Adaptive and Natural Computing Algorithms, Marco Tomassini; Alberto Antonioni; Fabio Daolio;
Автор: Sung Название: Algorithms in Bioinformatics ISBN: 1420070339 ISBN-13(EAN): 9781420070330 Издательство: Taylor&Francis Рейтинг: Цена: 13779.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents an introduction to the algorithmic techniques applied in bioinformatics. For each topic, this title details the biological motivation, defines the corresponding computational problems, and includes examples to illustrate each algorithm.
Minimize Power Consumption and Enhance User Experience
Essential for high-speed fifth-generation mobile networks, mobile cloud computing (MCC) integrates the power of cloud data centers with the portability of mobile computing devices. Mobile Cloud Computing: Architectures, Algorithms and Applications covers the latest technological and architectural advances in MCC. It also shows how MCC is used in health monitoring, gaming, learning, and commerce.
The book examines computation within a mobile device; the evolution, architecture, and applications of cloud computing; the integration of mobile computing and cloud computing; offloading strategies that address constraints such as poor battery life; and green technologies to optimize mobile power consumption. It also presents various resource allocation schemes of MCC, the architecture and applications of sensor MCC, the new concept of mobile social cloud, security and privacy issues in MCC, and different types of trust in MCC.
In addition, the book explains how to integrate MCC with vehicular networks, compares economic models, and explores the application of MCC to mobile learning, vehicle monitoring, digital forensic analysis, health monitoring, and other areas. The book concludes with a discussion of possible solutions to challenges such as energy efficiency, latency minimization, efficient resource management, billing, and security.
Автор: Marsland Название: Machine Learning ISBN: 1466583282 ISBN-13(EAN): 9781466583283 Издательство: Taylor&Francis Рейтинг: Цена: 12095.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
A Proven, Hands-On Approach for Students without a Strong Statistical Foundation
Since the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing work on the statistical interpretations of machine learning algorithms. Unfortunately, computer science students without a strong statistical background often find it hard to get started in this area.
Remedying this deficiency, Machine Learning: An Algorithmic Perspective, Second Edition helps students understand the algorithms of machine learning. It puts them on a path toward mastering the relevant mathematics and statistics as well as the necessary programming and experimentation.
New to the Second Edition
Two new chapters on deep belief networks and Gaussian processes
Reorganization of the chapters to make a more natural flow of content
Revision of the support vector machine material, including a simple implementation for experiments
New material on random forests, the perceptron convergence theorem, accuracy methods, and conjugate gradient optimization for the multi-layer perceptron
Additional discussions of the Kalman and particle filters
Improved code, including better use of naming conventions in Python
Suitable for both an introductory one-semester course and more advanced courses, the text strongly encourages students to practice with the code. Each chapter includes detailed examples along with further reading and problems. All of the code used to create the examples is available on the author's website.
Автор: Cameron Название: Microeconometrics Using Stata ISBN: 1597180734 ISBN-13(EAN): 9781597180733 Издательство: Taylor&Francis Рейтинг: Цена: 12554.00 р. Наличие на складе: Нет в наличии.
Описание: Updated to reflect Stata 11, this revised edition offers a complete and up-to-date survey of microeconometric methods available in Stata. The authors employ the new margins command, emphasizing both marginal effects at the means and average marginal effects. They also replace the xi command with factor variables, which allow you to specify indicator variables and interaction effects. Along with several new examples, this edition presents the new gmm command for generalized method of moments and nonlinear instrumental-variables estimation. In addition, the chapter on maximum likelihood estimation incorporates enhancements made to ml in Stata 11.
Автор: Bernadete Ribeiro; Rudolf F. Albrecht; Andrej Dobn Название: Adaptive and Natural Computing Algorithms ISBN: 3211249346 ISBN-13(EAN): 9783211249345 Издательство: Springer Рейтинг: Цена: 29209.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The ICANNGA series of Conferences has been organised since 1993 and has a long history of promoting the principles and understanding of computational intelligence paradigms within the scientific community and is a reference for established workers in this area.
Автор: Anthony Brabazon; Michael O`Neill; Se?n McGarraghy Название: Natural Computing Algorithms ISBN: 3662501163 ISBN-13(EAN): 9783662501160 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Introduction.- Introduction to Evolutionary Computing.- Genetic Algorithms.- Extending the Genetic Algorithm.- Evolution Strategies and Evolutionary Programming.- Differential Evolution.- Genetic Programming.- Particle Swarm Algorithms.- Ant Algorithms.- Honeybee Algorithms.- Other Social Algorithms.- Bacterial Foraging Algorithms.- Neural Networks for Supervised Learning.- Neural Networks for Unsupervised Learning.- Neuroevolution.- Artificial Immune Systems.- An Introduction to Developmental and Grammatical Computing.- Grammar-Based and Developmental Genetic Programming.- Grammatical Evolution.- TAG3P and Developmental TAG3P.- Genetic Regulatory Networks.- An Introduction to Physics-Inspired Computing.- Physics-Inspired Computing Algorithms.- Quantum-Inspired Evolutionary Algorithms.- Plant-Inspired Algorithms.- Chemistry-Inspired Algorithms.- Conclusions.- References.- Index.
Автор: Ville Kolehmainen; Pekka Toivanen; Bartlomiej Beli Название: Adaptive and Natural Computing Algorithms ISBN: 3642049206 ISBN-13(EAN): 9783642049200 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The ICANNGA series of conferences has been organized since 1993 and has a long history of promoting the principles and understanding of computational intelligence paradigms within the scienti?c community. Originally ICANNGA stood for "International Conference on Arti?cial Neural Networks and Genetic Algorithms," but in 2005 the conference was renamed to "International C- ference on Adaptive and Natural Computing Algorithms," while keeping the acronymICANNGA.The?rstICANNGAconferencewasheldinInnsbruckA- tria (1993), then Al es in France (1995), Norwich in the UK (1997), Portoroz in Slovenia (1999), Prague in the Czech Republic (2001), Roanne in France (2003), CoimbrainPortugal(2005)andWarsawinPoland(2007).ContinuingthisEu- peantradition, the9thICANNGA washeldinKuopio, Finland(2009).Thevast majority of ICANNGA conferences is organized by and based at a university. Drawing on the experience of previous events and following the same g- eral model, ICANNGA 2009 combined plenary lectures and technical sessions. Apart from being a widely recognized conference, it enhanced the possibility to exchange opinions through lectures and discussions, provided a great oppor- nity to meet new colleagues, as well as to renew old friendships and to facilitate the possibilities for international collaborations. As previously, the conference proceedings are published in the Springer LNCS series.
Автор: Anthony Brabazon; Michael O`Neill; Se?n McGarraghy Название: Natural Computing Algorithms ISBN: 3662436302 ISBN-13(EAN): 9783662436301 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.
Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context.
After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals.
Автор: Mukhopadhyay Sambit, Morris Edward, Arulkumaran Sa Название: Algorithms for Obstetrics and Gynaecology ISBN: 0199651396 ISBN-13(EAN): 9780199651399 Издательство: Oxford Academ Рейтинг: Цена: 7760.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Algorithms in Obstetrics and Gynaecology presents the core knowledge needed to tackle all situations in obstetrics and gynaecology, in a structured fashion. All algorithms are designed to support rapid decision making in the most clinically relevant situations to minimise the risks of a poor outcome.
Описание: New Algorithms, Architectures and Applications for Reconfigurable Computing consists of a collection of contributions from the authors of some of the best papers from the Field Programmable Logic conference (FPL`03) and the Design and Test Europe conference (DATE`03).
Автор: Bartlomiej Beliczynski; Andrzej Dzielinski; Marcin Название: Adaptive and Natural Computing Algorithms ISBN: 3540715908 ISBN-13(EAN): 9783540715900 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The two volume set LNCS 4431 and LNCS 4432 constitutes the refereed proceedings of the 8th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2007, held in Warsaw, Poland, in April 2007. The 178 revised full papers presented were carefully reviewed and selected from a total of 474 submissions.
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