Download or read book A Study of Backpropagation and Particle Swarm Optimization Learning Methods for Artificial Neural Network Training written by Mohd. Shukri Mohd. Ghazali and published by . This book was released on 2010 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book New Backpropagation Algorithm with Type 2 Fuzzy Weights for Neural Networks written by Fernando Gaxiola and published by Springer. This book was released on 2016-06-02 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book a neural network learning method with type-2 fuzzy weight adjustment is proposed. The mathematical analysis of the proposed learning method architecture and the adaptation of type-2 fuzzy weights are presented. The proposed method is based on research of recent methods that handle weight adaptation and especially fuzzy weights.The internal operation of the neuron is changed to work with two internal calculations for the activation function to obtain two results as outputs of the proposed method. Simulation results and a comparative study among monolithic neural networks, neural network with type-1 fuzzy weights and neural network with type-2 fuzzy weights are presented to illustrate the advantages of the proposed method.The proposed approach is based on recent methods that handle adaptation of weights using fuzzy logic of type-1 and type-2. The proposed approach is applied to a cases of prediction for the Mackey-Glass (for ô=17) and Dow-Jones time series, and recognition of person with iris biometric measure. In some experiments, noise was applied in different levels to the test data of the Mackey-Glass time series for showing that the type-2 fuzzy backpropagation approach obtains better behavior and tolerance to noise than the other methods.The optimization algorithms that were used are the genetic algorithm and the particle swarm optimization algorithm and the purpose of applying these methods was to find the optimal type-2 fuzzy inference systems for the neural network with type-2 fuzzy weights that permit to obtain the lowest prediction error.
Download or read book Evolutionary Programming VII written by V.W. Porto and published by Springer. This book was released on 1998-08-05 with total page 840 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 7th International Conference on Evolutionary Programming, EP98, held in San Diego, CA, USA, in March 1998. The volume presents 81 revised full papers selected from an overwhelming number of submissions. The papers are organized in topical sections on economics, emergence and complex systems; issues and innovations in evolutionary computation; applications; evolution-based approaches to engineering design; examining representations and operators; evolutionary computation theory; evolutionary computation and biological modeling; particle swarm; and combinations of evolutionary and neural computation.
Download or read book Research Anthology on Artificial Neural Network Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2021-07-16 with total page 1575 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks (ANNs) present many benefits in analyzing complex data in a proficient manner. As an effective and efficient problem-solving method, ANNs are incredibly useful in many different fields. From education to medicine and banking to engineering, artificial neural networks are a growing phenomenon as more realize the plethora of uses and benefits they provide. Due to their complexity, it is vital for researchers to understand ANN capabilities in various fields. The Research Anthology on Artificial Neural Network Applications covers critical topics related to artificial neural networks and their multitude of applications in a number of diverse areas including medicine, finance, operations research, business, social media, security, and more. Covering everything from the applications and uses of artificial neural networks to deep learning and non-linear problems, this book is ideal for computer scientists, IT specialists, data scientists, technologists, business owners, engineers, government agencies, researchers, academicians, and students, as well as anyone who is interested in learning more about how artificial neural networks can be used across a wide range of fields.
Download or read book Integration of Swarm Intelligence and Artificial Neural Network written by Satchidananda Dehuri and published by World Scientific. This book was released on 2011 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a new forum for the dissemination of knowledge in both theoretical and applied research on swarm intelligence (SI) and artificial neural network (ANN). It accelerates interaction between the two bodies of knowledge and fosters a unified development in the next generation of computational model for machine learning. To the best of our knowledge, the integration of SI and ANN is the first attempt to integrate various aspects of both the independent research area into a single volume.
Download or read book Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition written by Serkan Kiranyaz and published by Springer Science & Business Media. This book was released on 2013-07-16 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: For many engineering problems we require optimization processes with dynamic adaptation as we aim to establish the dimension of the search space where the optimum solution resides and develop robust techniques to avoid the local optima usually associated with multimodal problems. This book explores multidimensional particle swarm optimization, a technique developed by the authors that addresses these requirements in a well-defined algorithmic approach. After an introduction to the key optimization techniques, the authors introduce their unified framework and demonstrate its advantages in challenging application domains, focusing on the state of the art of multidimensional extensions such as global convergence in particle swarm optimization, dynamic data clustering, evolutionary neural networks, biomedical applications and personalized ECG classification, content-based image classification and retrieval, and evolutionary feature synthesis. The content is characterized by strong practical considerations, and the book is supported with fully documented source code for all applications presented, as well as many sample datasets. The book will be of benefit to researchers and practitioners working in the areas of machine intelligence, signal processing, pattern recognition, and data mining, or using principles from these areas in their application domains. It may also be used as a reference text for graduate courses on swarm optimization, data clustering and classification, content-based multimedia search, and biomedical signal processing applications.
Download or read book Integration Of Swarm Intelligence And Artificial Neural Network written by Satchidananda Dehuri and published by World Scientific. This book was released on 2011-06-08 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a new forum for the dissemination of knowledge in both theoretical and applied research on swarm intelligence (SI) and artificial neural network (ANN). It accelerates interaction between the two bodies of knowledge and fosters a unified development in the next generation of computational model for machine learning.To the best of our knowledge, the integration of SI and ANN is the first attempt to integrate various aspects of both the independent research area into a single volume.
Download or read book Designing Artificial Neural Network Using Particle Swarm Optimization written by Pooria Mazaheri and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural network modeling has become a special interest for many engineers and scientists to be utilized in different types of data as time series, regression, and classification and have been used to solve complicated practical problems in different areas, such as medicine, engineering, manufacturing, military, business. To utilize a prediction model that is based upon artificial neural network (ANN), some challenges should be addressed that optimal designing and training of ANN are major ones. ANN can be defined as an optimization task because it has many hyper parameters and weights that can be optimized. Metaheuristic algorithms such as swarm intelligence-based methods are a category of optimization methods that aim to find an optimal structure of ANN and to train the network by optimizing the weights. One of the commonly used swarm intelligence-based algorithms is particle swarm optimization (PSO) that can be used for optimizing ANN. In this study, we review the conducted research works on optimizing the ANNs using PSO. All studies are reviewed from two different perspectives: optimization of weights and optimization of structure and hyper parameters.
Download or read book Introduction to Fuzzy Arithmetic written by Arnold Kaufmann and published by Van Nostrand Reinhold. This book was released on 1991 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Applications of Artificial Neural Networks and Machine Learning in Civil Engineering written by Ali Kaveh and published by Springer Nature. This book was released on with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Comparison of Search Algorithms in Two stage Neural Network Training for Optical Character Recognition of Handwritten Digits written by Patrik Wayne Gilley and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks are a powerful machine learning technique that give a system the ability to develop multiple levels of abstraction to interpret data. Such networks require training to develop the neural layers and neuron weights in order to form reasonable conclusions from the data being interpreted. The conventional training method is to use backpropagation to feed the error between a neural network’s actual output and desired output back through the neural network to adjust the neural synapses’ weights to minimize such errors on subsequent training data. However, backpropagation has several limitations to its effectiveness in training neural networks. The most relevant limitation of backpropagation is that it tends to become trapped in local optimum solutions. This research studied the effectiveness in using search algorithms to improve upon a feed-forward Multi-Layer Perceptron artificial neural network trained by backpropagation in classifying handwritten digits. The search algorithms used for this research were the Bare Bones Fireworks Algorithm (BBFWA), Canonical Particle Swarm Optimization (PSO), and Cooperative Particle Swarm Optimization (CPSO) algorithms. Two sets of parameters for the BBFWA were tested in this study in order to examine the effects of parameters on the algorithm. The handwritten digit classification data was carried out on the MNIST handwritten character database, a common benchmark for handwritten character recognition. A neural network was trained with backpropagation, and then the search algorithms were seeded with its weights so that they could search for better neural network weight configurations. The complexity of using images of handwritten characters with a feed-forward Multi-Layer Perceptron resulted in a high degree of dimensionality in the problem, which negatively impacted the Particle Swarm Optimization algorithms. To analyze the impact of the problem dimensionality, the neural network was also tested with a PCA compressed MNIST database. It was found that the BBFWA performed the best out of the three algorithms on both datasets, as it was able to consistently improve upon the performance of the original neural networks. Between the two sets of BBFWA parameters, the simulation results indicated that the second parameter set outperformed the first parameter set in terms of both classification accuracy and fitness trends.
Download or read book Knowledge and Systems Engineering written by Viet-Ha Nguyen and published by Springer. This book was released on 2014-09-29 with total page 673 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains papers presented at the Sixth International Conference on Knowledge and Systems Engineering (KSE 2014), which was held in Hanoi, Vietnam, during 9–11 October, 2014. The conference was organized by the University of Engineering and Technology, Vietnam National University, Hanoi. Besides the main track of contributed papers, this proceedings feature the results of four special sessions focusing on specific topics of interest and three invited keynote speeches. The book gathers a total of 51 carefully reviewed papers describing recent advances and development on various topics including knowledge discovery and data mining, natural language processing, expert systems, intelligent decision making, computational biology, computational modeling, optimization algorithms, and industrial applications.
Download or read book Handbook of Neural Computation written by Pijush Samui and published by Academic Press. This book was released on 2017-07-18 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world. Each contributor presents a specific research issue with its recent and future trends. As the demand rises in the engineering and medical industries for neural networks and other machine learning methods to solve different types of operations, such as data prediction, classification of images, analysis of big data, and intelligent decision-making, this book provides readers with the latest, cutting-edge research in one comprehensive text. - Features high-quality research articles on multivariate adaptive regression splines, the minimax probability machine, and more - Discusses machine learning techniques, including classification, clustering, regression, web mining, information retrieval and natural language processing - Covers supervised, unsupervised, reinforced, ensemble, and nature-inspired learning methods
Download or read book Artificial Intelligence written by George F. Luger and published by Pearson Higher Ed. This book was released on 2011-11-21 with total page 779 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Artificial Intelligence: Structures and Strategies for Complex Problem Solving is ideal for a one- or two-semester undergraduate course on AI. In this accessible, comprehensive text, George Luger captures the essence of artificial intelligence–solving the complex problems that arise wherever computer technology is applied. Ideal for an undergraduate course in AI, the Sixth Edition presents the fundamental concepts of the discipline first then goes into detail with the practical information necessary to implement the algorithms and strategies discussed. Readers learn how to use a number of different software tools and techniques to address the many challenges faced by today’s computer scientists.
Download or read book Swarm Intelligence and Bio Inspired Computation written by Priti Srinivas Sajja and published by Elsevier Inc. Chapters. This book was released on 2013-05-16 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bio-inspired models have taken inspiration from the nature to solve challenging problems in an intelligent manner. Major aims of such bio-inspired models of computation are to propose new unconventional computing architectures and novel problem solving paradigms. Computing models such as artificial neural network (ANN), genetic algorithm (GA), and swarm intelligence (SI) are major constituent models of the bio-inspired approach. Applications of these models are ubiquitous and hence proposed to be applied for Semantic Web. The chapter discusses fundamentals of these bio-inspired constituents along with some heuristic that can be used to design and implement these constituents and briefly surveys recent applications of these models for the Semantic Web. The study shows that the objective of the Semantic Web is better met with such approach and the Web can be accessed in more human-oriented way. At the end, a generic framework for web content filtering based on neuro-fuzzy approach is presented. By considering online webpages and fuzzy user profile, the proposed system classifies the webpages into vague categories using a neural network.
Download or read book Proceedings of the First International Conference on Advanced Data and Information Engineering DaEng 2013 written by Tutut Herawan and published by Springer Science & Business Media. This book was released on 2013-12-14 with total page 728 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceeding is a collection of research papers presented at the International Conference on Data Engineering 2013 (DaEng-2013), a conference dedicated to address the challenges in the areas of database, information retrieval, data mining and knowledge management, thereby presenting a consolidated view to the interested researchers in the aforesaid fields. The goal of this conference was to bring together researchers and practitioners from academia and industry to focus on advanced on data engineering concepts and establishing new collaborations in these areas. The topics of interest are as follows but are not limited to: • Database theory • Data management • Data mining and warehousing • Data privacy & security • Information retrieval, integration and visualization • Information system • Knowledge discovery in databases • Mobile, grid and cloud computing • Knowledge-based • Knowledge management • Web data, services and intelligence
Download or read book Trends in Computer Science Engineering and Information Technology written by Dhinaharan Nagamalai and published by Springer Science & Business Media. This book was released on 2011-09-14 with total page 753 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Conference on Computer Science, Engineering and Information Technology, CCSEIT 2011, held in Tirunelveli, India, in September 2011. The 73 revised full papers were carefully reviewed and selected from more than 400 initial submissions. The papers feature significant contributions to all major fields of the Computer Science and Information Technology in theoretical and practical aspects.
