Foundations Of Computational Intelligence Volume 2

DOWNLOAD

Download Foundations Of Computational Intelligence Volume 2 PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Foundations Of Computational Intelligence Volume 2 book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page

Foundations Of Computational Intelligence Volume 2

DOWNLOAD
Author : Aboul-Ella Hassanien
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-06-15

Foundations Of Computational Intelligence Volume 2 written by Aboul-Ella Hassanien and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-15 with Mathematics categories.

Foundations of Computational Intelligence Volume 2: Approximation Reasoning: Theoretical Foundations and Applications Human reasoning usually is very approximate and involves various types of - certainties. Approximate reasoning is the computational modelling of any part of the process used by humans to reason about natural phenomena or to solve real world problems. The scope of this book includes fuzzy sets, Dempster-Shafer theory, multi-valued logic, probability, random sets, and rough set, near set and hybrid intelligent systems. Besides research articles and expository papers on t- ory and algorithms of approximation reasoning, papers on numerical experiments and real world applications were also encouraged. This Volume comprises of 12 chapters including an overview chapter providing an up-to-date and state-of-the research on the applications of Computational Intelligence techniques for - proximation reasoning. The Volume is divided into 2 parts: Part-I: Approximate Reasoning – Theoretical Foundations Part-II: Approximate Reasoning – Success Stories and Real World Applications Part I on Approximate Reasoning – Theoretical Foundations contains four ch- ters that describe several approaches of fuzzy and Para consistent annotated logic approximation reasoning. In Chapter 1, “Fuzzy Sets, Near Sets, and Rough Sets for Your Computational Intelligence Toolbox” by Peters considers how a user might utilize fuzzy sets, near sets, and rough sets, taken separately or taken together in hybridizations as part of a computational intelligence toolbox. In multi-criteria decision making, it is necessary to aggregate (combine) utility values corresponding to several criteria (parameters).

Foundations Of Computational Intelligence Volume 5

DOWNLOAD
Author : Ajith Abraham
language : en
Publisher: Springer
Release Date : 2009-07-11

Foundations Of Computational Intelligence Volume 5 written by Ajith Abraham and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-11 with Technology & Engineering categories.

Foundations of Computational Intelligence Volume 5: Function Approximation and Classification Approximation theory is that area of analysis which is concerned with the ability to approximate functions by simpler and more easily calculated functions. It is an area which, like many other fields of analysis, has its primary roots in the mat- matics. The need for function approximation and classification arises in many branches of applied mathematics, computer science and data mining in particular. This edited volume comprises of 14 chapters, including several overview Ch- ters, which provides an up-to-date and state-of-the art research covering the theory and algorithms of function approximation and classification. Besides research ar- cles and expository papers on theory and algorithms of function approximation and classification, papers on numerical experiments and real world applications were also encouraged. The Volume is divided into 2 parts: Part-I: Function Approximation and Classification – Theoretical Foundations Part-II: Function Approximation and Classification – Success Stories and Real World Applications Part I on Function Approximation and Classification – Theoretical Foundations contains six chapters that describe several approaches Feature Selection, the use Decomposition of Correlation Integral, Some Issues on Extensions of Information and Dynamic Information System and a Probabilistic Approach to the Evaluation and Combination of Preferences Chapter 1 “Feature Selection for Partial Least Square Based Dimension Red- tion” by Li and Zeng investigate a systematic feature reduction framework by combing dimension reduction with feature selection. To evaluate the proposed framework authors used four typical data sets.

Foundations Of Computational Intelligence

DOWNLOAD
Author : Ajith Abraham
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-04-21

Foundations Of Computational Intelligence written by Ajith Abraham and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-21 with Mathematics categories.

Foundations of Computational Intelligence Volume 4: Bio-Inspired Data Mining Theoretical Foundations and Applications Recent advances in the computing and electronics technology, particularly in sensor devices, databases and distributed systems, are leading to an exponential growth in the amount of data stored in databases. It has been estimated that this amount doubles every 20 years. For some applications, this increase is even steeper. Databases storing DNA sequence, for example, are doubling their size every 10 months. This growth is occurring in several applications areas besides bioinformatics, like financial transactions, government data, environmental mo- toring, satellite and medical images, security data and web. As large organizations recognize the high value of data stored in their databases and the importance of their data collection to support decision-making, there is a clear demand for - phisticated Data Mining tools. Data mining tools play a key role in the extraction of useful knowledge from databases. They can be used either to confirm a parti- lar hypothesis or to automatically find patterns. In the second case, which is - lated to this book, the goal may be either to describe the main patterns present in dataset, what is known as descriptive Data Mining or to find patterns able to p- dict behaviour of specific attributes or features, known as predictive Data Mining. While the first goal is associated with tasks like clustering, summarization and association, the second is found in classification and regression problems.

Computer And Information Science 2009

DOWNLOAD
Author : Roger Lee
language : en
Publisher: Springer
Release Date : 2009-05-01

Computer And Information Science 2009 written by Roger Lee and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-01 with Technology & Engineering categories.

This volume includes the best papers of the IEEE/ACIS International Conference on Computer and Information Science, ICIS 2009, held on June 2009 in Shanghai, China.

Biologically Inspired Optimisation Methods

DOWNLOAD
Author : Andrew Lewis
language : en
Publisher: Springer
Release Date : 2009-05-12

Biologically Inspired Optimisation Methods written by Andrew Lewis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-12 with Technology & Engineering categories.

This book covers the latest theories, applications and techniques in Biologically-Inspired Optimisation Methods. Many chapters derive from studies presented at workshops and international conferences on e-Science, Grid Computing and Evolutionary computation.

Complex Networks

DOWNLOAD
Author : Ronaldo Menezes
language : en
Publisher: Springer
Release Date : 2009-04-22

Complex Networks written by Ronaldo Menezes and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-22 with Computers categories.

Though the reductionist approachto biology and medicine has led to several imp- tant advances, further progresses with respect to the remaining challenges require integration of representation, characterization and modeling of the studied systems along a wide range of spatial and time scales. Such an approach, intrinsically - lated to systems biology, is poised to ultimately turning biology into a more precise and synthetic discipline, paving the way to extensive preventive and regenerative medicine [1], drug discovery [20] and treatment optimization [24]. A particularly appealing and effective approach to addressing the complexity of interactions inherent to the biological systems is provided by the new area of c- plex networks [34, 30, 8, 13, 12]. Basically, it is an extension of graph theory [10], focusing on the modeling, representation, characterization, analysis and simulation ofcomplexsystemsbyconsideringmanyelementsandtheirinterconnections.C- plex networks concepts and methods have been used to study disease [17], tr- scription networks [5, 6, 4], protein-protein networks [22, 36, 16, 39], metabolic networks [23] and anatomy [40].

Computational Intelligence Techniques For Bioprocess Modelling Supervision And Control

DOWNLOAD
Author : Maria Carmo Nicoletti
language : en
Publisher: Springer
Release Date : 2009-07-09

Computational Intelligence Techniques For Bioprocess Modelling Supervision And Control written by Maria Carmo Nicoletti and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-09 with Technology & Engineering categories.

Computational Intelligence (CI) and Bioprocess are well-established research areas which have much to offer each other. Under the perspective of the CI area, Biop- cess can be considered a vast application area with a growing number of complex and challenging tasks to be dealt with, whose solutions can contribute to boosting the development of new intelligent techniques as well as to help the refinement and s- cialization of many of the already existing techniques. Under the perspective of the Bioprocess area, CI can be considered a useful repertoire of theories, methods and techniques that can contribute and offer interesting alternative approaches for solving many of its problems, particularly those hard to solve using conventional techniques. Although throughout the past years CI and Bioprocess areas have accumulated substantial specific knowledge and progress has been quick and with a high degree of success, we believe there is still a long way to go in order to use the potentialities of the available CI techniques and knowledge at their full extent, as tools for supporting problem solving in bioprocesses. One of the reasons is the fact that both areas have progressed steadily and have been continuously accumulating and refining specific knowledge; another reason is the high level of technical expertise demanded by each of them. The acquisition of technical skills, experience and good insights in either of the two areas is very demanding and a hard task to be accomplished by any professional.

Software Engineering Artificial Intelligence Networking And Parallel Distributed Computing

DOWNLOAD
Author : Roger Lee
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-04-30

Software Engineering Artificial Intelligence Networking And Parallel Distributed Computing written by Roger Lee and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-30 with Mathematics categories.

The purpose of the 10th ACIS International Conference on Software Engineering Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD rd 2009), held in Daegu, Korea on May 27–29, 2009, the 3 International Workshop st on e-Activity (IWEA 2009) and the 1 International Workshop on Enterprise Architecture Challenges and Responses (WEACR 2009) is to aim at bringing together researchers and scientist, businessmen and entrepreneurs, teachers and students to discuss the numerous fields of computer science, and to share ideas and information in a meaningful way. Our conference officers selected the best 24 papers from those papers accepted for presentation at the conference in order to publish them in this volume. The papers were chosen based on review scores submitted by members of the program committee, and underwent further rounds of rigorous review. In chapter 1, Igor Crk and Chris Gniady propose a network-aware energy m- agement mechanism that provides a low-cost solution that can significantly reduce energy consumption in the entire system while maintaining responsiveness of local interactive workloads. Their dynamic mechanisms reduce the decision delay before the disk is spun-up, reduce the number of erroneous spin-ups in local wo- stations, decrease the network bandwidth, and reduce the energy consumption of individual drives. In chapter 2, Yoshihito Saito and Tokuro Matsuo describe a task allocation mechanism and its performance concerning with software developing. They run simulations and discuss the results in terms of effective strategies of task allocation.

Hybrid Self Organizing Modeling Systems

DOWNLOAD
Author : Godfrey C Onwubolu
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-06-15

Hybrid Self Organizing Modeling Systems written by Godfrey C Onwubolu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-15 with Mathematics categories.

The Group Method of Data Handling (GMDH) is a typical inductive modeling method that is built on principles of self-organization for modeling complex systems. This book clearly presents hybrids of some computational intelligence techniques and GMDH approach.

Foundations Of Computational Intelligence

DOWNLOAD
Author : Aboul-Ella Hassanien
language : en
Publisher: Springer
Release Date : 2009-05-02

Foundations Of Computational Intelligence written by Aboul-Ella Hassanien and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-02 with Computers categories.

Foundations of Computational Intelligence Volume 1: Learning and Approximation: Theoretical Foundations and Applications Learning methods and approximation algorithms are fundamental tools that deal with computationally hard problems and problems in which the input is gradually disclosed over time. Both kinds of problems have a large number of applications arising from a variety of fields, such as algorithmic game theory, approximation classes, coloring and partitioning, competitive analysis, computational finance, cuts and connectivity, inapproximability results, mechanism design, network design, packing and covering, paradigms for design and analysis of approxi- tion and online algorithms, randomization techniques, real-world applications, scheduling problems and so on. The past years have witnessed a large number of interesting applications using various techniques of Computational Intelligence such as rough sets, connectionist learning; fuzzy logic; evolutionary computing; artificial immune systems; swarm intelligence; reinforcement learning, intelligent multimedia processing etc. . In spite of numerous successful applications of C- putational Intelligence in business and industry, it is sometimes difficult to explain the performance of these techniques and algorithms from a theoretical perspective. Therefore, we encouraged authors to present original ideas dealing with the inc- poration of different mechanisms of Computational Intelligent dealing with Lea- ing and Approximation algorithms and underlying processes. This edited volume comprises 15 chapters, including an overview chapter, which provides an up-to-date and state-of-the art research on the application of Computational Intelligence for learning and approximation.