Illustrated Computational Intelligence

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Illustrated Computational Intelligence

Author : Priti Srinivas Sajja
Publisher : Springer Nature
ISBN 13 : 9811595895
Total Pages : 225 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Illustrated Computational Intelligence by : Priti Srinivas Sajja

Download or read book Illustrated Computational Intelligence written by Priti Srinivas Sajja and published by Springer Nature. This book was released on 2020-11-16 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a summary of artificial intelligence and machine learning techniques in its first two chapters. The remaining chapters of the book provide everything one must know about the basic artificial intelligence to modern machine intelligence techniques including the hybrid computational intelligence technique, using the concepts of several real-life solved examples, design of projects and research ideas. The solved examples with more than 200 illustrations presented in the book are a great help to instructors, students, non–AI professionals, and researchers. Each example is discussed in detail with encoding, normalization, architecture, detailed design, process flow, and sample input/output. Summary of the fundamental concepts with solved examples is a unique combination and highlight of this book.

Computational Intelligence

Author : Andries P. Engelbrecht
Publisher : John Wiley & Sons
ISBN 13 : 9780470512500
Total Pages : 628 pages
Book Rating : 4.5/5 (125 download)

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Book Synopsis Computational Intelligence by : Andries P. Engelbrecht

Download or read book Computational Intelligence written by Andries P. Engelbrecht and published by John Wiley & Sons. This book was released on 2007-10-22 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Intelligence: An Introduction, Second Edition offers an in-depth exploration into the adaptive mechanisms that enable intelligent behaviour in complex and changing environments. The main focus of this text is centred on the computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. Engelbrecht provides readers with a wide knowledge of Computational Intelligence (CI) paradigms and algorithms; inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without any difficulty through a single Java class as part of the CI library. Key features of this second edition include: A tutorial, hands-on based presentation of the material. State-of-the-art coverage of the most recent developments in computational intelligence with more elaborate discussions on intelligence and artificial intelligence (AI). New discussion of Darwinian evolution versus Lamarckian evolution, also including swarm robotics, hybrid systems and artificial immune systems. A section on how to perform empirical studies; topics including statistical analysis of stochastic algorithms, and an open source library of CI algorithms. Tables, illustrations, graphs, examples, assignments, Java code implementing the algorithms, and a complete CI implementation and experimental framework. Computational Intelligence: An Introduction, Second Edition is essential reading for third and fourth year undergraduate and postgraduate students studying CI. The first edition has been prescribed by a number of overseas universities and is thus a valuable teaching tool. In addition, it will also be a useful resource for researchers in Computational Intelligence and Artificial Intelligence, as well as engineers, statisticians, operational researchers, and bioinformaticians with an interest in applying AI or CI to solve problems in their domains. Check out http://www.ci.cs.up.ac.za for examples, assignments and Java code implementing the algorithms.

Deep Learning Illustrated

Author : Jon Krohn
Publisher : Addison-Wesley Professional
ISBN 13 : 0135121728
Total Pages : 725 pages
Book Rating : 4.1/5 (351 download)

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Book Synopsis Deep Learning Illustrated by : Jon Krohn

Download or read book Deep Learning Illustrated written by Jon Krohn and published by Addison-Wesley Professional. This book was released on 2019-08-05 with total page 725 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come." – Tim Urban, author of Wait But Why Fully Practical, Insightful Guide to Modern Deep Learning Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely intuitive and offers a complete introduction to the discipline’s techniques. Packed with full-color figures and easy-to-follow code, it sweeps away the complexity of building deep learning models, making the subject approachable and fun to learn. World-class instructor and practitioner Jon Krohn–with visionary content from Grant Beyleveld and beautiful illustrations by Aglaé Bassens–presents straightforward analogies to explain what deep learning is, why it has become so popular, and how it relates to other machine learning approaches. Krohn has created a practical reference and tutorial for developers, data scientists, researchers, analysts, and students who want to start applying it. He illuminates theory with hands-on Python code in accompanying Jupyter notebooks. To help you progress quickly, he focuses on the versatile deep learning library Keras to nimbly construct efficient TensorFlow models; PyTorch, the leading alternative library, is also covered. You’ll gain a pragmatic understanding of all major deep learning approaches and their uses in applications ranging from machine vision and natural language processing to image generation and game-playing algorithms. Discover what makes deep learning systems unique, and the implications for practitioners Explore new tools that make deep learning models easier to build, use, and improve Master essential theory: artificial neurons, training, optimization, convolutional nets, recurrent nets, generative adversarial networks (GANs), deep reinforcement learning, and more Walk through building interactive deep learning applications, and move forward with your own artificial intelligence projects Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

COMPUTATIONAL INTELLIGENCE IN COMPLEX DECISION MAKING SYSTEMS

Author : Ruan Da
Publisher : Springer Science & Business Media
ISBN 13 : 9491216295
Total Pages : 398 pages
Book Rating : 4.4/5 (912 download)

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Book Synopsis COMPUTATIONAL INTELLIGENCE IN COMPLEX DECISION MAKING SYSTEMS by : Ruan Da

Download or read book COMPUTATIONAL INTELLIGENCE IN COMPLEX DECISION MAKING SYSTEMS written by Ruan Da and published by Springer Science & Business Media. This book was released on 2010-06-01 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, there has been a growing interest in the need for designing intelligent systems to address complex decision systems. One of the most challenging issues for the intelligent system is to effectively handle real-world uncertainties that cannot be eliminated. These uncertainties include various types of information that are incomplete, imprecise, fragmentary, not fully reliable, vague, contradictory, deficient, and overloading. The uncertainties result in a lack of the full and precise knowledge of the decision system, including the determining and selection of evaluation criteria, alternatives, weights, assignment scores, and the final integrated decision result. Computational intelligent techniques (including fuzzy logic, neural networks, and genetic algorithms etc.), which are complimentary to the existing traditional techniques, have shown great potential to solve these demanding, real-world decision problems that exist in uncertain and unpredictable environments. These technologies have formed the foundation for intelligent systems.

Computational Intelligence in Sports

Author : Iztok Fister
Publisher : Springer
ISBN 13 : 3030034909
Total Pages : 277 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Computational Intelligence in Sports by : Iztok Fister

Download or read book Computational Intelligence in Sports written by Iztok Fister and published by Springer. This book was released on 2018-12-17 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent research on computational intelligence (CI) algorithms in the field of sport. In the modern age, information technologies have greatly reduced the need for human effort in the carrying out of many daily tasks. These technologies have radically influenced the lives of humans, and the information society in general. Unfortunately, these advances have brought with them certain negative effects, including the encouragement of sedentary lifestyles and the attendant health problems such as obesity that these engender. Other modern maladies, chiefly cardiovascular disease, diabetes, and cancer, have also been on the increase. Today, sports are virtually the only activity that still connects modern humans to their original lifestyle, which was based on physical motion. This book tears familiarizing sports scientists with the foundations of computational intelligence, while at the same time presenting the problems that have arisen in the training domain to computer scientists. Lastly, the book proposes the use of an Artificial Sports Trainer designed to enhance the training of modern athletes who cannot afford the considerable expense of hiring a human personal trainer. This intelligent system can monitor performance and design and direct appropriate future training, thus promoting both healthy lifestyles and competitive success in athletes.

Computational Intelligence for Pattern Recognition

Author : Witold Pedrycz
Publisher : Springer
ISBN 13 : 3319896296
Total Pages : 428 pages
Book Rating : 4.3/5 (198 download)

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Book Synopsis Computational Intelligence for Pattern Recognition by : Witold Pedrycz

Download or read book Computational Intelligence for Pattern Recognition written by Witold Pedrycz and published by Springer. This book was released on 2018-04-30 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a comprehensive and up-to-date review of fuzzy pattern recognition. It carefully discusses a range of methodological and algorithmic issues, as well as implementations and case studies, and identifies the best design practices, assesses business models and practices of pattern recognition in real-world applications in industry, health care, administration, and business. Since the inception of fuzzy sets, fuzzy pattern recognition with its methodology, algorithms, and applications, has offered new insights into the principles and practice of pattern classification. Computational intelligence (CI) establishes a comprehensive framework aimed at fostering the paradigm of pattern recognition. The collection of contributions included in this book offers a representative overview of the advances in the area, with timely, in-depth and comprehensive material on the conceptually appealing and practically sound methodology and practices of CI-based pattern recognition.

Computational Intelligence in Data Mining

Author : G. Della Riccia
Publisher : Springer Science & Business Media
ISBN 13 : 9783211833261
Total Pages : 180 pages
Book Rating : 4.8/5 (332 download)

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Book Synopsis Computational Intelligence in Data Mining by : G. Della Riccia

Download or read book Computational Intelligence in Data Mining written by G. Della Riccia and published by Springer Science & Business Media. This book was released on 2000-05-31 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book aims to merge Computational Intelligence with Data Mining, which are both hot topics of current research and industrial development, Computational Intelligence, incorporates techniques like data fusion, uncertain reasoning, heuristic search, learning, and soft computing. Data Mining focuses on unscrambling unknown patterns or structures in very large data sets. Under the headline "Discovering Structures in Large Databases” the book starts with a unified view on 'Data Mining and Statistics – A System Point of View'. Two special techniques follow: 'Subgroup Mining', and 'Data Mining with Possibilistic Graphical Models'. "Data Fusion and Possibilistic or Fuzzy Data Analysis” is the next area of interest. An overview of possibilistic logic, nonmonotonic reasoning and data fusion is given, the coherence problem between data and non-linear fuzzy models is tackled, and outlier detection based on learning of fuzzy models is studied. In the domain of "Classification and Decomposition” adaptive clustering and visualisation of high dimensional data sets is introduced. Finally, in the section "Learning and Data Fusion” learning of special multi-agents of virtual soccer is considered. The last topic is on data fusion based on stochastic models.

Pattern Recognition and Computational Intelligence Techniques Using Matlab

Author : E. S. Gopi
Publisher : Springer Nature
ISBN 13 : 303022273X
Total Pages : 256 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Pattern Recognition and Computational Intelligence Techniques Using Matlab by : E. S. Gopi

Download or read book Pattern Recognition and Computational Intelligence Techniques Using Matlab written by E. S. Gopi and published by Springer Nature. This book was released on 2019-10-17 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the complex topic of using computational intelligence for pattern recognition in a straightforward and applicable way, using Matlab to illustrate topics and concepts. The author covers computational intelligence tools like particle swarm optimization, bacterial foraging, simulated annealing, genetic algorithm, and artificial neural networks. The Matlab based illustrations along with the code are given for every topic. Readers get a quick basic understanding of various pattern recognition techniques using only the required depth in math. The Matlab program and algorithm are given along with the running text, providing clarity and usefulness of the various techniques. Presents pattern recognition and the computational intelligence using Matlab; Includes mixtures of theory, math, and algorithms, letting readers understand the concepts quickly; Outlines an array of classifiers, various regression models, statistical tests and the techniques for pattern recognition using computational intelligence.

Springer Handbook of Computational Intelligence

Author : Janusz Kacprzyk
Publisher : Springer
ISBN 13 : 3662435055
Total Pages : 1634 pages
Book Rating : 4.6/5 (624 download)

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Book Synopsis Springer Handbook of Computational Intelligence by : Janusz Kacprzyk

Download or read book Springer Handbook of Computational Intelligence written by Janusz Kacprzyk and published by Springer. This book was released on 2015-05-28 with total page 1634 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Springer Handbook for Computational Intelligence is the first book covering the basics, the state-of-the-art and important applications of the dynamic and rapidly expanding discipline of computational intelligence. This comprehensive handbook makes readers familiar with a broad spectrum of approaches to solve various problems in science and technology. Possible approaches include, for example, those being inspired by biology, living organisms and animate systems. Content is organized in seven parts: foundations; fuzzy logic; rough sets; evolutionary computation; neural networks; swarm intelligence and hybrid computational intelligence systems. Each Part is supervised by its own Part Editor(s) so that high-quality content as well as completeness are assured.

Illustrating Evolutionary Computation with Mathematica

Author : Christian Jacob
Publisher : Morgan Kaufmann
ISBN 13 : 1558606378
Total Pages : 606 pages
Book Rating : 4.5/5 (586 download)

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Book Synopsis Illustrating Evolutionary Computation with Mathematica by : Christian Jacob

Download or read book Illustrating Evolutionary Computation with Mathematica written by Christian Jacob and published by Morgan Kaufmann. This book was released on 2001 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: Part 1: Fascinating Evolution -- Part 2: Evolutionary Computation -- Part 3: If Darwin was a Programmer -- Part 4: Evolution of Developmental Programs.

Advances in Computational Intelligence

Author : Ignacio Rojas
Publisher : Springer
ISBN 13 : 3030205185
Total Pages : 926 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Advances in Computational Intelligence by : Ignacio Rojas

Download or read book Advances in Computational Intelligence written by Ignacio Rojas and published by Springer. This book was released on 2019-06-05 with total page 926 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNCS 10305 and LNCS 10306 constitutes the refereed proceedings of the 15th International Work-Conference on Artificial Neural Networks, IWANN 2019, held at Gran Canaria, Spain, in June 2019. The 150 revised full papers presented in this two-volume set were carefully reviewed and selected from 210 submissions. The papers are organized in topical sections on machine learning in weather observation and forecasting; computational intelligence methods for time series; human activity recognition; new and future tendencies in brain-computer interface systems; random-weights neural networks; pattern recognition; deep learning and natural language processing; software testing and intelligent systems; data-driven intelligent transportation systems; deep learning models in healthcare and biomedicine; deep learning beyond convolution; artificial neural network for biomedical image processing; machine learning in vision and robotics; system identification, process control, and manufacturing; image and signal processing; soft computing; mathematics for neural networks; internet modeling, communication and networking; expert systems; evolutionary and genetic algorithms; advances in computational intelligence; computational biology and bioinformatics.

Computational Intelligence Paradigms

Author : S. Sumathi
Publisher : CRC Press
ISBN 13 : 9781439809037
Total Pages : 851 pages
Book Rating : 4.8/5 (9 download)

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Book Synopsis Computational Intelligence Paradigms by : S. Sumathi

Download or read book Computational Intelligence Paradigms written by S. Sumathi and published by CRC Press. This book was released on 2010-01-05 with total page 851 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering a wide range of programming examples implemented in MATLAB®, Computational Intelligence Paradigms: Theory and Applications Using MATLAB® presents theoretical concepts and a general framework for computational intelligence (CI) approaches, including artificial neural networks, fuzzy systems, evolutionary computation, genetic algorithms and programming, and swarm intelligence. It covers numerous intelligent computing methodologies and algorithms used in CI research. The book first focuses on neural networks, including common artificial neural networks; neural networks based on data classification, data association, and data conceptualization; and real-world applications of neural networks. It then discusses fuzzy sets, fuzzy rules, applications of fuzzy systems, and different types of fused neuro-fuzzy systems, before providing MATLAB illustrations of ANFIS, classification and regression trees, fuzzy c-means clustering algorithms, fuzzy ART map, and Takagi–Sugeno inference systems. The authors also describe the history, advantages, and disadvantages of evolutionary computation and include solved MATLAB programs to illustrate the implementation of evolutionary computation in various problems. After exploring the operators and parameters of genetic algorithms, they cover the steps and MATLAB routines of genetic programming. The final chapter introduces swarm intelligence and its applications, particle swarm optimization, and ant colony optimization. Full of worked examples and end-of-chapter questions, this comprehensive book explains how to use MATLAB to implement CI techniques for the solution of biological problems. It will help readers with their work on evolution dynamics, self-organization, natural and artificial morphogenesis, emergent collective behaviors, swarm intelligence, evolutionary strategies, genetic programming, and the evolution of social behaviors.

Understanding COVID-19: The Role of Computational Intelligence

Author : Janmenjoy Nayak
Publisher : Springer Nature
ISBN 13 : 3030747611
Total Pages : 569 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Understanding COVID-19: The Role of Computational Intelligence by : Janmenjoy Nayak

Download or read book Understanding COVID-19: The Role of Computational Intelligence written by Janmenjoy Nayak and published by Springer Nature. This book was released on 2021-07-27 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive description of the novel coronavirus infection, spread analysis, and related challenges for the effective combat and treatment. With a detailed discussion on the nature of transmission of COVID-19, few other important aspects such as disease symptoms, clinical application of radiomics, image analysis, antibody treatments, risk analysis, drug discovery, emotion and sentiment analysis, virus infection, and fatality prediction are highlighted. The main focus is laid on different issues and futuristic challenges of computational intelligence techniques in solving and identifying the solutions for COVID-19. The book drops radiance on the reasons for the growing profusion and complexity of data in this sector. Further, the book helps to focus on further research challenges and directions of COVID-19 for the practitioners as well as researchers.

Introducing Artificial Intelligence

Author : Henry Brighton
Publisher : Totem Books
ISBN 13 : 9781840468410
Total Pages : 0 pages
Book Rating : 4.4/5 (684 download)

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Book Synopsis Introducing Artificial Intelligence by : Henry Brighton

Download or read book Introducing Artificial Intelligence written by Henry Brighton and published by Totem Books. This book was released on 2007 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Can machines really think? Is the mind just a complicated computer program? Half a century of research into Artificial Intelligence has resulted in machines capable of beating the best human chess players and humanoid robots that can walk and interact with us. Yet exactly should we go about building a truly intelligent machine? Introducing Artificial Intelligence focuses on the major issues behind one of the hardest scientific problems ever undertaken.

Advances in Computational Intelligence Systems

Author : Thomas Jansen
Publisher : Springer Nature
ISBN 13 : 3030870944
Total Pages : 579 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Advances in Computational Intelligence Systems by : Thomas Jansen

Download or read book Advances in Computational Intelligence Systems written by Thomas Jansen and published by Springer Nature. This book was released on 2021-11-17 with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the papers presented at the 20th UK Workshop on Computational Intelligence (UKCI 2021), held virtually by Aberystwyth University, 8–10th September 2021. This marks the 20th anniversary of UKCI; a testament to the increasing role and importance of Computational Intelligence (CI) and the continuing interest in its development. UKCI provides a forum for the academic community and industry to share ideas and experience in this field. EDMA 2021, the 4th International Engineering Data- and Model-Driven Applications workshop, is also incorporated and held in conjunction with UKCI 2021. Paper submissions were invited in the areas of fuzzy systems, neural networks, evolutionary computation, machine learning, data mining, cognitive computing, intelligent robotics, hybrid methods, deep learning and applications of CI.

Breakthroughs in Software Science and Computational Intelligence

Author : Wang, Yingxu
Publisher : IGI Global
ISBN 13 : 1466602651
Total Pages : 516 pages
Book Rating : 4.4/5 (666 download)

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Book Synopsis Breakthroughs in Software Science and Computational Intelligence by : Wang, Yingxu

Download or read book Breakthroughs in Software Science and Computational Intelligence written by Wang, Yingxu and published by IGI Global. This book was released on 2012-03-31 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book charts the new ground broken by researchers exploring software science as it interacts with computational intelligence"--

Computational Intelligence

Author : Leszek Rutkowski
Publisher : Springer Science & Business Media
ISBN 13 : 3540762876
Total Pages : 519 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Computational Intelligence by : Leszek Rutkowski

Download or read book Computational Intelligence written by Leszek Rutkowski and published by Springer Science & Business Media. This book was released on 2008-05-29 with total page 519 pages. Available in PDF, EPUB and Kindle. Book excerpt: This quite simply superb book focuses on various techniques of computational intelligence, both single ones and those which form hybrid methods. These techniques are today commonly applied to issues of artificial intelligence. The book presents methods of knowledge representation using different techniques, namely the rough sets, type-1 fuzzy sets and type-2 fuzzy sets. Next up, various neural network architectures are presented and their learning algorithms are derived. Then, the family of evolutionary algorithms is discussed, including connections between these techniques and neural networks and fuzzy systems. Finally, various methods of data partitioning and algorithms of automatic data clustering are given and new neuro-fuzzy architectures are studied and compared.