the Nest of Students

Rao V. Dukkipati ... 680 pages - Publisher: Anshan Publishers; (October, 2010) ... Language: English - ISBN-10: 1904798675 - ISBN-13: 978-1848290433

This book presents an introduction to MATLAB and its applications in engineering problem solving. It is designed as an introductory course in MATLAB for engineers. The classical methods of electrical circuits,control systems, numerical methods, optimization, direct numerical integration methods, engineering mechanics and mechanical vibrations are covered using MATLAB software. The numerous worked examples and unsolved exercise problems are intended to provide the reader with an awareness of the general applicability to electrical circuits, control systems, numerical methods, optimization, direct numerical integration methods, engineering mechanics and mechanical vibrations using MATLAB. Contents: MATLAB Basics - Electrical Circuits - Control Systems - Numerical Methods - Optimization - Direct Numerical Integration Methods - Engineering Mechanics - Mechanical Vibration.

Steve Brooks, Andrew Gelman ... 619 pages - Publisher: Chapman and Hall/CRC; (May, 2011) ... Language: English - ISBN-10: 1420079417 - ISBN-13: 978-1420079418.

Since their popularization in the 1990s, Markov chain Monte Carlo (MCMC) methods have revolutionized statistical computing and have had an especially profound impact on the practice of Bayesian statistics. Furthermore, MCMC methods have enabled the development and use of intricate models in an astonishing array of disciplines as diverse as fisheries science and economics. The wide-ranging practical importance of MCMC has sparked an expansive and deep investigation into fundamental Markov chain theory. 

Tariq Rashid ... 222 pages - Publisher: CreateSpace Independent Publishing Platform; 1st edition (March, 2016) ... Language: English - ISBN-10: 1530826608 - ISBN-13: 978-1530826605 ...

A step-by-step gentle journey through the mathematics of neural networks, and making your own using the Python computer language. Neural networks are a key element of deep learning and artificial intelligence, which today is capable of some truly impressive feats. Yet too few really understand how neural networks actually work. This guide will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work. You won't need any mathematics beyond secondary school, and an accessible introduction to calculus is also included. The ambition of this guide is to make neural networks as accessible as possible to as many readers as possible - there are enough texts for advanced readers already! You'll learn to code in Python and make your own neural network, teaching it to recognise human handwritten numbers, and performing as well as professionally developed networks. Part 1 is about ideas. We introduce the mathematical ideas underlying the neural networks, gently with lots of illustrations and examples. Part 2 is practical. We introduce the popular and easy to learn Python programming language, and gradually builds up a neural network which can learn to recognise human handwritten numbers, easily getting it to perform as well as networks made by professionals. Part 3 extends these ideas further. We push the performance of our neural network to an industry leading 98% using only simple ideas and code, test the network on your own handwriting, take a privileged peek inside the mysterious mind of a neural network, and even get it all working on a Raspberry Pi. All the code in this has been tested to work on a Raspberry Pi Zero.

Daniel Graupe ... 500 pages - Publisher: World Scientific Publishing; 3rd edition (November 19, 2013) ... Language: English - ISBN-10: 9814522732 - ISBN-13: 978-9814522731 ...

Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in medicine, in finance, in security and beyond. This volume covers the basic theory and architecture of the major artificial neural networks. Uniquely, it presents 18 complete case studies of applications of neural networks in various fields, ranging from cell-shape classification to micro-trading in finance and to constellation recognition all with their respective source codes. These case studies demonstrate to the readers in detail how such case studies are designed and executed and how their specific results are obtained. The book is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks.

Karl Hinderer, Ulrich Rieder, Michael Stieglitz ... 530 pages - Publisher: Springer; 1st edition (January, 2017) ... Language: English - ISBN-10: 3319488139 - ISBN-13: 978-3319488134 ...

Jacek M. Zurada ... 758 pages - Publisher: West Group; 1st Edition (October, 1992) ... Language: English - ISBN-10: 0314933913 - ISBN-13: 978-031493391 ...

Introduction to Artificial Neural Systems by Jacek M. Zurada. Covering algorithms with their advantages, disadvantages and most of all their stability and why they work!

Joseph P. Bigus ... 220 pages - Publisher: Mcgraw-Hill; (May, 1996) ... Language: English - ISBN-10: 0070057796 - ISBN-13: 978-0070057791 ...

Readers will find concrete implementation strategies, reinforced with real-world business examples and a minimum of formulas, and case studies drawn from a broad range of industries. The book illustrates the popular data mining functions of classification, clustering, modeling, and time-series forecasting--through examples developed using the IBM Neural Network Utility.

Simon Haykin ... 842 pages - Publisher: Prentice Hall; 2nd edition (July, 1998) ... Language: English - ISBN-10: 0132733501 - ISBN-13: 978-0132733502 ...

W. T. Ziemba ... 756 pages - Publisher: World Scientific Publishing Company; (September, 2006) ... Language: English - ISBN-10: 981256800X - ISBN-13: 978-9812568007 ...

A reprint of one of the classic volumes on portfolio theory and investment, this book has been used by the leading professors at universities such as Stanford, Berkeley, and Carnegie-Mellon. It contains five parts, each with a review of the literature and about 150 pages of computational and review exercises and further in-depth, challenging problems.Frequently referenced and highly usable, the material remains as fresh and relevant for a portfolio theory course as ever.

Paul Attewell, David Monaghan ... 264 pages - Publisher: Univ. of California Press; (May, 2015) ... Language: English - ISBN-10: 0520280989 - ISBN-13: 978-0520280984 ...

We live in a world of big data: the amount of information collected on human behavior each day is staggering, and exponentially greater than at any time in the past. Additionally, powerful algorithms are capable of churning through seas of data to uncover patterns. Providing a simple and accessible introduction to data mining, Paul Attewell and David B. Monaghan discuss how data mining substantially differs from conventional statistical modeling familiar to most social scientists. The authors also empower social scientists to tap into these new resources and incorporate data mining methodologies in their analytical toolkits. Data Mining for the Social Sciences demystifies the process by describing the diverse set of techniques available, discussing the strengths and weaknesses of various approaches, and giving practical demonstrations of how to carry out analyses using tools in various statistical software packages.

James R. Evans, Edward Minieka ... 488 pages - Publisher: CRC Press; 2nd edition (March, 1992) ... Language: English - ISBN-10: 0824786025 - ISBN-13: 978-0824786021 ...

A revised and expanded advanced-undergraduate/graduate text (first ed., 1978) about optimization algorithms for problems that can be formulated on graphs and networks. This edition provides many new applications and algorithms while maintaining the classic foundations on which contemporary algorithm.

Dimitri P. Bertsekas ... 608 pages - Publisher: Athena Scientific; (May, 1998) ... Language: English - ISBN-10: 1886529027 - ISBN-13: 978-1886529021 ...

An insightful, comprehensive, and up-to-date treatment of linear, nonlinear, and discrete/combinatorial network optimization problems, their applications, and their analytical and algorithmic methodology. It covers extensively theory, algorithms, and applications, and it aims to bridge the gap between linear and nonlinear network optimization on one hand, and integer/combinatorial network optimization on the other. Among its special features, the book: 1) provides a comprehensive account of the principal algorithms for linear network flow problems, including simplex, dual ascent, and auction algorithms 2) describes the application of network algorithms in many practical contexts, with special emphasis on data communication networks 3) develops in detail the computational complexity analysis of the main linear network optimization algorithms 4) covers extensively the main algorithms for specialized network problems, such as shortest path, max-flow, assignment, and traveling salesman 5) describes the main models for discrete network optimization problems, such as constrained shortest path, traveling salesman, vehicle routing, multidimensional assignment, facility location, spanning tree construction, etc 6) describes the main algorithmic approaches for integer-constrained network problems, such as branch-and-bound, Lagrangian relaxation and subgradient optimization, genetic algorithms, tabu search, simulated annealing, and rollout algorithms 7) develops the main methods for nonlinear network problems, such as convex separable and multicommodity flow problems arising in communication, transportation, and manufacturing contexts 8) discusses extensively auction algorithms, based on the author's original research on the subject 9) contains many examples, practical applications, illustrations, and exercises 10) contains much new material not found in any other textbook

Mitsuo Gen, Runwei Cheng, Lin Lin ... 692 pages - Publisher: Springer; (September, 2008) ... Language: English - ISBN-10: 1848001800 - ISBN-13: 978-1848001800 ...

Network models are critical tools in business, management, science and industry. “Network Models and Optimization” presents an insightful, comprehensive, and up-to-date treatment of multiple objective genetic algorithms to network optimization problems in many disciplines, such as engineering, computer science, operations research, transportation, telecommunication, and manufacturing. The book extensively covers algorithms and applications, including shortest path problems, minimum cost flow problems, maximum flow problems, minimum spanning tree problems, traveling salesman and postman problems, location-allocation problems, project scheduling problems, multistage-based scheduling problems, logistics network problems, communication network problem, and network models in assembly line balancing problems, and airline fleet assignment problems. The book can be used both as a student textbook and as a professional reference for practitioners who use network optimization methods to model and solve problems.

William Kocay, Donald L. Kreher ... 566 pages - Publisher: Chapman and Hall/CRC; 2nd edition (September, 2016) ... Language: English - ISBN-10: 1482251167 - ISBN-13: 978-1482251166 ...

The second edition of this popular book presents the theory of graphs from an algorithmic viewpoint. The authors present the graph theory in a rigorous, but informal style and cover most of the main areas of graph theory. The ideas of surface topology are presented from an intuitive point of view. We have also included a discussion on linear programming that emphasizes problems in graph theory. The text is suitable for students in computer science or mathematics programs.

Oliver Nelles ... 785 pages - Publisher: Springer; (December, 2000) ... Language: English - ISBN-10: 3540673695 - ISBN-13: 978-3540673699 ...

Written from an engineering point of view, this book covers the most common and important approaches for the identification of nonlinear static and dynamic systems. The book also provides the reader with the necessary background on optimization techniques, making it fully self-contained. The new edition includes exercises.

Nadia Nedjah, Leandro dos Santos Coelho, Luiza de Macedo Mourelle ... 211 pages - Publisher: Springer; (March, 2012) ... Language: English - ISBN-10: 3642261515 - ISBN-13: 978-3642261510 ...

The editors of this volume, Nadia Nedjah, Leandro dos Santos Coelho and Luiza de Macedo Mourelle, have done a superb job of assembling some of the most innovative and intriguing applications and additions to the methodology and theory of multi-objective swarm intelligence ― the immitation of social swarms behaviors for the solution of optimization problems with respect to many criteria.

Marvin L. ... 418 pages - Publisher: CreateSpace Independent Publishing Platform; (October, 2016) ... Language: English - ISBN-10: 1539701956 - ISBN-13: 978-1539701958 ...

Neural Network Toolbox provides algorithms, functions, and apps to create, train, visualize, and simulate neural networks. You can perform classification, regression, clustering, dimensionality reduction, time-series forecasting, and dynamic system modeling and control. The toolbox includes convolutional neural network and autoencoder deep learning algorithms for image classification and feature learning tasks. To speed up training of large data sets, you can distribute computations and data across multicore processors, GPUs, and computer clusters using Parallel Computing Toolbox. The more importan features are de next: •Deep learning, including convolutional neural networks and autoencoders •Parallel computing and GPU support for accelerating training (with Parallel Computing Toolbox •Supervised learning algorithms, including multilayer, radial basis, learning vector quantization (LVQ), time-delay, nonlinear autoregressive (NARX), and recurrent neural network (RNN) •Unsupervised learning algorithms, including self-organizing maps and competitive layers •Apps for data-fitting, pattern recognition, and clustering •Preprocessing, postprocessing, and network visualization for improving training efficiency and assessing network performance •Simulink blocks for building and evaluating neural networks and for control systems applications.

Thorsten Wagener, Hoshin V. Gupta, Howard S. Wheater ...
332 pages - Publisher: Imperial College Press; (September, 2004) ... Language: English - ISBN-10: 1860944663 - ISBN-13: 978-1860944666 ...

This important monograph is based on the results of a study on the identification of conceptual lumped rainfall-runoff models for gauged and ungauged catchments. The task of model identification remains difficult despite decades of research. A detailed problem analysis and an extensive review form the basis for the development of a Matlab® modelling toolkit consisting of two components: a Rainfall-Runoff Modelling Toolbox (RRMT) and a Monte Carlo Analysis Toolbox (MCAT). These are subsequently applied to study the tasks of model identification and evaluation. A novel dynamic identifiability approach has been developed for the gauged catchment case. The theory underlying the application of rainfall-runoff models for predictions in ungauged catchments is studied, problems are highlighted and promising ways to move forward are investigated. Modelling frameworks for both gauged and ungauged cases are developed. This book presents the first extensive treatment of rainfall-runoff model identification in gauged and ungauged catchments.

Satchidananda Dehuri, A. K. Jagadev, M. Panda ... 201 pages - Publisher: Springer; (March, 2015) ...
Language: English - ISBN-10: 3662463083 - ISBN-13: 978-3662463086 ...

The aim of this book is to understand the state-of-the-art theoretical and practical advances of swarm intelligence. It comprises seven contemporary relevant chapters. In chapter 1, a review of Bacteria Foraging Optimization (BFO) techniques for both single and multiple criterions problem is presented. A survey on swarm intelligence for multiple and many objectives optimization is presented in chapter 2 along with a topical study on EEG signal analysis. Without compromising the extensive simulation study, a comparative study of variants of MOPSO is provided in chapter 3. Intractable problems like subset and job scheduling problems are discussed in chapters 4 and 7 by different hybrid swarm intelligence techniques. An attempt to study image enhancement by ant colony optimization is made in chapter 5. Finally, chapter 7 covers the aspect of uncertainty in data by hybrid PSO. 

Fei Tao, Lin Zhang, Yuanjun Laili ... 361 pages - Publisher: Springer; (September, 2016) ...
Language: English - ISBN-10: 3319380419 - ISBN-13: 978-3319380414 ...

Presenting the concept and design and implementation of configurable intelligent optimization algorithms in manufacturing systems, this book provides a new configuration method to optimize manufacturing processes. It provides a comprehensive elaboration of basic intelligent optimization algorithms, and demonstrates how their improvement, hybridization and parallelization can be applied to manufacturing. Furthermore, various applications of these intelligent optimization algorithms are exemplified in detail, chapter by chapter. The intelligent optimization algorithm is not just a single algorithm; instead it is a general advanced optimization mechanism which is highly scalable with robustness and randomness. Therefore, this book demonstrates the flexibility of these algorithms, as well as their robustness and reusability in order to solve mass complicated problems in manufacturing. Since the genetic algorithm was presented decades ago, a large number of intelligent optimization algorithms and their improvements have been developed. However, little work has been done to extend their applications and verify their competence in solving complicated problems in manufacturing. This book will provide an invaluable resource to students, researchers, consultants and industry professionals interested in engineering optimization. It will also be particularly useful to three groups of readers: algorithm beginners, optimization engineers and senior algorithm designers. It offers a detailed description of intelligent optimization algorithms to algorithm beginners; recommends new configurable design methods for optimization engineers, and provides future trends and challenges of the new configuration mechanism to senior algorithm designers.