Biologically-Inspired Techniques for Knowledge Discovery and Data Mining

Biologically-Inspired Techniques for Knowledge Discovery and Data Mining

Author: Alam, Shafiq

Publisher: IGI Global

Published: 2014-05-31

Total Pages: 397

ISBN-13: 1466660791

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Biologically-inspired data mining has a wide variety of applications in areas such as data clustering, classification, sequential pattern mining, and information extraction in healthcare and bioinformatics. Over the past decade, research materials in this area have dramatically increased, providing clear evidence of the popularity of these techniques. Biologically-Inspired Techniques for Knowledge Discovery and Data Mining exemplifies prestigious research and shares the practices that have allowed these areas to grow and flourish. This essential reference publication highlights contemporary findings in the area of biologically-inspired techniques in data mining domains and their implementation in real-life problems. Providing quality work from established researchers, this publication serves to extend existing knowledge within the research communities of data mining and knowledge discovery, as well as for academicians and students in the field.


Biological Data Mining

Biological Data Mining

Author: Jake Y. Chen

Publisher: CRC Press

Published: 2009-09-01

Total Pages: 736

ISBN-13: 1420086855

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Like a data-guzzling turbo engine, advanced data mining has been powering post-genome biological studies for two decades. Reflecting this growth, Biological Data Mining presents comprehensive data mining concepts, theories, and applications in current biological and medical research. Each chapter is written by a distinguished team of interdisciplin


Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining

Author: Usama M. Fayyad

Publisher:

Published: 1996

Total Pages: 638

ISBN-13:

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Eight sections of this book span fundamental issues of knowledge discovery, classification and clustering, trend and deviation analysis, dependency derivation, integrated discovery systems, augumented database systems and application case studies. The appendices provide a list of terms used in the literature of the field of data mining and knowledge discovery in databases, and a list of online resources for the KDD researcher.


Incorporating Nature-Inspired Paradigms in Computational Applications

Incorporating Nature-Inspired Paradigms in Computational Applications

Author: Khosrow-Pour, Mehdi

Publisher: IGI Global

Published: 2018-04-06

Total Pages: 398

ISBN-13: 1522550216

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Many techniques have been developed to control the variety of dynamic systems. To develop those control techniques, it is fundamental to know the mathematical relations between the system inputs and outputs. Incorporating Nature-Inspired Paradigms in Computational Applications is a critical scholarly resource that examines the application of nature-inspired paradigms on system identification. Featuring coverage on a broad range of topics such as biogeographic computation, evolutionary control systems, and natural computing, this book is geared towards IT professionals, engineers, computer scientists, academicians, researchers, and graduate-level students seeking current research on the application of nature-inspired paradigms.


Trends and Applications in Knowledge Discovery and Data Mining

Trends and Applications in Knowledge Discovery and Data Mining

Author: Jiuyong Li

Publisher: Springer

Published: 2013-08-23

Total Pages: 571

ISBN-13: 3642403190

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This book constitutes the refereed proceedings at PAKDD Workshops 2013, affiliated with the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) held in Gold Coast, Australia in April 2013. The 47 revised full papers presented were carefully reviewed and selected from 92 submissions. The workshops affiliated with PAKDD 2013 include: Data Mining Applications in Industry and Government (DMApps), Data Analytics for Targeted Healthcare (DANTH), Quality Issues, Measures of Interestingness and Evaluation of Data Mining Models (QIMIE), Biologically Inspired Techniques for Data Mining (BDM), Constraint Discovery and Application (CDA), Cloud Service Discovery (CloudSD).


Biologically Inspired Techniques in Many-Criteria Decision Making

Biologically Inspired Techniques in Many-Criteria Decision Making

Author: Satchidananda Dehuri

Publisher: Springer Nature

Published: 2020-01-21

Total Pages: 268

ISBN-13: 3030390330

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This book addresses many-criteria decision-making (MCDM), a process used to find a solution in an environment with several criteria. In many real-world problems, there are several different objectives that need to be taken into account. Solving these problems is a challenging task and requires careful consideration. In real applications, often simple and easy to understand methods are used; as a result, the solutions accepted by decision makers are not always optimal solutions. On the other hand, algorithms that would provide better outcomes are very time consuming. The greatest challenge facing researchers is how to create effective algorithms that will yield optimal solutions with low time complexity. Accordingly, many current research efforts are focused on the implementation of biologically inspired algorithms (BIAs), which are well suited to solving uni-objective problems. This book introduces readers to state-of-the-art developments in biologically inspired techniques and their applications, with a major emphasis on the MCDM process. To do so, it presents a wide range of contributions on e.g. BIAs, MCDM, nature-inspired algorithms, multi-criteria optimization, machine learning and soft computing.


Swarm Intelligence and Bio-Inspired Computation

Swarm Intelligence and Bio-Inspired Computation

Author: Xin-She Yang

Publisher: Newnes

Published: 2013-05-16

Total Pages: 445

ISBN-13: 0124051774

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Swarm Intelligence and bio-inspired computation have become increasing popular in the last two decades. Bio-inspired algorithms such as ant colony algorithms, bat algorithms, bee algorithms, firefly algorithms, cuckoo search and particle swarm optimization have been applied in almost every area of science and engineering with a dramatic increase of number of relevant publications. This book reviews the latest developments in swarm intelligence and bio-inspired computation from both the theory and application side, providing a complete resource that analyzes and discusses the latest and future trends in research directions. It can help new researchers to carry out timely research and inspire readers to develop new algorithms. With its impressive breadth and depth, this book will be useful for advanced undergraduate students, PhD students and lecturers in computer science, engineering and science as well as researchers and engineers. - Focuses on the introduction and analysis of key algorithms - Includes case studies for real-world applications - Contains a balance of theory and applications, so readers who are interested in either algorithm or applications will all benefit from this timely book.


Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications

Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications

Author: Management Association, Information Resources

Publisher: IGI Global

Published: 2016-07-26

Total Pages: 1810

ISBN-13: 1522507892

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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.


Trends and Applications in Knowledge Discovery and Data Mining

Trends and Applications in Knowledge Discovery and Data Mining

Author: Wen-Chih Peng

Publisher: Springer

Published: 2014-11-26

Total Pages: 835

ISBN-13: 3319131869

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This book constitutes the refereed proceedings at PAKDD Workshops 2014, held in conjunction with the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) held in Tainan, Taiwan, in May 2014. The 73 revised papers presented were carefully reviewed and selected from 179 submissions. The workshops affiliated with PAKDD 2014 include: Data Analytics for Targeted Healthcare, DANTH; Data Mining and Decision Analytics for Public Health and Wellness, DMDA-Health; Biologically Inspired Data Mining Techniques, BDM; Mobile Data Management, Mining, and Computing on Social Networks, MobiSocial; Big Data Science and Engineering on E-Commerce, BigEC; Cloud Service Discovery, CloudSD; Mobile Sensing, Mining and Visualization for Human Behavior Inferences, MSMV-HBI; Scalable Dats Analytics: Theory and Algorithms, SDA; Algorithms for Large-Scale Information Processing in Knowledge Discovery, ALSIP; Data Mining in Social Networks, SocNet; Data Mining in Biomedical Informatics and Healthcare, DMBIH; and Pattern Mining and Application of Big Data, BigPMA.