TAILIEUCHUNG - Ebook An introduction to Neural network methods for differential equations

Ebook "An introduction to Neural network methods for differential equations" introduces a variety of neural network methods for solving differential equations arising in science and engineering. The emphasis is placed on a deep understanding of the neural network techniques, which has been presented in a mostly heuristic and intuitive manner. This approach will enable the reader to understand the working, efficiency and shortcomings of each neural network technique for solving differential equations. The objective of this book is to provide the reader with a sound understanding of the foundations of neural networks and a comprehensive introduction to neural network methods for solving differential equations together with recent developments in the techniques and their applications. | SPRINGER BRIEFS IN APPLIED SCIENCES AND TECHNOLOGY COMPUTATIONAL INTELLIGENCE Neha Yadav Anupam Yadav Manoj Kumar An Introduction to Neural Network Methods for Differential Equations SpringerBriefs in Applied Sciences and Technology Computational Intelligence Series editor Janusz Kacprzyk Warsaw Poland About this Series The series Studies in Computational Intelligence SCI publishes new develop- ments and advances in the various areas of computational intelligence quickly and with a high quality. The intent is to cover the theory applications and design methods of computational intelligence as embedded in the fields of engineering computer science physics and life sciences as well as the methodologies behind them. The series contains monographs lecture notes and edited volumes in com- putational intelligence spanning the areas of neural networks connectionist sys- tems genetic algorithms evolutionary computation artificial intelligence cellular automata self-organizing systems soft computing fuzzy systems and hybrid intelligent systems. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution which enable both wide and rapid dissemination of research output. More information about this series at http series 10618 Neha Yadav Anupam Yadav Manoj Kumar An Introduction to Neural Network Methods for Differential Equations 123 Neha Yadav Manoj Kumar Department of Applied Sciences Department of Mathematics ITM University Motilal Nehru National Institute of Gurgaon Haryana Technology India Allahabad India Anupam Yadav Department of Sciences and Humanities National Institute of Technology Uttarakhand Srinagar Uttarakhand India ISSN 2191-530X ISSN 2191-5318 electronic SpringerBriefs in Applied Sciences and Technology ISBN 978-94-017-9815-0 ISBN 978-94-017-9816-7 eBook DOI 978-94-017-9816-7 Library of Congress Control Number 2015932071 Springer Dordrecht Heidelberg New York London

• Quản trị mạng
• Neural network methods
• Differential equations
• Finite difference method
• Neural network method
• Biological neural network
• Artificial neural network
• Multi layer perceptron
• Radial basis function neural networks
• Bayesian neural networks and its application in obstacle avoidance methods
• Bayesian neural networks
• The most suitable autonomous task
• The optimal neural network structure
• Previously reported shared control methods
• Building maintenance contractor
• Multi criteria decision making methods
• Artificial neural network model
• Spearman correlation coefficients
• Articial neural network
• Machine learning based methods
• Population estimation of rohingya refugees
• Comparing data driven
• Satellite image driven approaches
• Various financial ratios
• Entropy and Critic Methods
• Segregation of financial ratios
• Financial efficiency of the business organizations
• Multivariate least regression
• Stability constants
• Quantitative structure property relationship
• QSPR modeling methods
• BMC Cancer
• Cervical cancer
• 5–year overall survival
• Computational intelligence methods
• Probabilistic neural network
• Dynamic Optimization
• Neural Network
• Algorithm Convergence
• Multiobjective Optimization
• Ant Programming
• Green Manufacturing
• Colony Algorithms
• báo cáo khoa học
• báo cáo hóa học
• công trình nghiên cứu về hóa học
• tài liệu về hóa học
• cách trình bày báo cáo
• Computed torque controller
• Sliding mode control
• Delta parallel robot
• Computed torque control
• Neural network control
• Expert system
• Product model
• Prototypal intelligent nesting system
• Methods of artificial intelligence
• BMC Bioinformatics
• Data mining
• Named entity recognition
• CRF based methods yield
• Deep learning
• Deep recurrent neural network
• Restricted Boltzmann machine
• Protein torsion angle prediction
• Gene optimization
• Bayes’ theorem
• Euclidean distance
• Codon usage bias
• Highly expressed gene
• 3D profile
• Alternating decision tree
• Proteins capable
• Forming fibrils
• Alzheimer disease
• BMC Genomics
• Protein nucleic acid binding
• Recurrent neural network
• Nucleic acid molecules
• High throughput technologies
• Several computational methods