Book Description
This book constitutes the refereed proceedings of the Second International Symposium on Intelligence Computation and Applications, ISICA 2007, held in Wuhan, China, September 21-23, 2007.
The 71 revised full papers were carefully reviewed and selected from nearly 1000 submissions. The topics include Evolutionary Computation, Evolutionary learning, Neural Networks, Swarms, Pattern Recognition, Data Mining and others.
Average customer rating:
|
Advances in Natural Computation: Second International Conference, ICNC 2006, Xi'an, China, September 24-28, 2006, Proceedings, Part I (Lecture Notes in Computer Science)
Manufacturer: Springer
ProductGroup: Book
Binding: Paperback
 Data Mining
| Databases
| Computers & Internet
| Subjects
| Books
Fuzzy Logic
| Algorithms
| Programming
| Computers & Internet
| Subjects
| Books
General
| Algorithms
| Programming
| Computers & Internet
| Subjects
| Books
General
| Artificial Intelligence
| Computer Science
| Computers & Internet
| Subjects
| Books
Machine Vision
| Artificial Intelligence
| Computer Science
| Computers & Internet
| Subjects
| Books
Neural Networks
| Artificial Intelligence
| Computer Science
| Computers & Internet
| Subjects
| Books
Human Vision & Language Systems
| Artificial Intelligence
| Computer Science
| Computers & Internet
| Subjects
| Books
General
| Computers & Internet
| Subjects
| Books
Bioinformatics
| Biological Sciences
| Science
| Subjects
| Books
ASIN: 3540459014 |
Book Description
The two volume set LNCS 4221 and LNCS 4222 constitutes the refereed proceedings of the Second International Conference on Natural Computation, ICNC 2006, held in Xi'an, China, in September 2006 as a joint event in federation with the Third International Conference on Fuzzy Systems and Knowledge Discovery FSKD 2006 (LNAI 4223).
After a demanding review process 168 carefully revised full papers and 86 revised short papers were selected from 1915 submissions for presentation in two volumes. The first volume includes 130 papers related to artificial neural networks, natural neural systems and cognitive science, neural network applications, as well as evolutionary computation: theory and algorithms. The 124 papers in the second volume are orgainzed in topical sections on other topics in natural computation, natural computation techniques applications, hardware, and cross-disciplinary topics.
Book Description
This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. The book is unique in the sense of describing how a search technique, the genetic algorithm, can be used for pattern classification mainly through approximating decision boundaries, and it demonstrates the effectiveness of the genetic classifiers vis-à-vis several widely used classifiers, including neural networks. It provides a balanced mixture of theories, algorithms and applications, and in particular results from the bioinformatics and Web intelligence domains.
This book will be useful to graduate students and researchers in computer science, electrical engineering, systems science, and information technology, both as a text and reference book. Researchers and practitioners in industry working in system design, control, pattern recognition, data mining, soft computing, bioinformatics and Web intelligence will also benefit.
Average customer rating:
|
Evolutionary Computation for Modeling and Optimization (Interdisciplinary Applied Mathematics)
Daniel Ashlock
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover
Artificial Life
| Artificial Intelligence
| Computer Science
| Computers & Internet
| Subjects
| Books
General
| Artificial Intelligence
| Computer Science
| Computers & Internet
| Subjects
| Books
Computer Mathematics
| Artificial Intelligence
| Computer Science
| Computers & Internet
| Subjects
| Books
General
| Computers & Internet
| Subjects
| Books
General
| Biology
| Biological Sciences
| Science
| Subjects
| Books
Bioinformatics
| Biological Sciences
| Science
| Subjects
| Books
General
| Applied
| Mathematics
| Science
| Subjects
| Books
General
| Mathematics
| Science
| Subjects
| Books
General
| Biology
| Biological Sciences
| Professional Science
| Professional & Technical
| Subjects
| Books
General
| Applied
| Mathematics
| Professional Science
| Professional & Technical
| Subjects
| Books
All Amazon Upgrade
| Amazon Upgrade
| Stores
| Books
Computers & Internet
| Amazon Upgrade
| Stores
| Books
Professional & Technical
| Amazon Upgrade
| Stores
| Books
Science
| Amazon Upgrade
| Stores
| Books
All Titles
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Computers & Internet
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Professional
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Science
| Qualifying Textbooks - Fall 2007
| Stores
| Books
ASIN: 0387221964 |
Book Description
Evolutionary Computation for Optimization and Modeling is an introduction to evolutionary computation, a field which includes genetic algorithms, evolutionary programming, evolution strategies, and genetic programming. The text is a survey of some application of evolutionary algorithms. It introduces mutation, crossover, design issues of selection and replacement methods, the issue of populations size, and the question of design of the fitness function. It also includes a methodological material on efficient implementation. Some of the other topics in this book include the design of simple evolutionary algorithms, applications to several types of optimization, evolutionary robotics, simple evolutionary neural computation, and several types of automatic programming including genetic programming. The book gives applications to biology and bioinformatics and introduces a number of tools that can be used in biological modeling, including evolutionary game theory. Advanced techniques such as cellular encoding, grammar based encoding, and graph based evolutionary algorithms are also covered.
This book presents a large number of homework problems, projects, and experiments, with a goal of illustrating single aspects of evolutionary computation and comparing different methods. Its readership is intended for an undergraduate or first-year graduate course in evolutionary computation for computer science, engineering, or other computational science students. Engineering, computer science, and applied math students will find this book a useful guide to using evolutionary algorithms as a problem solving tool.
Average customer rating:
- Significant Addition to Biocomputing
- A good literature survey
|
Evolutionary Computation in Bioinformatics (The Morgan Kaufmann Series in Artificial Intelligence)
Manufacturer: Morgan Kaufmann
ProductGroup: Book
Binding: Hardcover
Artificial Life
| Artificial Intelligence
| Computer Science
| Computers & Internet
| Subjects
| Books
General
| Artificial Intelligence
| Computer Science
| Computers & Internet
| Subjects
| Books
Human Vision & Language Systems
| Artificial Intelligence
| Computer Science
| Computers & Internet
| Subjects
| Books
General
| Computers & Internet
| Subjects
| Books
General
| Languages & Tools
| Programming
| Computers & Internet
| Subjects
| Books
General
| Biology
| Biological Sciences
| Science
| Subjects
| Books
Bioinformatics
| Biological Sciences
| Science
| Subjects
| Books
Genetics
| Evolution
| Science
| Subjects
| Books
General
| Evolution
| Science
| Subjects
| Books
Biotechnology
| Special Topics
| Medicine
| Subjects
| Books
General
| Biology
| Biological Sciences
| Professional Science
| Professional & Technical
| Subjects
| Books
Genetics
| Evolution
| Professional Science
| Professional & Technical
| Subjects
| Books
Biotechnology
| Basic Sciences
| Medical
| Professional & Technical
| Subjects
| Books
All Amazon Upgrade
| Amazon Upgrade
| Stores
| Books
Computers & Internet
| Amazon Upgrade
| Stores
| Books
Medicine
| Amazon Upgrade
| Stores
| Books
Professional & Technical
| Amazon Upgrade
| Stores
| Books
Science
| Amazon Upgrade
| Stores
| Books
All Titles
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Similar Items:
-
Fuzzy Logic with Engineering Applications
-
Machine Learning (Mcgraw-Hill International Edit)
ASIN: 1558607978 |
Book Description
Bioinformatics has never been as popular as it is today. The genomics revolution is generating so much data in such rapid succession that it has become difficult for biologists to decipher. In particular, there are many problems in biology that are too large to solve with standard methods. Researchers in evolutionary computation (EC) have turned their attention to these problems. They understand the power of EC to rapidly search very large and complex spaces and return reasonable solutions. While these researchers are increasingly interested in problems from the biological sciences, EC and its problem-solving capabilities are generally not yet understood or applied in the biology community.
This book offers a definitive resource to bridge the computer science and biology communities. Gary Fogel and David Corne, well-known representatives of these fields, introduce biology and bioinformatics to computer scientists, and evolutionary computation to biologists and computer scientists unfamiliar with these techniques. The fourteen chapters that follow are written by leading computer scientists and biologists who examine successful applications of evolutionary computation to various problems in the biological sciences.
* Describes applications of EC to bioinformatics in a wide variety of areas including DNA sequencing, protein folding, gene and protein classification, drug targeting, drug design, data mining of biological databases, and biodata visualization.
* Offers industrial and academic researchers in computer science, biology, and bioinformatics an important resource for applying evolutionary computation.
* Includes a detailed appendix of biological data resources.
Customer Reviews:
Significant Addition to Biocomputing.......2002-12-20
I like this book. Bioinformatics is a ripe area for applying evolutionary algorithms and the book provides a good overview of many different applications. Some chapters are more polished than others, but that's to be expected. The editors do an excellent job of introducing both bioinformatics and evolutionary computation to their respective audiences. I can't think of another book that makes such an effort to integrate the two communities.
I see another reviewer gave the book 3 stars. I've no idea why. The book is excellent, and has encouraged me to take a look at other papers in this area.
A good literature survey.......2002-12-16
The subject of this book would seem a natural one, given the evolutionary paradigm in biology. Genetic algorithms and evolutionary programming have now found use in many different fields such as physics, financial engineering, network modeling, and computational radiology, to name a few. This use will no doubt continue as computer processing power increases in the future. Although genetic/evolutionary approaches are still much more effective from a computational point of view than strict combinatorial ones, they are still very time intensive, and for many problems have yet to compete with ordinary Monte Carlo techniques. This book gives a brief overview of how evolutionary algorithms are used in bioinformatics, with emphasis on genetic sequence alignment and protein folding. The book does not offer in-depth discussion on these algorithms, but does give references where more information can be obtained. Therefore the book could be described as a literature survey, at least for the chapters that I read, which did not include those on protein folding.
The book is written for the computer scientist who wants to move into bioinformatics, and the biologist, who needs more background in these types of algorithms. Therefore, the editors of the book include two introductory chapters, one introducing bioinformatics for computer scientists, the other an introduction to evolutionary computation for biologists. The latter is more detailed, and the authors introduce the biologist to some of the elementary aspects of evolutionary computation. One interesting, but too short discussion is on the "No Free Lunch Theorem", which implies that evolutionary programs are not in any sense "universal", in that the choice of such a program will depend on the problem at hand, and in fact there may be many such programs for the problem, each with their own performance properties. The theorem is not proved in this book, but references to the proof are given. However, the proof involves a level of mathematics that a biologist would probably not have knowledge of, and so this reference would not be accessible to such a reader. In addition, the theorem has generated a lot of controversy, but the authors do point this out. The authors also discuss effectively the difference between the analytical and heuristic approaches to sequence alignment, setting the stage for later chapters in the book. The problem of local search algorithms getting "trapped" in local minima is also given a very intuitive and understandable treatment by the authors.
The book also includes a discussion on the "DNA sequence reconstruction problem". Algorithms for dealing with this problem are recommended and the the problem is presented as one in integer programming. The authors present a hybrid evolutionary algorithm for dealing with this problem. They characterize this algorithm as being hybrid since it does make use of "crossover" operators and a heuristic "greedy-improvement" method. The discussion of this algorithm is only brief, but references are given. However the main reference is not yet available as it is very recent and in press, and, although the authors do include a fairly lengthy discussion of computational experiments, without a detailed description of the algorithm or source code, their results cannot be checked or validated.
The contrast between optimization theory and evolutionary algorithms is a common theme in the book, with emphasis on the use of evolutionary algorithms to design scoring schemes for sequence alignment where optimization issues can be ignored. The difference between the optimal alignment obtained by various mathematical techniques and the correct (biological) alignment is carefully pointed out. Thus one must be able to tell whether an objective function is relevant from a biological standpoint. In chapter 5 of the book for example, the author introduces an alignment algorithm based on a combination of simulated annealing (SA), and genetic algorithms (GA), called appropriately SAGA. This chapter is the most helpful one in the book, for the author gives pseudocode for this algorithm, with Web links given for obtaining the source code. This allows the interested reader to study the efficacy of the SAGA algorithm in doing muliple sequence alignment.
The use of simulated evolution to find optimal neural networks for identifying coding regions is discussed in chapter 9 of the book. The use of genetic algorithms to assign the weights in a neural network is well-known. The authors point out a further advantage in their use, namely that evolutionary neural networks can adapt to unexpected inputs on their own, and thus do not require any intervention on the part of the user. References are given that elaborate on the power of this approach. Readers who have worked with neural networks will understand fully the need for improvements over back-propagation and the need for automatic topology selection. The authors do not show however that the function-approximation ability of neural networks, so important from both a mathematical and applications standpoint, is improved by their approach.
Book Description
This book constitutes the refereed proceedings of the 5th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2007, held in Valencia, Spain in April 2007, colocated with the Evo* 2007 events.
The 28 revised full papers were carefully reviewed and selected from 60 submissions. Bringing experts in computer science together with experts in bioinformatics and the biological sciences resulted in contributions on fundamental and theoretical issues, along with a wide variety of papers dealing with different applications areas, such as biomarker discovery, cell simulation and modeling, ecological modeling, fluxomics, gene networks, biotechnology, metabolomics, microarray analysis, phylogenetics, protein interactions, proteomics, sequence analysis and alignment, as well as systems biology
Book Description
This book constitutes the refereed proceedings of the 6th International Conference on Evolvable Systems, ICES 2005, held in Sitges, Spain in September 2005.
The 21 revised full papers presented were carefully reviewed and selected. The papers are organized in topical sections on fault tolerance and recovery, platforms for evolving digital systems, evolution of analog circuits, evolutionary robotics, evolutionary hardware design methodologies, bio-inspired architectures, and applications.
Average customer rating:
- A good review of new topics
|
Evolvable Systems: From Biology to Hardware: Third International Conference, ICES 2000, Edinburgh, Scotland, UK, April 17-19, 2000 Proceedings (Lecture Notes in Computer Science)
Manufacturer: Springer
ProductGroup: Book
Binding: Paperback
General
| Artificial Intelligence
| Computer Science
| Computers & Internet
| Subjects
| Books
General
| Computer Science
| Computers & Internet
| Subjects
| Books
PCs
| Hardware
| Computers & Internet
| Subjects
| Books
General
| Hardware
| Computers & Internet
| Subjects
| Books
Design & Architecture
| Hardware
| Computers & Internet
| Subjects
| Books
General
| Programming
| Computers & Internet
| Subjects
| Books
General
| Computers & Internet
| Subjects
| Books
General
| Evolution
| Science
| Subjects
| Books
Bioinformatics
| Biological Sciences
| Science
| Subjects
| Books
Mathematics
| Professional Science
| Professional & Technical
| Subjects
| Books
| Applied
| Chaos & Systems
| Geometry & Topology
| Mathematical Analysis
| Mathematical Physics
| Number Systems
| Pure Mathematics
| Transformations
| Trigonometry
All Amazon Upgrade
| Amazon Upgrade
| Stores
| Books
Computers & Internet
| Amazon Upgrade
| Stores
| Books
Professional & Technical
| Amazon Upgrade
| Stores
| Books
Science
| Amazon Upgrade
| Stores
| Books
All Titles
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Computers & Internet
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Professional
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Science
| Qualifying Textbooks - Fall 2007
| Stores
| Books
ASIN: 3540673385 |
Book Description
This book constitutes the refereed proceedings of the Third International Conference on Evolvable Systems: From Biology to Hardware, ICES 2000, held in Edinburgh, Scotland, UK, in April 2000.The 27 revised full papers presented were carefully reviewed and selected for inclusion in the proceedings. Among the topics covered are evaluation of digital systems, evolution of analog systems, embryonic electronics, bio-inspired systems, artificial neural networks, adaptive robotics, adaptive hardware platforms, molecular computing, reconfigurable systems, immune systems, and self-repair.
Customer Reviews:
A good review of new topics.......2001-07-31
This is a fine medium-advanced book on evolvable hardware. The book contains some of the very latest material you will be able to find available on print or in the internet. Specially, I find very interesting the immunotronics approach from the University of York staff.
Book Description
The three volume set LNAI 4692, LNAI 4693, and LNAI 4694, constitute the refereed proceedings of the 11th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2007, held in Vietri sul Mare, Italy, September 12-14, 2007.
The 409 revised papers presented were carefully reviewed and selected from about 1203 submissions. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; topics covered in the first volume are artificial neural networks and connectionists systems, fuzzy and neuro-fuzzy systems, evolutionary computation, machine learning and classical AI, agent systems, knowledge based and expert systems, hybrid intelligent systems, miscellaneous intelligent algorithms, intelligent vision and image processing, knowledge management and ontologies, Web intelligence, multimedia, e-learning and teaching, intelligent signal processing, control and robotics, other intelligent systems applications, papers of the experience management and engineering workshop, industrial applications of intelligent systems, as well as information engineering and applications in ubiquotous computing environments.
Book Description
The three volume set LNAI 4692, LNAI 4693, and LNAI 4694, constitute the refereed proceedings of the 11th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2007, held in Vietri sul Mare, Italy, September 12-14, 2007.
The 409 revised papers presented were carefully reviewed and selected from about 1203 submissions. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; topics covered in the first volume are artificial neural networks and connectionists systems, fuzzy and neuro-fuzzy systems, evolutionary computation, machine learning and classical AI, agent systems, knowledge based and expert systems, hybrid intelligent systems, miscellaneous intelligent algorithms, intelligent vision and image processing, knowledge management and ontologies, Web intelligence, multimedia, e-learning and teaching, intelligent signal processing, control and robotics, other intelligent systems applications, papers of the experience management and engineering workshop, industrial applications of intelligent systems, as well as information engineering and applications in ubiquotous computing environments.
Books:
- Ageless: The Naked Truth About Bioidentical Hormones
- Agile Web Development with Rails, 2nd Edition
- Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology
- An Introduction to Genetic Analysis
- An Introduction to Systems Biology: Design Principles of Biological Circuits (Chapman & Hall/Crc Mathematical and Computational Biology Series)
- Anatomy of Movement
- Animal Behavior: An Evolutionary Approach, Eighth Edition
- Atlas of Plastics Additives
- Bacteria for Breakfast: Probiotics for Good Health
- Biodiesel: Growing A New Energy Economy
Books Index
Books Home
Recommended Books
- To the Best of My Recollection
- The Mammoth Book of More Historical Whodunnits
- Sometimes a Great Notion
- Rita Mae Brown: Three Mrs. Murphy Mysteries: Wish You Were Here; Rest in Pieces; Murder at Monticell
- Saint John's Bible: Prophets
- Organic Chemistry
- Savage Summit: The Life and Death of the First Women of K2
- Arts & Architecture: The Entenza Years
- Microbiology: A Systems Approach
- North Dakota Department of Transportation roadside research project: Wildflower inventory
