Description: 6。《非数值并行算法——遗传算法》，刘勇等着 科学出版社 1995年第一版
本书系统地叙述了非数值并行算法之一的模拟退火算法的基本原理以及最新进展，同时为了便于读者解决实际问题，书中对具体算法的步骤作了详细介绍。本书共分七章，第一章介绍算法的思想、特点。发展过程和前景。第二章介绍算法的基本理论。第三章讨论算法解连续优化问题。第四章利用算法设计和优化神经网络。第五章介绍在组合优化中的应用。第六章介绍应用遗传程序设计解决程序设计自动化问题。第七章对遗传算法和其它适应性算法进行比较。
本书可供高校有关专业的师生、科研人员、工程技术人员阅读参考。-6. "Non - numerical parallel algorithms -- Genetic Algorithm" Liu Yong waiting 520-531 1995 version of the first book to systematically describe the non - numerical parallel algorithms one count of simulated annealing Law and the basic tenets of the latest progress, in order to help readers solve practical problems, book of the specific algorithm steps in detail. The book is divided into seven chapters, the first chapter describes the idea algorithm, characteristics. The development process and prospects. The second chapter describes the basic algorithm theory. The third chapter discusses Algorithm for continuous optimization problems. Chapter IV using the algorithm design and optimization of neural networks. The fifth chapter in combinatorial optimization applications. Chapter V Platform: |
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Author:孙东 |
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Description: 8。《遗传算法及其应用》，陈国良等编着 人民邮电出版社 2001年第一版
本书系统全面地介绍了遗传算法的基本原理、设计方法及其并行实现，以及它在组合优化、机器学习、图像处理、过程控制、进化神经网络、模糊模式识别和人工生命等方面的应用。 本书可作为高等院校计算机、无线电电子学、自动控制、生物医学工程等有关专业高年级学生或研究生的教材和参考书，也可供从事人工智能、信息处理研究和应用的科技人员学习参考。-8. "Genetic algorithm and its application," Chen Guoliang edited and published with the People's Post and in 2001 the first book version of the full introduction of the genetic algorithm basic tenets , design methods and parallel implementation, and its portfolio optimization, machine learning, image processing, process control, evolutionary neural networks, Fuzzy Pattern Recognition and Artificial Life, and so on the application. The book can be used as institutions of higher learning computers, radio electronics, automatic control, biomedical engineering, and other professional grade students or graduate teaching and reference materials, are also available in artificial intelligence, information processing and application of information technology to study. Platform: |
Size: 6905064 |
Author:孙东 |
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Description: 6。《非数值并行算法——遗传算法》，刘勇等着 科学出版社 1995年第一版
本书系统地叙述了非数值并行算法之一的模拟退火算法的基本原理以及最新进展，同时为了便于读者解决实际问题，书中对具体算法的步骤作了详细介绍。本书共分七章，第一章介绍算法的思想、特点。发展过程和前景。第二章介绍算法的基本理论。第三章讨论算法解连续优化问题。第四章利用算法设计和优化神经网络。第五章介绍在组合优化中的应用。第六章介绍应用遗传程序设计解决程序设计自动化问题。第七章对遗传算法和其它适应性算法进行比较。
本书可供高校有关专业的师生、科研人员、工程技术人员阅读参考。-6. "Non- numerical parallel algorithms-- Genetic Algorithm" Liu Yong waiting 520-531 1995 version of the first book to systematically describe the non- numerical parallel algorithms one count of simulated annealing Law and the basic tenets of the latest progress, in order to help readers solve practical problems, book of the specific algorithm steps in detail. The book is divided into seven chapters, the first chapter describes the idea algorithm, characteristics. The development process and prospects. The second chapter describes the basic algorithm theory. The third chapter discusses Algorithm for continuous optimization problems. Chapter IV using the algorithm design and optimization of neural networks. The fifth chapter in combinatorial optimization applications. Chapter V Platform: |
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Author:孙东 |
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Description: 8。《遗传算法及其应用》，陈国良等编着 人民邮电出版社 2001年第一版
本书系统全面地介绍了遗传算法的基本原理、设计方法及其并行实现，以及它在组合优化、机器学习、图像处理、过程控制、进化神经网络、模糊模式识别和人工生命等方面的应用。 本书可作为高等院校计算机、无线电电子学、自动控制、生物医学工程等有关专业高年级学生或研究生的教材和参考书，也可供从事人工智能、信息处理研究和应用的科技人员学习参考。-8. "Genetic algorithm and its application," Chen Guoliang edited and published with the People's Post and in 2001 the first book version of the full introduction of the genetic algorithm basic tenets , design methods and parallel implementation, and its portfolio optimization, machine learning, image processing, process control, evolutionary neural networks, Fuzzy Pattern Recognition and Artificial Life, and so on the application. The book can be used as institutions of higher learning computers, radio electronics, automatic control, biomedical engineering, and other professional grade students or graduate teaching and reference materials, are also available in artificial intelligence, information processing and application of information technology to study. Platform: |
Size: 6904832 |
Author:孙东 |
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Description: 遗传算法是一种借鉴生物界自然选择和进化机制发展起来的高度并行、随机、自适应搜索算法。由于其具有健壮性，特别适合于处理传统搜索算法解决不好的复杂的和非线性问题。以遗传算法为核心的进化算法已与模糊系统理论、人工神经网络等一起成为计算智能研究中的热点，受到许多学科的共同关注。 本书全面系统地介绍了遗传算法的基本理论，重点介绍了遗传算法的经典应用和国内外的新-Genetic Algorithm is a kind of drawing on biological mechanisms of natural selection and evolutionary development of highly parallel, randomized, adaptive search algorithm. Due to its robustness, particularly suited to deal with traditional search algorithms are not properly solved complex and nonlinear problems. To genetic algorithms as the core of the evolutionary algorithm with fuzzy system theory, artificial neural networks, along with computational intelligence research hotspot by many subjects of common concern. This book comprehensively and systematically introduce the genetic algorithm Platform: |
Size: 6230016 |
Author:涂满园 |
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Description: 人工神经网络(Aartificial Neural Network，下简称ANN)是模拟生物神经元的结构而提出的一种信息处理方法。早在1943年，已由心理学家Warren S.Mcculloch和数学家Walth H.Pitts提出神经元数学模型，后被冷落了一段时间，80年代又迅猛兴起［1］。ANN之所以受到人们的普遍关注，是由于它具有本质的非线形特征、并行处理能力、强鲁棒性以及自组织自学习的能力。其中研究得最为成熟的是误差的反传模型算法(BP算法，Back Propagation)，它的网络结构及算法直观、简单，在工业领域中应用较多。-Artificial Neural Networks (Aartificial Neural Network, under the short title of ANN) is a simulation of the structure of biological neurons and the information put forward a method of treatment. At early 1943, by Warren S. Mcculloch psychologists and mathematicians Walth H. Pitts proposed mathematical model of neurons, was left out in the cold for some time, and the rapid rise of the 80' s [1]. ANN because the general concern of the people is the essence of it is because of the non-linear characteristics of parallel processing capabilities, strong robustness and self-organizing capacity of self-learning. Research one of the most sophisticated are the error-propagation model of the algorithm (BP algorithm, Back Propagation), its network structure and algorithm for intuitive, simple, application in the industrial field more. Platform: |
Size: 159744 |
Author:pjh |
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Description: 摘要图像特征的提取是视觉图像识别的重要方法之一，采用细胞神经网络（&’’）并行处理器进行图像特征的提取
具有实时快速的优点。该文将介绍&’’ 并行处理器的基本工作原理及其实现图像特征处理的逻辑组合通用方法，并以
图像的纹理分割与识别为例来说明&’’ 并行处理器应用于视觉图像识别的通用编程方法。-Abstract image feature extraction is a visual image to identify one of the important ways, the use of cellular neural networks for parallel processors (& ' ' ) image feature extraction with the advantages of rapid real-time. This paper will introduce & ' ' parallel processors to achieve the basic working principle and characteristics of image processing method of the logic combination of GM and image texture segmentation and recognition as an example to illustrate the application of parallel processors & ' ' visual image recognition General programming method. Platform: |
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Author:martin |
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Description: 由于人工神经网络具有大规模并行信息处理，良好的自适应与自学习
等许多特点，因此利用神经网络解决复杂非线性动态系统的预测问题就有了一条新的可能途径
-As massively parallel artificial neural network information processing, a good adaptive and self-learning and many other features, the use of neural networks to solve complex nonlinear dynamic system of prediction may have a new way Platform: |
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Author:杨利明 |
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Description: 文章介绍如何使用CUDA实现神经网络，并把他应用在GPU图像处理单元上。
-An Artificial Neural Network is an information processing method that was inspired by the way biological nervous systems function, such as the brain, to process information. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. Neural Networks have been widely used in "analogous" signal classifications, including handwriting, voice and image recognitions. Neural network can also be used in computer games. It enables games with the ability to adaptively learn from player behaviors. This technique has been used in racing games, such that opponent cars controlled by computers can learn how to drive by human players.
Since a Neural Network requires a considerable number of vector and matrix operations to get results, it is very suitable to be implemented in a parallel programming model and run on Graphics Processing Units (GPUs). Our goal is to utilize and unleash the power of GPUs to boost the performance o Platform: |
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Author:尘封 |
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Description: 人工神经网络（ArtificialNeuralNetworks，简写为ANNs）也简称为神经网络（NNs）或称作连接模型（ConnectionistModel），它是一种模范动物神经网络行为特征，进行分布式并行信息处理的算法数学模型。这种网络依靠系统的复杂程度，通过调整内部大量节点之间相互连接的关系，从而达到处理信息的目的。
-Artificial neural network (ArtificialNeuralNetworks, abbreviated as ANNs) also referred to as neural networks (NNs) or known connection model (ConnectionistModel), it is a neural network model of animal behavior characteristics, the distributed parallel algorithm for information processing model. This network relies on the complexity of the system, by adjusting the connection between the number of nodes within the relationship, so as to achieve the purpose of processing information. Platform: |
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Author:小林 |
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Description: 人工神经网络（ArtificialNeuralNetworks，简写为ANNs）也简称为神经网络（NNs）或称作连接模型（ConnectionistModel），它是一种模范动物神经网络行为特征，进行分布式并行信息处理的算法数学模型。这种网络依靠系统的复杂程度，通过调整内部大量节点之间相互连接的关系，从而达到处理信息的目的。-Artificial neural network (ArtificialNeuralNetworks, abbreviated as ANNs) are also referred to as neural networks (NNs) or known connection model (ConnectionistModel), it is a neural network model animal behavior, for distributed and parallel information processing algorithms mathematical model. Such networks rely on the complexity of the system, a large number of nodes by adjusting the internal connection between the relationship, so as to achieve the purpose of processing information. Platform: |
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Author:刘一鸣 |
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Description: Multi-step-prediction of chaotic time series based
on co-evolutionary recurrent neural network
协同进化递归神经网络的多步混沌时间序列预测-This paper proposes a co-evolutionary recurrent neural network (CERNN) for the multi-step-prediction of chaotic
time series, it estimates the proper parameters of phase space reconstruction and optimizes the structure of recurrent
neural networks by co-evolutionary strategy. The searching space was separated into two subspaces and the individuals
are trained in a parallel computational procedure. It can dynamically combine the embedding method with the capability
of recurrent neural network to incorporate past experience due to internal recurrence. The eff ectiveness of CERNN is
evaluated by using three benchmark chaotic time series data sets: the Lorenz series, Mackey–Glass series and real-world
sun spot series. The simulation results show that CERNN improves the performances of multi-step-prediction of chaotic
time series. Platform: |
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Author: |
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Description: 针对传统方法在齿轮故障诊断中可靠性不高的问题,提出了基于证据理论的混合诊断算法。
根据齿轮故障特征向量,采用两个并行的BP神经网络进行局部故障诊断,获得彼此独立的证据。再用
证据理论对各证据进行融合,最终实现对齿轮的故障诊断。实例结果表明,该方法可充分利用各种故障
的冗余和互补信息,有效地提高诊断的可信度。
关键词 证据理论 齿轮 神经网络 故障诊断
-Gear Fault Diagnosis based on Evidence Theory
Xiong Wei Cheng Jiatang Xu Shaokun
(Engineering College, Honghe University, Mengzi 661100,China)
Abstract For the reason of low-reliability exists in the gear fault diagnosis of traditional methods, a method
based on evidence theory hybrid diagnosis algorithm is presented. According to the fault feature vectors, two parallel
BP neural networks are used to carry on local fault diagnosis to acquire the independent evidences each other. Then
evidence theory is employed to fuse evidences, and gear fault diagnosis is fulfilled finally. Example shows that, vari-
ous faults redundant and complement information can be sufficiently used and the reliability of diagnosis is effectively
improved.
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Author:whb |
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Description: 齿轮箱具有传动比固定、传动转矩大、结构紧凑等
优点,是机械系统的重要部件。
-Gear Fault Diagnosis based on Evidence Theory
Xiong Wei Cheng Jiatang Xu Shaokun
(Engineering College, Honghe University, Mengzi 661100,China)
Abstract For the reason of low-reliability exists in the gear fault diagnosis of traditional methods, a method
based on evidence theory hybrid diagnosis algorithm is presented. According to the fault feature vectors, two parallel
BP neural networks are used to carry on local fault diagnosis to acquire the independent evidences each other. Then
evidence theory is employed to fuse evidences, and gear fault diagnosis is fulfilled finally. Example shows that, vari-
ous faults redundant and complement information can be sufficiently used and the reliability of diagnosis is effectively
improved.
Platform: |
Size: 63488 |
Author:whb |
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Description: 针对传统方法在齿轮故障诊断中可靠性不高的问题,提出了基于证据理论的混合诊断算法。根据齿轮故障特征向量,采用两个并行的BP神经网络进行局部故障诊断,获得彼此独立的证据。再用
证据理论对各证据进行融合,最终实现对齿轮的故障诊断。实例结果表明,该方法可充分利用各种故障的冗余和互补信息,有效地提高诊断的可信度。
-For the reason of low-reliability exists in the gear fault diagnosis of traditional methods, a method
based on evidence theory hybrid diagnosis algorithm is presented. According to the fault feature vectors, two parallel
BP neural networks are used to carry on local fault diagnosis to acquire the independent evidences each other. Then
evidence theory is employed to fuse evidences, and gear fault diagnosis is fulfilled finally. Example shows that, vari-
ous faults redundant and complement information can be sufficiently used and the reliability of diagnosis is effectively
improved.
Platform: |
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Author:whb |
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Description: Neural networks are composed of simple elements operating in parallel. These
elements are inspired by biological nervous systems. As in nature, the network
function is determined largely by the connections between elements. We can
train a neural network to perform a particular function by adjusting the values
of the connections (weights) between elements.
Commonly neural networks are adjusted, or trained, so that a particular input
leads to a specific target output. Such a situation is shown below. Platform: |
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Author:n |
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Description: 《人工神经网络与模糊信号处理.pdf》,书中首先介绍人工神经网络和模糊理论的信号处理概要；其次作为神经网络的典型的例子介绍阶梯型及相互结合型的神经网络以及基于它们的信号处理，还介绍模糊推论和模糊信号处理等；最后示出神经网络与模糊信号处理的种种应用实例，介绍今后以高度智能化系统为目标的人工并列处理模型和智能信号处理等。
-" Artificial neural networks and fuzzy signal processing. Pdf" , the book introduces the theory of artificial neural networks and fuzzy signal processing summary secondly as a typical example of neural networks and the mutual introduction of combined ladder-type neural network as well as their signal-based treatment, also introduced fuzzy inference and fuzzy signal processing finally showing neural networks and fuzzy signal processing various application examples, introduced in the future in a highly artificial intelligent system for the target model of parallel processing and intelligent signal processing. Platform: |
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Author:唐小米 |
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Description: 工神经网络（Artificial Neural Network）又称连接机模型，是在现代神经学、生物学、心理学等学科研究的基础上产生的，它反映了生物神经系统处理外界事物的基本过程，是在模拟人脑神经组织的基础上发展起来的计算系统，是由大量处理单元通过广泛互联而构成的网络体系，它具有生物神经系统的基本特征，在一定程度上反映了人脑功能的若干反映，是对生物系统的某种模拟，具有大规模并行、分布式处理、自组织、自学习等优点，被广泛应用于语音分析、图像识别、数字水印、计算机视觉等很多领域，取得了许多突出的成果。最近由于人工神经网络的快速发展，它已经成为模式识别的强有力的工具。神经网络的运用展开了新的领域，解决其它模式识别不能解决的问题，其分类功能特别适合于模式识别与分类的应用。多层前向BP网络是目前应用最多的一种神经网络形式-Artificial neural network (Artificial Neural Network) connection, also known as machine model, is based on interdisciplinary research in modern neurology, biology, psychology, etc. produced on, it reflects the fundamental processes of biological neural processing of external things, is in the simulation developed on the basis of human brain tissue computing system is constituted by a large number of processing units interconnected through an extensive network system, it has the basic characteristics of biological neural systems, to a certain extent reflects the number of reflecting the human brain function is simulation of certain biological systems, with massively parallel, distributed processing, self-organizing, self-learning, etc., are widely used in many areas of speech analysis, image recognition, digital watermarking, computer vision, and achieved many outstanding achievements . Recently due to the rapid development of artificial neural networks, it has become a powerful tool fo Platform: |
Size: 100352 |
Author:沈阳阳 |
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Search - parallel neural networks