一篇论文，短时交通流预测、遗传算法 As we know, to predict short-term traffic flow accurately and efficiently is the premise and key of traffic management and control. This paper applies the theory of genetic algorithm into the BP neural network structure, designs an
Foreword Author's Biographical Information Part A—General Theory Chapter 1—Learning Algorithms for Neuro-Fuzzy Networks 1 Introduction 2 Neuro-Fuzzy Networks 2.1 The Conventional Fuzzy Model 2.2 From Fuzzy to Neuro-Fuzzy 2.3 Initialization 2.4 Train
Chapter 1—Preliminaries 1.1. Computational Intelligence: its inception and research agenda 1.2. Organization and readership 1.3. References Chapter 2—Neural Networks and Neurocomputing 2.1. Introduction 2.2. Generic models of computational neurons 2
Preface About the Editors Part 1—Fundamentals and Neuro-Fuzzy Signal Processing Chapter 1—Fuzzy Logic and Neuro-Fuzzy Systems in Medicine and Bio-Medical Engineering: A Historical Perspective 1. The First Period: The Infancy 2. Further Developments
Preface Chapter 1—Introduction 1.1 Neuroinformatics 1.1.1 Neural Memory: Neural Information Storage 1.1.2 Information-Traffic in the Neurocybernetic System 1.2 Information-Theoretic Framework of Neurocybernetics 1.3 Entropy, Thermodynamics and Infor
根据神经网络和遗传算法原理，在MATLAB中编程实现神经网络遗传算法非线性函数寻优-Nonlinear function of the neural network, genetic algorithm optimization based on neural network and genetic algorithm theory, programming in MATLAB
Intelligent and Evolutionary Systems: The 20th Asia Pacific Symposium, IES 2016, Canberra, Australia, November 2016, Proceedings (Proceedings in Adaptation, Learning and Optimization) Over the last two decades the field of Intelligent Systems delive
Machine Learning, Optimization, and Big Data: Second International Workshop, MOD 2016, Volterra, Italy, August 26-29, 2016, Revised Selected Papers (Lecture Notes in Computer Science) This book constitutes revised selected papers from the Second Int
Blind equalization (BE) technology is a new adaptive technology. BE only uses the prior information of received signals to equalize the channel characteristics, so train- ing sequence is not needed. The output sequence is close to the transmitted se
This Book discusses machine learning for model order reduction, which can be used in modern VLSI design to predict the behavior of an electronic circuit, via mathematical models that predict behavior. The author describes techniques to reduce signif
In this paper, we propose a novel approach to achieve spectrum prediction, parameter fitting, inverse design, and performance optimization for the plasmonic waveguide-coupled with cavities structure (PWCCS) based on artificial neural networks (ANNs).
