Brain and Nature Inspired Learning Computation and Recognition

Brain and Nature Inspired Learning Computation and Recognition
Author: Licheng Jiao,Ronghua Shang,Weitong Zhang,Fang Liu
Publsiher: Elsevier
Total Pages: 788
Release: 2020-01-31
ISBN 10: 9780128197950
ISBN 13: 0128197951
Language: EN, FR, DE, ES & NL

Brain and Nature Inspired Learning Computation and Recognition Book Review:

Brain and Nature-Inspired Learning, Computation and Recognition presents a systematic analysis of neural networks, natural computing, machine learning and compression, algorithms and applications inspired by the brain and biological mechanisms found in nature. Sections cover new developments and main applications, algorithms and simulations. Developments in brain and nature-inspired learning have promoted interest in image processing, clustering problems, change detection, control theory and other disciplines. The book discusses the main problems and applications pertaining to bio-inspired computation and recognition, introducing algorithm implementation, model simulation, and practical application of parameter setting. Readers will find solutions to problems in computation and recognition, particularly neural networks, natural computing, machine learning and compressed sensing. This volume offers a comprehensive and well-structured introduction to brain and nature-inspired learning, computation, and recognition. Presents an invaluable systematic introduction to brain and nature-inspired learning, computation and recognition Describes the biological mechanisms, mathematical analyses and scientific principles behind brain and nature-inspired learning, calculation and recognition Systematically analyzes neural networks, natural computing, machine learning and compression, algorithms and applications inspired by the brain and biological mechanisms found in nature Discusses the theory and application of algorithms and neural networks, natural computing, machine learning and compression perception

Brain and Nature Inspired Learning Computation and Recognition

Brain and Nature Inspired Learning  Computation and Recognition
Author: Licheng Jiao,Ronghua Shang,Fang Liu,Weitong Zhang
Publsiher: Elsevier
Total Pages: 788
Release: 2020-01-18
ISBN 10: 0128204044
ISBN 13: 9780128204047
Language: EN, FR, DE, ES & NL

Brain and Nature Inspired Learning Computation and Recognition Book Review:

Brain and Nature-Inspired Learning, Computation and Recognition presents a systematic analysis of neural networks, natural computing, machine learning and compression, algorithms and applications inspired by the brain and biological mechanisms found in nature. Sections cover new developments and main applications, algorithms and simulations. Developments in brain and nature-inspired learning have promoted interest in image processing, clustering problems, change detection, control theory and other disciplines. The book discusses the main problems and applications pertaining to bio-inspired computation and recognition, introducing algorithm implementation, model simulation, and practical application of parameter setting. Readers will find solutions to problems in computation and recognition, particularly neural networks, natural computing, machine learning and compressed sensing. This volume offers a comprehensive and well-structured introduction to brain and nature-inspired learning, computation, and recognition. Presents an invaluable systematic introduction to brain and nature-inspired learning, computation and recognition Describes the biological mechanisms, mathematical analyses and scientific principles behind brain and nature-inspired learning, calculation and recognition Systematically analyzes neural networks, natural computing, machine learning and compression, algorithms and applications inspired by the brain and biological mechanisms found in nature Discusses the theory and application of algorithms and neural networks, natural computing, machine learning and compression perception

Nature Inspired Computing Concepts Methodologies Tools and Applications

Nature Inspired Computing  Concepts  Methodologies  Tools  and Applications
Author: Management Association, Information Resources
Publsiher: IGI Global
Total Pages: 1780
Release: 2016-07-26
ISBN 10: 1522507892
ISBN 13: 9781522507895
Language: EN, FR, DE, ES & NL

Nature Inspired Computing Concepts Methodologies Tools and Applications Book Review:

As technology continues to become more sophisticated, mimicking natural processes and phenomena also becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for man-made computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications takes an interdisciplinary approach to the topic of natural computing, including emerging technologies being developed for the purpose of simulating natural phenomena, applications across industries, and the future outlook of biologically and nature-inspired technologies. Emphasizing critical research in a comprehensive multi-volume set, this publication is designed for use by IT professionals, researchers, and graduate students studying intelligent computing.

Nature Inspired Computing Design Development and Applications

Nature Inspired Computing Design  Development  and Applications
Author: Nunes de Castro, Leandro
Publsiher: IGI Global
Total Pages: 435
Release: 2012-05-31
ISBN 10: 1466615753
ISBN 13: 9781466615755
Language: EN, FR, DE, ES & NL

Nature Inspired Computing Design Development and Applications Book Review:

The observation of nature has been the inspiration for many materials, laws, and theories, as well as computational methods. Nature-Inspired computing Design, Development, and Applications covers all the main areas of natural computing, from methods to computationally synthesized natural phenomena, to computing paradigms based on natural materials. This volume is comprised of ideas and research from nature to develop computational systems or materials to perform computation. Researchers, academic educators, and professionals will find a comprehensive view of all aspects of natural computing with emphasis on its main branches.

Metaheuristic Optimization Nature Inspired Algorithms Swarm and Computational Intelligence Theory and Applications

Metaheuristic Optimization  Nature Inspired Algorithms Swarm and Computational Intelligence  Theory and Applications
Author: Modestus O. Okwu,Lagouge K. Tartibu
Publsiher: Springer Nature
Total Pages: 192
Release: 2020-11-13
ISBN 10: 3030611116
ISBN 13: 9783030611118
Language: EN, FR, DE, ES & NL

Metaheuristic Optimization Nature Inspired Algorithms Swarm and Computational Intelligence Theory and Applications Book Review:

This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm, ant lion optimization algorithm, grasshopper optimization algorithm, butterfly optimization algorithm and others. The algorithms have been arranged in chapters to help readers gain better insight into nature-inspired systems and swarm intelligence. All the MATLAB codes have been provided in the appendices of the book to enable readers practice how to solve examples included in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences.

Nature Inspired Computing for Data Science

Nature Inspired Computing for Data Science
Author: Minakhi Rout,Jitendra Kumar Rout,Himansu Das
Publsiher: Springer Nature
Total Pages: 295
Release: 2019-11-26
ISBN 10: 3030338207
ISBN 13: 9783030338206
Language: EN, FR, DE, ES & NL

Nature Inspired Computing for Data Science Book Review:

This book discusses the current research and concepts in data science and how these can be addressed using different nature-inspired optimization techniques. Focusing on various data science problems, including classification, clustering, forecasting, and deep learning, it explores how researchers are using nature-inspired optimization techniques to find solutions to these problems in domains such as disease analysis and health care, object recognition, vehicular ad-hoc networking, high-dimensional data analysis, gene expression analysis, microgrids, and deep learning. As such it provides insights and inspiration for researchers to wanting to employ nature-inspired optimization techniques in their own endeavors.

Nature Inspired VLSI Circuits From Concept to Implementation

Nature Inspired VLSI Circuits   From Concept to Implementation
Author: Hongjiang Song
Publsiher: Lulu.com
Total Pages: 135
Release: 2021
ISBN 10: 1387847163
ISBN 13: 9781387847167
Language: EN, FR, DE, ES & NL

Nature Inspired VLSI Circuits From Concept to Implementation Book Review:

Nature Inspired Computation and Machine Learning

Nature Inspired Computation and Machine Learning
Author: Alexander Gelbukh,Félix Castro Espinoza,Sofía N. Galicia-Haro
Publsiher: Springer
Total Pages: 522
Release: 2014-11-05
ISBN 10: 331913650X
ISBN 13: 9783319136509
Language: EN, FR, DE, ES & NL

Nature Inspired Computation and Machine Learning Book Review:

The two-volume set LNAI 8856 and LNAI 8857 constitutes the proceedings of the 13th Mexican International Conference on Artificial Intelligence, MICAI 2014, held in Tuxtla, Mexico, in November 2014. The total of 87 papers plus 1 invited talk presented in these proceedings were carefully reviewed and selected from 348 submissions. The first volume deals with advances in human-inspired computing and its applications. It contains 44 papers structured into seven sections: natural language processing, natural language processing applications, opinion mining, sentiment analysis, and social network applications, computer vision, image processing, logic, reasoning, and multi-agent systems, and intelligent tutoring systems. The second volume deals with advances in nature-inspired computation and machine learning and contains also 44 papers structured into eight sections: genetic and evolutionary algorithms, neural networks, machine learning, machine learning applications to audio and text, data mining, fuzzy logic, robotics, planning, and scheduling, and biomedical applications.

Brain Inspired Computing

Brain Inspired Computing
Author: Lucio Grandinetti,Thomas Lippert,Nicolai Petkov
Publsiher: Springer
Total Pages: 213
Release: 2014-10-16
ISBN 10: 3319120840
ISBN 13: 9783319120843
Language: EN, FR, DE, ES & NL

Brain Inspired Computing Book Review:

This book constitutes the thoroughly refereed conference proceedings of the International Workshop on Brain-inspired Computing, BrainComp 2013, held in Cetraro, Italy, in July 2013. The 16 revised full papers were carefully reviewed and selected from numerous submissions and cover topics such as brain structure and function as a neuroscience perspective, computational models and brain-inspired computing, HPC and visualization for human brain simulations.

Nature Inspired Algorithms for Big Data Frameworks

Nature Inspired Algorithms for Big Data Frameworks
Author: Banati, Hema,Mehta, Shikha,Kaur, Parmeet
Publsiher: IGI Global
Total Pages: 412
Release: 2018-09-28
ISBN 10: 1522558535
ISBN 13: 9781522558538
Language: EN, FR, DE, ES & NL

Nature Inspired Algorithms for Big Data Frameworks Book Review:

As technology continues to become more sophisticated, mimicking natural processes and phenomena becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for manmade computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Algorithms for Big Data Frameworks is a collection of innovative research on the methods and applications of extracting meaningful information from data using algorithms that are capable of handling the constraints of processing time, memory usage, and the dynamic and unstructured nature of data. Highlighting a range of topics including genetic algorithms, data classification, and wireless sensor networks, this book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the application of nature and biologically inspired algorithms for handling challenges posed by big data in diverse environments.

Nature Inspired Computing for Control Systems

Nature Inspired Computing for Control Systems
Author: Hiram Eredín Ponce Espinosa
Publsiher: Springer
Total Pages: 289
Release: 2015-12-16
ISBN 10: 3319262300
ISBN 13: 9783319262307
Language: EN, FR, DE, ES & NL

Nature Inspired Computing for Control Systems Book Review:

The book presents recent advances in nature-inspired computing, giving a special emphasis to control systems applications. It reviews different techniques used for simulating physical, chemical, biological or social phenomena at the purpose of designing robust, predictive and adaptive control strategies. The book is a collection of several contributions, covering either more general approaches in control systems, or methodologies for control tuning and adaptive controllers, as well as exciting applications of nature-inspired techniques in robotics. On one side, the book is expected to motivate readers with a background in conventional control systems to try out these powerful techniques inspired by nature. On the other side, the book provides advanced readers with a deeper understanding of the field and a broad spectrum of different methods and techniques. All in all, the book is an outstanding, practice-oriented reference guide to nature-inspired computing addressing graduate students, researchers and practitioners in the field of control engineering.

Frontiers in Nature Inspired Industrial Optimization

Frontiers in Nature Inspired Industrial Optimization
Author: Mahdi Khosravy
Publsiher: Springer Nature
Total Pages: 135
Release: 2021
ISBN 10: 981163128X
ISBN 13: 9789811631283
Language: EN, FR, DE, ES & NL

Frontiers in Nature Inspired Industrial Optimization Book Review:

Handbook of Research on Soft Computing and Nature Inspired Algorithms

Handbook of Research on Soft Computing and Nature Inspired Algorithms
Author: Shandilya, Shishir K.,Shandilya, Smita,Deep, Kusum,Nagar, Atulya K.
Publsiher: IGI Global
Total Pages: 627
Release: 2017-03-10
ISBN 10: 1522521291
ISBN 13: 9781522521297
Language: EN, FR, DE, ES & NL

Handbook of Research on Soft Computing and Nature Inspired Algorithms Book Review:

Soft computing and nature-inspired computing both play a significant role in developing a better understanding to machine learning. When studied together, they can offer new perspectives on the learning process of machines. The Handbook of Research on Soft Computing and Nature-Inspired Algorithms is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem solving, this publication is ideally designed for students, researchers, scholars, professionals, and practitioners seeking current research on the advanced workings of intelligence in computing systems.

Advances in Multi Objective Nature Inspired Computing

Advances in Multi Objective Nature Inspired Computing
Author: Carlos Coello Coello,Clarisse Dhaenens,Laetitia Jourdan
Publsiher: Springer Science & Business Media
Total Pages: 195
Release: 2010-02-04
ISBN 10: 364211217X
ISBN 13: 9783642112171
Language: EN, FR, DE, ES & NL

Advances in Multi Objective Nature Inspired Computing Book Review:

The purpose of this book is to collect contributions that deal with the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems. Such a collection intends to provide an overview of the state-of-the-art developments in this field, with the aim of motivating more researchers in operations research, engineering, and computer science, to do research in this area. As such, this book is expected to become a valuable reference for those wishing to do research on the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems.

Neural Information Processing

Neural Information Processing
Author: Bao-Liang Lu,Liqing Zhang,James Kwok
Publsiher: Springer Science & Business Media
Total Pages: 778
Release: 2011-10-26
ISBN 10: 3642249574
ISBN 13: 9783642249570
Language: EN, FR, DE, ES & NL

Neural Information Processing Book Review:

The three volume set LNCS 7062, LNCS 7063, and LNCS 7064 constitutes the proceedings of the 18th International Conference on Neural Information Processing, ICONIP 2011, held in Shanghai, China, in November 2011. The 262 regular session papers presented were carefully reviewed and selected from numerous submissions. The papers of part I are organized in topical sections on perception, emotion and development, bioinformatics, biologically inspired vision and recognition, bio-medical data analysis, brain signal processing, brain-computer interfaces, brain-like systems, brain-realistic models for learning, memory and embodied cognition, Clifford algebraic neural networks, combining multiple learners, computational advances in bioinformatics, and computational-intelligent human computer interaction. The second volume is structured in topical sections on cybersecurity and data mining workshop, data mining and knowledge doscovery, evolutionary design and optimisation, graphical models, human-originated data analysis and implementation, information retrieval, integrating multiple nature-inspired approaches, Kernel methods and support vector machines, and learning and memory. The third volume contains all the contributions connected with multi-agent systems, natural language processing and intelligent Web information processing, neural encoding and decoding, neural network models, neuromorphic hardware and implementations, object recognition, visual perception modelling, and advances in computational intelligence methods based pattern recognition.

Artificial Intelligence in the Age of Neural Networks and Brain Computing

Artificial Intelligence in the Age of Neural Networks and Brain Computing
Author: Robert Kozma,Cesare Alippi,Yoonsuck Choe,Francesco Carlo Morabito
Publsiher: Academic Press
Total Pages: 352
Release: 2018-10-30
ISBN 10: 0128162503
ISBN 13: 9780128162507
Language: EN, FR, DE, ES & NL

Artificial Intelligence in the Age of Neural Networks and Brain Computing Book Review:

Artificial Intelligence in the Age of Neural Networks and Brain Computing demonstrates that existing disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity and smart autonomous search engines. The book covers the major basic ideas of brain-like computing behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as future alternatives. The success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel and Amazon can be interpreted using this book. Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN) Authored by top experts, global field pioneers and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making Edited by high-level academics and researchers in intelligent systems and neural networks

Brain inspired Computing

Brain inspired Computing
Author: Katrin Amunts,Lucio Grandinetti,Thomas Lippert,Nicolai Petkov
Publsiher: Springer Nature
Total Pages: 159
Release: 2021
ISBN 10: 3030824276
ISBN 13: 9783030824273
Language: EN, FR, DE, ES & NL

Brain inspired Computing Book Review:

This open access book constitutes revised selected papers from the 4th International Workshop on Brain-Inspired Computing, BrainComp 2019, held in Cetraro, Italy, in July 2019. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They deal with research on brain atlasing, multi-scale models and simulation, HPC and data infra-structures for neuroscience as well as artificial and natural neural architectures.

Computational Intelligence in Data Mining

Computational Intelligence in Data Mining
Author: Himansu Sekhar Behera,Janmenjoy Nayak,Bighnaraj Naik,Danilo Pelusi
Publsiher: Springer
Total Pages: 801
Release: 2019-08-17
ISBN 10: 9811386765
ISBN 13: 9789811386763
Language: EN, FR, DE, ES & NL

Computational Intelligence in Data Mining Book Review:

This proceeding discuss the latest solutions, scientific findings and methods for solving intriguing problems in the fields of data mining, computational intelligence, big data analytics, and soft computing. This gathers outstanding papers from the fifth International Conference on “Computational Intelligence in Data Mining” (ICCIDM), and offer a “sneak preview” of the strengths and weaknesses of trending applications, together with exciting advances in computational intelligence, data mining, and related fields.

Handbook of Nature Inspired and Innovative Computing

Handbook of Nature Inspired and Innovative Computing
Author: Albert Y. Zomaya
Publsiher: Springer Science & Business Media
Total Pages: 736
Release: 2006-01-10
ISBN 10: 9780387405322
ISBN 13: 0387405321
Language: EN, FR, DE, ES & NL

Handbook of Nature Inspired and Innovative Computing Book Review:

As computing devices proliferate, demand increases for an understanding of emerging computing paradigms and models based on natural phenomena. Neural networks, evolution-based models, quantum computing, and DNA-based computing and simulations are all a necessary part of modern computing analysis and systems development. Vast literature exists on these new paradigms and their implications for a wide array of applications. This comprehensive handbook, the first of its kind to address the connection between nature-inspired and traditional computational paradigms, is a repository of case studies dealing with different problems in computing and solutions to these problems based on nature-inspired paradigms. The "Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies" is an essential compilation of models, methods, and algorithms for researchers, professionals, and advanced-level students working in all areas of computer science, IT, biocomputing, and network engineering.

Data Science Thinking

Data Science Thinking
Author: Longbing Cao
Publsiher: Springer
Total Pages: 390
Release: 2018-08-17
ISBN 10: 3319950924
ISBN 13: 9783319950921
Language: EN, FR, DE, ES & NL

Data Science Thinking Book Review:

This book explores answers to the fundamental questions driving the research, innovation and practices of the latest revolution in scientific, technological and economic development: how does data science transform existing science, technology, industry, economy, profession and education? How does one remain competitive in the data science field? What is responsible for shaping the mindset and skillset of data scientists? Data Science Thinking paints a comprehensive picture of data science as a new scientific paradigm from the scientific evolution perspective, as data science thinking from the scientific-thinking perspective, as a trans-disciplinary science from the disciplinary perspective, and as a new profession and economy from the business perspective. The topics cover an extremely wide spectrum of essential and relevant aspects of data science, spanning its evolution, concepts, thinking, challenges, discipline, and foundation, all the way to industrialization, profession, education, and the vast array of opportunities that data science offers. The book's three parts each detail layers of these different aspects. The book is intended for decision-makers, data managers (e.g., analytics portfolio managers, business analytics managers, chief data analytics officers, chief data scientists, and chief data officers), policy makers, management and decision strategists, research leaders, and educators who are responsible for pursuing new scientific, innovation, and industrial transformation agendas, enterprise strategic planning, a next-generation profession-oriented course development, as well as those who are involved in data science, technology, and economy from an advanced perspective. Research students in data science-related courses and disciplines will find the book useful for positing their innovative scientific journey, planning their unique and promising career, and competing within and being ready for the next generation of science, technology, and economy.