Hybrid Computational Intelligence

Hybrid Computational Intelligence
Author: Siddhartha Bhattacharyya,Vaclav Snasel,Deepak Gupta,Ashish Khanna
Publsiher: Academic Press
Total Pages: 250
Release: 2020-03-05
ISBN 10: 012818700X
ISBN 13: 9780128187005
Language: EN, FR, DE, ES & NL

Hybrid Computational Intelligence Book Review:

Hybrid Computational Intelligence: Challenges and Utilities is a comprehensive resource that begins with the basics and main components of computational intelligence. It brings together many different aspects of the current research on HCI technologies, such as neural networks, support vector machines, fuzzy logic and evolutionary computation, while also covering a wide range of applications and implementation issues, from pattern recognition and system modeling, to intelligent control problems and biomedical applications. The book also explores the most widely used applications of hybrid computation as well as the history of their development. Each individual methodology provides hybrid systems with complementary reasoning and searching methods which allow the use of domain knowledge and empirical data to solve complex problems. Provides insights into the latest research trends in hybrid intelligent algorithms and architectures Focuses on the application of hybrid intelligent techniques for pattern mining and recognition, in big data analytics, and in human-computer interaction Features hybrid intelligent applications in biomedical engineering and healthcare informatics

Hybrid Computational Intelligence

Hybrid Computational Intelligence
Author: Siddhartha Bhattacharyya,Václav Snášel,Indrajit Pan,Debashis De
Publsiher: CRC Press
Total Pages: 220
Release: 2019-10-01
ISBN 10: 042984266X
ISBN 13: 9780429842665
Language: EN, FR, DE, ES & NL

Hybrid Computational Intelligence Book Review:

Hybrid computational intelligent techniques are efficient in dealing with the real-world problems encountered in engineering fields. The primary objective of this book is to provide an exhaustive introduction as well as review of the hybrid computational intelligent paradigm, with supportive case studies. In addition, it aims to provide a gallery of engineering applications where this computing paradigm can be effectively use. Finally, it focuses on the recent quantum inspired hybrid intelligence to develop intelligent solutions for the future. The book also incorporates video demonstrations of each application for better understanding of the subject matter.

Tree Structure based Hybrid Computational Intelligence

Tree Structure based Hybrid Computational Intelligence
Author: Yuehui Chen,Ajith Abraham
Publsiher: Springer
Total Pages: 206
Release: 2009-11-03
ISBN 10: 9783642047381
ISBN 13: 3642047386
Language: EN, FR, DE, ES & NL

Tree Structure based Hybrid Computational Intelligence Book Review:

Research in computational intelligence is directed toward building thinking machines and improving our understanding of intelligence. As evident, the ultimate achievement in this field would be to mimic or exceed human cognitive capabilities including reasoning, recognition, creativity, emotions, understanding, learning and so on. In this book, the authors illustrate an hybrid computational intelligence framework and it applications for various problem solving tasks. Based on tree-structure based encoding and the specific function operators, the models can be flexibly constructed and evolved by using simple computational intelligence techniques. The main idea behind this model is the flexible neural tree, which is very adaptive, accurate and efficient. Based on the pre-defined instruction/operator sets, a flexible neural tree model can be created and evolved. This volume comprises of 6 chapters including an introductory chapter giving the fundamental definitions and the last Chapter provides some important research challenges. Academics, scientists as well as engineers engaged in research, development and application of computational intelligence techniques and data mining will find the comprehensive coverage of this book invaluable.

Springer Handbook of Computational Intelligence

Springer Handbook of Computational Intelligence
Author: Janusz Kacprzyk,Witold Pedrycz
Publsiher: Springer
Total Pages: 1634
Release: 2015-05-28
ISBN 10: 3662435055
ISBN 13: 9783662435052
Language: EN, FR, DE, ES & NL

Springer Handbook of Computational Intelligence Book Review:

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.

Tree Structure based Hybrid Computational Intelligence

Tree Structure based Hybrid Computational Intelligence
Author: Yuehui Chen,Ajith Abraham
Publsiher: Springer Science & Business Media
Total Pages: 206
Release: 2009-11-27
ISBN 10: 3642047394
ISBN 13: 9783642047398
Language: EN, FR, DE, ES & NL

Tree Structure based Hybrid Computational Intelligence Book Review:

Research in computational intelligence is directed toward building thinking machines and improving our understanding of intelligence. As evident, the ultimate achievement in this field would be to mimic or exceed human cognitive capabilities including reasoning, recognition, creativity, emotions, understanding, learning and so on. In this book, the authors illustrate an hybrid computational intelligence framework and it applications for various problem solving tasks. Based on tree-structure based encoding and the specific function operators, the models can be flexibly constructed and evolved by using simple computational intelligence techniques. The main idea behind this model is the flexible neural tree, which is very adaptive, accurate and efficient. Based on the pre-defined instruction/operator sets, a flexible neural tree model can be created and evolved. This volume comprises of 6 chapters including an introductory chapter giving the fundamental definitions and the last Chapter provides some important research challenges. Academics, scientists as well as engineers engaged in research, development and application of computational intelligence techniques and data mining will find the comprehensive coverage of this book invaluable.

Computational Intelligence

Computational Intelligence
Author: Mircea Gh. Negoita,Daniel Neagu,Vasile Palade
Publsiher: Springer Science & Business Media
Total Pages: 213
Release: 2005-02-17
ISBN 10: 9783540232193
ISBN 13: 3540232192
Language: EN, FR, DE, ES & NL

Computational Intelligence Book Review:

Hybrid Intelligent Systems has become an important research topic in computer science and a key application field in science and engineering. This book offers a gentle introduction to the engineering aspects of hybrid intelligent systems, also emphasizing the interrelation with the main intelligent technologies such as genetic algorithms – evolutionary computation, neural networks, fuzzy systems, evolvable hardware, DNA computing, artificial immune systems. A unitary whole of theory and application, the book provides readers with the fundamentals, background information, and practical methods for building a hybrid intelligent system. It treats a panoply of applications, including many in industry, educational systems, forecasting, financial engineering, and bioinformatics. This volume is useful to newcomers in the field because it quickly familiarizes them with engineering elements of developing hybrid intelligent systems and a wide range of real applications, including non-industrial applications. Researchers, developers and technically oriented managers can use the book for developing both new hybrid intelligent systems approaches and new applications requiring the hybridization of the typical tools and concepts to computational intelligence.

Hybrid Computational Intelligence

Hybrid Computational Intelligence
Author: Siddhartha Bhattacharyya,Václav Snásel,Ashish Khanna,Deepak Gupta
Publsiher: Academic Press
Total Pages: 252
Release: 2020-03-06
ISBN 10: 0128186992
ISBN 13: 9780128186992
Language: EN, FR, DE, ES & NL

Hybrid Computational Intelligence Book Review:

Hybrid Computational Intelligence: Challenges and Utilities is a comprehensive resource that begins with the basics and main components of computational intelligence. It brings together many different aspects of the current research on HCI technologies, such as neural networks, support vector machines, fuzzy logic and evolutionary computation, while also covering a wide range of applications and implementation issues, from pattern recognition and system modeling, to intelligent control problems and biomedical applications. The book also explores the most widely used applications of hybrid computation as well as the history of their development. Each individual methodology provides hybrid systems with complementary reasoning and searching methods which allow the use of domain knowledge and empirical data to solve complex problems.

Hybrid Computational Intelligence Systems Based on Statistical and Neural Networks Methods for Time Series Forecasting

Hybrid Computational Intelligence Systems Based on Statistical and Neural Networks Methods for Time Series Forecasting
Author: Saeed Matroushi
Publsiher: Unknown
Total Pages: 308
Release: 2011
ISBN 10: 1928374650XXX
ISBN 13: OCLC:760070839
Language: EN, FR, DE, ES & NL

Hybrid Computational Intelligence Systems Based on Statistical and Neural Networks Methods for Time Series Forecasting Book Review:

Parameter Learning of Bayesian Network by Hybrid Computational Intelligence Approach

Parameter Learning of Bayesian Network by Hybrid Computational Intelligence Approach
Author: Honghua Dai,Gang Li,Yiqing Tu
Publsiher: Unknown
Total Pages: 6
Release: 2002
ISBN 10: 1928374650XXX
ISBN 13: OCLC:223344145
Language: EN, FR, DE, ES & NL

Parameter Learning of Bayesian Network by Hybrid Computational Intelligence Approach Book Review:

Illustrated Computational Intelligence

Illustrated Computational Intelligence
Author: Priti Srinivas Sajja
Publsiher: Springer Nature
Total Pages: 225
Release: 2020-11-16
ISBN 10: 9811595895
ISBN 13: 9789811595899
Language: EN, FR, DE, ES & NL

Illustrated Computational Intelligence Book Review:

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 in Systems and Control Design and Applications

Computational Intelligence in Systems and Control Design and Applications
Author: S.G. Tzafestas
Publsiher: Springer Science & Business Media
Total Pages: 376
Release: 2001-11-30
ISBN 10: 9781402003943
ISBN 13: 1402003943
Language: EN, FR, DE, ES & NL

Computational Intelligence in Systems and Control Design and Applications Book Review:

This book contains thirty timely contributions in the emerging field of Computational Intelligence (CI) with reference to system control design and applications. The three basic constituents ofCI are neural networks (NNs). fuzzy logic (FL) I fuzzy reasoning (FR). and genetic algorithms (GAs). NNs mimic the distributed functioning of the human brain and consist of many. rather simple. building elements (called artificial neurons) which are controlled by adaptive parameters and are able to incorporate via learning the knowledge provided by the environment, and thus respond intelligently to new stimuli. Fuzzy logic (FL) provides the means to build systems that can reason linguistically under uncertainty like the human experts (common sense reasoning). Both NNs and FL I FR are among the most widely used tools for modeling unknown systems with nonlinear behavior. FL suits better when there is some kind of knowledge about the system. such as, for example, the linguistic information of a human expert. On the other hand. NNs possess unique learning and generalization capabilities that allow the user to construct very accurate models of nonlinear systems simply using input-output data. GAs offer an interesting set of generic tools for systematic random search optimization following the mechanisms of natural genetics. In hybrid Computational Intelligence - based systems these three tools (NNs, FL, GAs) are combined in several synergetic ways producing integrated tools with enhanced learning, generalization. universal approximation. reasoning and optimization abilities.

Computational Intelligence for Information Retrieval

Computational Intelligence for Information Retrieval
Author: Dharmender Saini,Gopal Chaudhary,Vedika Gupta
Publsiher: CRC Press
Total Pages: 292
Release: 2021-12-15
ISBN 10: 1000484726
ISBN 13: 9781000484724
Language: EN, FR, DE, ES & NL

Computational Intelligence for Information Retrieval Book Review:

This book provides a thorough understanding of the integration of computational intelligence with information retrieval including content-based image retrieval using intelligent techniques, hybrid computational intelligence for pattern recognition, intelligent innovative systems, and protecting and analysing big data on cloud platforms. The book aims to investigate how computational intelligence frameworks are going to improve information retrieval systems. The emerging and promising state-of-the-art of human–computer interaction is the motivation behind this book. The book covers a wide range of topics, starting from the tools and languages of artificial intelligence to its philosophical implications, and thus provides a plethora of theoretical as well as experimental research, along with surveys and impact studies. Further, the book aims to showcase the basics of information retrieval and computational intelligence for beginners, as well as their integration, and challenge discussions for existing practitioners, including using hybrid application of augmented reality, computational intelligence techniques for recommendation systems in big data, and a fuzzy-based approach for characterization and identification of sentiments.

Recent Advances of Hybrid Intelligent Systems Based on Soft Computing

Recent Advances of Hybrid Intelligent Systems Based on Soft Computing
Author: Patricia Melin,Oscar Castillo,Janusz Kacprzyk
Publsiher: Springer Nature
Total Pages: 341
Release: 2020-11-06
ISBN 10: 3030587282
ISBN 13: 9783030587284
Language: EN, FR, DE, ES & NL

Recent Advances of Hybrid Intelligent Systems Based on Soft Computing Book Review:

This book describes recent advances on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and their application in areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing. There are some papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There are also some papers that present theory and practice of meta-heuristics in different areas of application. Another group of papers describes diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical applications. There are also some papers that present theory and practice of neural networks in different areas of application. In addition, there are papers that present theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, there are some papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition problems.

Advanced Machine Vision Paradigms for Medical Image Analysis

Advanced Machine Vision Paradigms for Medical Image Analysis
Author: Tapan K. Gandhi,Siddhartha Bhattacharyya,Sourav De,Debanjan Konar,Sandip Dey
Publsiher: Academic Press
Total Pages: 308
Release: 2020-08-11
ISBN 10: 0128192968
ISBN 13: 9780128192962
Language: EN, FR, DE, ES & NL

Advanced Machine Vision Paradigms for Medical Image Analysis Book Review:

Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis

Hybrid Metaheuristics

Hybrid Metaheuristics
Author: Christian Blum,Andrea Roli,Michael Sampels
Publsiher: Springer
Total Pages: 290
Release: 2008-06-24
ISBN 10: 3540782958
ISBN 13: 9783540782957
Language: EN, FR, DE, ES & NL

Hybrid Metaheuristics Book Review:

Optimization problems are of great importance across a broad range of fields. They can be tackled, for example, by approximate algorithms such as metaheuristics. This book is intended both to provide an overview of hybrid metaheuristics to novices of the field, and to provide researchers from the field with a collection of some of the most interesting recent developments. The authors involved in this book are among the top researchers in their domain.

Hybrid Machine Intelligence for Medical Image Analysis

Hybrid Machine Intelligence for Medical Image Analysis
Author: Siddhartha Bhattacharyya,Debanjan Konar,Jan Platos,Chinmoy Kar,Kalpana Sharma
Publsiher: Springer
Total Pages: 293
Release: 2019-08-08
ISBN 10: 9811389306
ISBN 13: 9789811389306
Language: EN, FR, DE, ES & NL

Hybrid Machine Intelligence for Medical Image Analysis Book Review:

The book discusses the impact of machine learning and computational intelligent algorithms on medical image data processing, and introduces the latest trends in machine learning technologies and computational intelligence for intelligent medical image analysis. The topics covered include automated region of interest detection of magnetic resonance images based on center of gravity; brain tumor detection through low-level features detection; automatic MRI image segmentation for brain tumor detection using the multi-level sigmoid activation function; and computer-aided detection of mammographic lesions using convolutional neural networks.

Soft Computing for Hybrid Intelligent Systems

Soft Computing for Hybrid Intelligent Systems
Author: Oscar Castillo,Patricia Melin,Witold Pedrycz
Publsiher: Springer
Total Pages: 448
Release: 2008-09-10
ISBN 10: 354070812X
ISBN 13: 9783540708124
Language: EN, FR, DE, ES & NL

Soft Computing for Hybrid Intelligent Systems Book Review:

We describe in this book, new methods and applications of hybrid intelligent systems using soft computing techniques. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and evolutionary al- rithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of intelligent control, which are basically papers that use hybrid systems to solve particular problems of control. The second part contains papers with the main theme of pattern recognition, which are basically papers using soft computing techniques for achieving pattern recognition in different applications. The third part contains papers with the themes of intelligent agents and social systems, which are papers that apply the ideas of agents and social behavior to solve real-world problems. The fourth part contains papers that deal with the hardware implementation of intelligent systems for solving particular problems. The fifth part contains papers that deal with modeling, simulation and optimization for real-world applications.

Computational Intelligence for Information Retrieval

Computational Intelligence for Information Retrieval
Author: Dharmender Saini,Gopal Chaudhary,Vedika Gupta
Publsiher: Sensors Communication for Urban Intelligence
Total Pages: 278
Release: 2021-12
ISBN 10: 9780367680800
ISBN 13: 0367680807
Language: EN, FR, DE, ES & NL

Computational Intelligence for Information Retrieval Book Review:

This book provides a thorough understanding of the integration of computational intelligence with information retrieval including content-based image retrieval using intelligent techniques, hybrid computational intelligence for pattern recognition, intelligent innovative systems, and protecting and analysing big data on cloud platforms. The book aims to investigate how computational intelligence frameworks are going to improve information retrieval systems. The emerging and promising state-of-the-art of human-computer interaction is the motivation behind this book. The book covers a wide range of topics, starting from the tools and languages of artificial intelligence to its philosophical implications, and thus provides a plethora of theoretical as well as experimental research, along with surveys and impact studies. Further, the book aims to showcase the basics of information retrieval and computational intelligence for beginners, as well as their integration, and challenge discussions for existing practitioners, including using hybrid application of augmented reality, computational intelligence techniques for recommendation systems in big data, and a fuzzy-based approach for characterization and identification of sentiments.

Trends in Deep Learning Methodologies

Trends in Deep Learning Methodologies
Author: Vincenzo Piuri,Sandeep Raj,Angelo Genovese,Rajshree Srivastava
Publsiher: Academic Press
Total Pages: 306
Release: 2020-11-12
ISBN 10: 0128232684
ISBN 13: 9780128232682
Language: EN, FR, DE, ES & NL

Trends in Deep Learning Methodologies Book Review:

Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more. In recent years, many powerful algorithms have been developed for matching patterns in data and making predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher level representations of raw data. Earlier, it was a common requirement to have a domain expert to develop a specific model for each specific application, however, recent advancements in representation learning algorithms allow researchers across various subject domains to automatically learn the patterns and representation of the given data for the development of specific models. Provides insights into the theory, algorithms, implementation and the application of deep learning techniques Covers a wide range of applications of deep learning across smart healthcare and smart engineering Investigates the development of new models and how they can be exploited to find appropriate solutions

Hybrid Artificial Intelligent Systems

Hybrid Artificial Intelligent Systems
Author: Emilio S. Corchado Rodriguez,Vaclav Snasel,Ajith Abraham,Michal Wozniak,Manuel Grana,Sung-Bae Cho
Publsiher: Springer Science & Business Media
Total Pages: 606
Release: 2012-03-21
ISBN 10: 3642289304
ISBN 13: 9783642289309
Language: EN, FR, DE, ES & NL

Hybrid Artificial Intelligent Systems Book Review:

The two LNAI volumes 7208 and 7209 constitute the proceedings of the 7th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2012, held in Salamanca, Spain, in March 2012. The 118 papers published in these proceedings were carefully reviewed and selected from 293 submissions. They are organized in topical sessions on agents and multi agents systems, HAIS applications, cluster analysis, data mining and knowledge discovery, evolutionary computation, learning algorithms, systems, man, and cybernetics by HAIS workshop, methods of classifier fusion, HAIS for computer security (HAISFCS), data mining: data preparation and analysis, hybrid artificial intelligence systems in management of production systems, hybrid artificial intelligent systems for ordinal regression, hybrid metaheuristics for combinatorial optimization and modelling complex systems, hybrid computational intelligence and lattice computing for image and signal processing and nonstationary models of pattern recognition and classifier combinations.