文首次在遗传算法中使用一种新的个体选择方法,并利用遗传算法和误差反向传播算法相结合训练神经元的连接权值,能够优化控制器性能参数和全局搜索能力,在航向控制系统中的仿真数据显示比单纯误差反向传播算法误差更小。     

SAGA在测试数据自动生成中的应用

结合遗传算法（GA）的并行搜索结构和模拟退火算法（SA）的概率突跳性,并结合自适应交叉算子和遗传算子,形成了一种新的自适应SAGA混合优化算法。在测试数据自动生成系统中,经过实际程序的实验,表明该算法有更强的搜索能力,可以更快的找到全局最优解。     

Business applications of artificial intelligence knowledge based expert systems

Business organizations have shown a broad range of interest in knowledge based systems, including not only expert systems but also advisory systems, to assist experts in their tasks, and checklist systems to support clerical workers. These interests can be displayed by mapping existing and planned systems along two axes: the role a system in intended to serve and the complexity of the problem environment with which the system must deal. The maps provide a vehicle for understanding the rationales employed by businesses in making decisions to build knowledge based systems. They also provide a basis for understanding what currently is practical, and what barriers exist that will limit the future growth of business knowledge based systems.     

A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems

Nowadays, many current real financial applications have nonlinear and uncertain behaviors which change across the time. Therefore, the need to solve highly nonlinear, time variant problems has been growing rapidly. These problems along with other problems of traditional models caused growing interest in artificial intelligent techniques. In this paper, comparative research review of three famous artificial intelligence techniques, i.e., artificial neural networks, expert systems and hybrid intelligence systems, in financial market has been done. A financial market also has been categorized on three domains: credit evaluation, portfolio management and financial prediction and planning. For each technique, most famous and especially recent researches have been discussed in comparative aspect. Results show that accuracy of these artificial intelligent methods is superior to that of traditional statistical methods in dealing with financial problems, especially regarding nonlinear patterns. However, this outperformance is not absolute.     

Application of artificial intelligence in sales

Expert systems for application in computer companies have been designed and implemented inhouse by DEC in the USA. The systems help in the sales, engineering and manufacture cycle, and lower the cost of selling and implementing computers.     

Using artificial intelligence in communication system design

The authors describe a knowledge-based design support system, called KDSS, that will help designers inexperienced in communication system design easily create advanced systems like intelligent networks, and large-scale distributed computing systems. They began by designing a support system for protocol and communication software. They then experimented with applying expert-system technology in design support systems and developed an expert system for protocol synthesis called KSPS. An expert system for protocol and communication software design that is based on the earlier work is also part of KDSS     

人工智能技术在网络空间安全防御中的应用

如何及时处理海量网络态势信息并有效应对动态演化的网络攻击是网络空间安全防御面临的主要挑战,人工智能技术由于具有传统方法所不具备的智能特性,近年来在网络空间安全防御中得到了广泛的关注,并取得了大量的研究成果。综述了近年来神经网络、多Agent系统以及专家系统等人工智能技术在网络空间安全防御中的主要应用和方法,分析比较了它们各自的应用特点,给出了未来研究与发展的趋势。     

Application of artificial intelligence notions in structural optimization programs

The main obstacle against the wider application of mathematical programming methods (MPM) in structural design is long computing time. The efficiency of MPM can be significantly improved by adopting some of the ideas used in the field of Artificial Intelligence (AI). The paper presents an application of AI notions for the improvement of the effectiveness of structural optimization programs. The key element of the presented approach is taking advantage of previous design results for the selection of initial values of decision variables and rearranging of the constraints. Basing on the presented concept, a computer program for the optimization of trusses has been developed. The AI notions proved to be quite easy to implement in the form of program modules. The numerical results of the application of AI in structural design seem very promising although some problems must still be analysed.     

人工智能在计算机网络技术中的应用分析

随着信息技术的快速发展,人工智能已成为引领新一轮科技革命和产业变革的战略性技术。现阶段,各个国家都在争先布局和发展人工智能,以期能在未来科技革命中抢占高点和先机。人工智能是一种模拟人脑工作的技术形式,它包含系统推荐、人工神经网络、语言处理、机器学习等方面的内容。将人工智能应用于计算机网络技术,可以节省人力资源、提升效率,可较好地弥补当前计算机网络技术在运用过程中存在的不足,进一步提升计算机网络技术水平。     

Argumentation in artificial intelligence

Over the last ten years, argumentation has come to be increasingly central as a core study within Artificial Intelligence (AI). The articles forming this volume reflect a variety of important trends, developments, and applications covering a range of current topics relating to the theory and applications of argumentation. Our aims in this introduction are, firstly, to place these contributions in the context of the historical foundations of argumentation in AI and, subsequently, to discuss a number of themes that have emerged in recent years resulting in a significant broadening of the areas in which argumentation based methods are used. We begin by presenting a brief overview of the issues of interest within the classical study of argumentation: in particular, its relationship—in terms of both similarities and important differences—to traditional concepts of logical reasoning and mathematical proof. We continue by outlining how a number of foundational contributions provided the basis for the formulation of argumentation models and their promotion in AI related settings and then consider a number of new themes that have emerged in recent years, many of which provide the principal topics of the research presented in this volume.