Nature Inspired Methods In Chemometrics Genetic Algorithms And Artificial Neural Networks PDF Download

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Nature-inspired Methods in Chemometrics: Genetic Algorithms and Artificial Neural Networks

Nature-inspired Methods in Chemometrics: Genetic Algorithms and Artificial Neural Networks
Author: Riccardo Leardi
Publisher: Elsevier
Total Pages: 402
Release: 2003-12-03
Genre: Science
ISBN: 9780080522623

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In recent years Genetic Algorithms (GA) and Artificial Neural Networks (ANN) have progressively increased in importance amongst the techniques routinely used in chemometrics. This book contains contributions from experts in the field is divided in two sections (GA and ANN). In each part, tutorial chapters are included in which the theoretical bases of each technique are expertly (but simply) described. These are followed by application chapters in which special emphasis will be given to the advantages of the application of GA or ANN to that specific problem, compared to classical techniques, and to the risks connected with its misuse. This book is of use to all those who are using or are interested in GA and ANN. Beginners can focus their attentions on the tutorials, whilst the most advanced readers will be more interested in looking at the applications of the techniques. It is also suitable as a reference book for students. Subject matter is steadily increasing in importance Comparison of Genetic Algorithms (GA) and Artificial Neural Networks (ANN) with the classical techniques Suitable for both beginners and advanced researchers


Comprehensive Chemometrics

Comprehensive Chemometrics
Author:
Publisher: Elsevier
Total Pages: 2880
Release: 2009-03-09
Genre: Science
ISBN: 044452701X

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Designed to serve as the first point of reference on the subject, Comprehensive Chemometrics presents an integrated summary of the present state of chemical and biochemical data analysis and manipulation. The work covers all major areas ranging from statistics to data acquisition, analysis, and applications. This major reference work provides broad-ranging, validated summaries of the major topics in chemometrics—with chapter introductions and advanced reviews for each area. The level of material is appropriate for graduate students as well as active researchers seeking a ready reference on obtaining and analyzing scientific data. Features the contributions of leading experts from 21 countries, under the guidance of the Editors-in-Chief and a team of specialist Section Editors: L. Buydens; D. Coomans; P. Van Espen; A. De Juan; J.H. Kalivas; B.K. Lavine; R. Leardi; R. Phan-Tan-Luu; L.A. Sarabia; and J. Trygg Examines the merits and limitations of each technique through practical examples and extensive visuals: 368 tables and more than 1,300 illustrations (750 in full color) Integrates coverage of chemical and biological methods, allowing readers to consider and test a range of techniques Consists of 2,200 pages and more than 90 review articles, making it the most comprehensive work of its kind Offers print and online purchase options, the latter of which delivers flexibility, accessibility, and usability through the search tools and other productivity-enhancing features of ScienceDirect


Comprehensive Chemometrics

Comprehensive Chemometrics
Author: Steven Brown
Publisher: Elsevier
Total Pages: 2948
Release: 2020-05-26
Genre: Science
ISBN: 0444641661

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Comprehensive Chemometrics, Second Edition, Four Volume Set features expanded and updated coverage, along with new content that covers advances in the field since the previous edition published in 2009. Subject of note include updates in the fields of multidimensional and megavariate data analysis, omics data analysis, big chemical and biochemical data analysis, data fusion and sparse methods. The book follows a similar structure to the previous edition, using the same section titles to frame articles. Many chapters from the previous edition are updated, but there are also many new chapters on the latest developments. Presents integrated reviews of each chemical and biological method, examining their merits and limitations through practical examples and extensive visuals Bridges a gap in knowledge, covering developments in the field since the first edition published in 2009 Meticulously organized, with articles split into 4 sections and 12 sub-sections on key topics to allow students, researchers and professionals to find relevant information quickly and easily Written by academics and practitioners from various fields and regions to ensure that the knowledge within is easily understood and applicable to a large audience Presents integrated reviews of each chemical and biological method, examining their merits and limitations through practical examples and extensive visuals Bridges a gap in knowledge, covering developments in the field since the first edition published in 2009 Meticulously organized, with articles split into 4 sections and 12 sub-sections on key topics to allow students, researchers and professionals to find relevant information quickly and easily Written by academics and practitioners from various fields and regions to ensure that the knowledge within is easily understood and applicable to a large audience


Nature Inspired Cooperative Strategies for Optimization (NICSO 2010)

Nature Inspired Cooperative Strategies for Optimization (NICSO 2010)
Author: Carlos Cruz
Publisher: Springer Science & Business Media
Total Pages: 401
Release: 2010-04-07
Genre: Computers
ISBN: 3642125379

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Many aspects of Nature, Biology or even from Society have become part of the techniques and algorithms used in computer science or they have been used to enhance or hybridize several techniques through the inclusion of advanced evolution, cooperation or biologically based additions. The previous NICSO workshops were held in Granada, Spain, 2006, Acireale, Italy, 2007, and in Tenerife, Spain, 2008. As in the previous editions, NICSO 2010, held in Granada, Spain, was conceived as a forum for the latest ideas and the state of the art research related to nature inspired cooperative strategies. The contributions collected in this book cover topics including nature-inspired techniques like Genetic Algorithms, Evolutionary Algorithms, Ant and Bee Colonies, Swarm Intelligence approaches, Neural Networks, several Cooperation Models, Structures and Strategies, Agents Models, Social Interactions, as well as new algorithms based on the behaviour of fireflies or bats.


Chemometric Methods in Capillary Electrophoresis

Chemometric Methods in Capillary Electrophoresis
Author: Grady Hanrahan
Publisher: John Wiley & Sons
Total Pages: 460
Release: 2009-10-22
Genre: Science
ISBN: 0470530189

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Use chemometric techniques to develop optimum separation conditions for capillary electrophoreses For all its advantages, capillary electrophoresis (CE) also carries significant disadvantages for the researcher. Offering a unique blend of information from authors active in a variety of developments of chemometrics in CE, Chemometric Methods in Capillary Electrophoresis presents modern chemometric methods as an alternative to help alleviate the problems commonly encountered during routine analysis and method development. Focusing on current chemometric methods utilized in CE endeavours by research-active experts in the field, the book begins with a thorough introduction to CE and chemometric-related concepts and the need for modern chemometric methods in CE. Part 1 discusses differing types of screening designs and response surface methodology¿in an¿application based format Part 2 includes vital discussion on various exploratory data analysis, prediction, and classification techniques utilized in CE-related studies Part 3 provides practical information on modelling quantitative structure relationships Part 4 explores transformation techniques, in particular fundamental studies and applications of cross-correlation and Hadamard Transform Electrophoresis Showing how chemometric methods are applied in a wide array of applications including biological, medical, pharmaceutical, food, forensic, and environmental science, Chemometric Methods in Capillary Electrophoresis is not only highly significant to capillary electrophoresis-based endeavours, but instructive for investigators active in other areas of separation science who could benefit from its informative content.


Introduction to Multivariate Statistical Analysis in Chemometrics

Introduction to Multivariate Statistical Analysis in Chemometrics
Author: Kurt Varmuza
Publisher: CRC Press
Total Pages: 328
Release: 2016-04-19
Genre: Mathematics
ISBN: 1420059491

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Using formal descriptions, graphical illustrations, practical examples, and R software tools, Introduction to Multivariate Statistical Analysis in Chemometrics presents simple yet thorough explanations of the most important multivariate statistical methods for analyzing chemical data. It includes discussions of various statistical methods, such as


Nature-Inspired Optimization Algorithms

Nature-Inspired Optimization Algorithms
Author: Xin-She Yang
Publisher: Academic Press
Total Pages: 312
Release: 2020-09-09
Genre: Science
ISBN: 0128219890

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Nature-Inspired Optimization Algorithms, Second Edition provides an introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, and multi-objective optimization. This book can serve as an introductory book for graduates, for lecturers in computer science, engineering and natural sciences, and as a source of inspiration for new applications. Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature Provides a theoretical understanding and practical implementation hints Presents a step-by-step introduction to each algorithm Includes four new chapters covering mathematical foundations, techniques for solving discrete and combination optimization problems, data mining techniques and their links to optimization algorithms, and the latest deep learning techniques, background and various applications


Molecular Descriptors for Chemoinformatics

Molecular Descriptors for Chemoinformatics
Author: Roberto Todeschini
Publisher: John Wiley & Sons
Total Pages: 1257
Release: 2009-10-30
Genre: Science
ISBN: 9783527628773

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The number-one reference on the topic now contains a wealth of new data: The entire relevant literature over the past six years has been painstakingly surveyed, resulting in hundreds of new descriptors being added to the list, and some 3,000 new references in the bibliography section. Volume 1 contains an alphabetical listing of more than 3300 descriptors and related terms for chemoinformatic analysis of chemical compound properties, while the second volume lists over 6,000 references selected from 450 journals. To make the data even more accessible, the introductory section has been completely re-written and now contains several "walk-through" reading lists of selected keywords for novice users.


Modern Techniques for Food Authentication

Modern Techniques for Food Authentication
Author: Da-Wen Sun
Publisher: Academic Press
Total Pages: 805
Release: 2018-07-25
Genre: Medical
ISBN: 0128142650

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Modern Techniques for Food Authentication, Second Edition presents a comprehensive review of the novel techniques available to authenticate food products, including various spectroscopic technologies, methods based on isotopic analysis and chromatography, and other techniques based on DNA, enzymatic analysis and electrophoresis. This new edition pinpoints research and development trends for those working in research, development and operations in the food industry, giving them readily accessible information on modern food authentication techniques to ensure a safe and authentic food supply. It will also serve as an essential reference source to undergraduate and postgraduate students, and for researchers in universities and research institutions. Presents emerging imaging techniques that have proven to be powerful, non-destructive tools for food authentication Includes applications of hyperspectral imaging to reflect the current trend of developments in food imaging technology for each topic area Provides pixel level visualization techniques needed for fast and effective food sample testing Contains two new chapters on Imaging Spectroscopic Techniques


Genetic Algorithms for Machine Learning

Genetic Algorithms for Machine Learning
Author: John J. Grefenstette
Publisher: Springer Science & Business Media
Total Pages: 167
Release: 2012-12-06
Genre: Computers
ISBN: 1461527406

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The articles presented here were selected from preliminary versions presented at the International Conference on Genetic Algorithms in June 1991, as well as at a special Workshop on Genetic Algorithms for Machine Learning at the same Conference. Genetic algorithms are general-purpose search algorithms that use principles inspired by natural population genetics to evolve solutions to problems. The basic idea is to maintain a population of knowledge structure that represent candidate solutions to the problem of interest. The population evolves over time through a process of competition (i.e. survival of the fittest) and controlled variation (i.e. recombination and mutation). Genetic Algorithms for Machine Learning contains articles on three topics that have not been the focus of many previous articles on GAs, namely concept learning from examples, reinforcement learning for control, and theoretical analysis of GAs. It is hoped that this sample will serve to broaden the acquaintance of the general machine learning community with the major areas of work on GAs. The articles in this book address a number of central issues in applying GAs to machine learning problems. For example, the choice of appropriate representation and the corresponding set of genetic learning operators is an important set of decisions facing a user of a genetic algorithm. The study of genetic algorithms is proceeding at a robust pace. If experimental progress and theoretical understanding continue to evolve as expected, genetic algorithms will continue to provide a distinctive approach to machine learning. Genetic Algorithms for Machine Learning is an edited volume of original research made up of invited contributions by leading researchers.