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Author: Banati, Hema
Publisher: IGI Global
ISBN: 1522558535
Category : Computers
Languages : en
Pages : 435
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Book Description
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.
Author: Banati, Hema
Publisher: IGI Global
ISBN: 1522558535
Category : Computers
Languages : en
Pages : 435
Get Book Here
Book Description
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.
Author: Zhizhin, Gennadiy Vladimirovich
Publisher: IGI Global
ISBN: 1522596534
Category : Science
Languages : en
Pages : 245
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Book Description
In studying biology, one of the more difficult factors to predict is how parents attributes will affect their children and how those children will affect their own children. Organizing and calculating those vast statistics can become extremely tedious without the proper mathematical and reproductive knowledge. Attractors and Higher Dimensions in Population and Molecular Biology: Emerging Research and Opportunities is a collection of innovative research on the methods and applications of population logistics. While highlighting topics including gene analysis, crossbreeding, and reproduction, this book is ideally designed for academics, researchers, biologists, and mathematicians seeking current research on modeling the reproduction process of a biological population.
Author: Minakhi Rout
Publisher: Springer Nature
ISBN: 3030338207
Category : Computers
Languages : en
Pages : 303
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Book Description
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.
Author: Simon James Fong
Publisher: Springer Nature
ISBN: 981156695X
Category : Technology & Engineering
Languages : en
Pages : 228
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Book Description
This book aims to provide some insights into recently developed bio-inspired algorithms within recent emerging trends of fog computing, sentiment analysis, and data streaming as well as to provide a more comprehensive approach to the big data management from pre-processing to analytics to visualization phases. The subject area of this book is within the realm of computer science, notably algorithms (meta-heuristic and, more particularly, bio-inspired algorithms). Although application domains of these new algorithms may be mentioned, the scope of this book is not on the application of algorithms to specific or general domains but to provide an update on recent research trends for bio-inspired algorithms within a specific application domain or emerging area. These areas include data streaming, fog computing, and phases of big data management. One of the reasons for writing this book is that the bio-inspired approach does not receive much attention but shows considerable promise and diversity in terms of approach of many issues in big data and streaming. Some novel approaches of this book are the use of these algorithms to all phases of data management (not just a particular phase such as data mining or business intelligence as many books focus on); effective demonstration of the effectiveness of a selected algorithm within a chapter against comparative algorithms using the experimental method. Another novel approach is a brief overview and evaluation of traditional algorithms, both sequential and parallel, for use in data mining, in order to provide an overview of existing algorithms in use. This overview complements a further chapter on bio-inspired algorithms for data mining to enable readers to make a more suitable choice of algorithm for data mining within a particular context. In all chapters, references for further reading are provided, and in selected chapters, the author also include ideas for future research.
Author: Irfan Ali
Publisher: CRC Press
ISBN: 1040164625
Category : Computers
Languages : en
Pages : 335
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Book Description
This book comprehensively discusses nature‐inspired algorithms, deep learning methods, applications of mathematical programming, and artificial intelligence techniques. It further covers important topics such as the use of machine learning and the Internet of Things and multi‐objective optimization under Fermatean hesitant fuzzy and uncertain environment. This book: Addresses solving practical problems such as supply chain management, smart manufacturing, and healthcare analytics using intelligent computing and discusses solving the fuzzy inference system in ant colony optimization for traveling salesman problem Presents an overview of artificial intelligence (AI) and explainable AI decision‐making (XAIDM) and illustrates a data‐driven optimization concept for modeling environmental and economic sustainability Discusses machine learning‐based multi‐objective optimization technique for load balancing in integrated fog‐cloud environment Explains the use of heuristics and metaheuristics in supply chain networks and the use of fuzzy optimization in sustainable development goals Discusses sustainable transit of hazardous waste, green fractional transportation system, perishable inventory, M‐estimation of functional regression operator, and intuitionistic fuzzy sets applications The text is primarily written for graduate students and academic researchers in diverse fields, including operations research, mathematics, statistics, computer science, information and communication technology, and industrial engineering.
Author: Ajith Abraham
Publisher: Springer Nature
ISBN: 3030493393
Category : Technology & Engineering
Languages : en
Pages : 398
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Book Description
This book highlights recent research on bio-inspired computing and its various innovative applications in information and communication technologies. It presents 38 high-quality papers from the 10th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2019) and 9th World Congress on Information and Communication Technologies (WICT 2019), which was held at GIET University, Gunupur, India, on December 16–18, 2019. As a premier conference, IBICA–WICT brings together researchers, engineers and practitioners whose work involves bio-inspired computing, computational intelligence and their applications in information security, real-world contexts, etc. Including contributions by authors from 18 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1668463083
Category : Computers
Languages : en
Pages : 1378
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Book Description
Much of the world has access to internet and social media. The internet has quickly become a new hub for not only communication, but also community development. In most communities, people develop new cultural norms and identity development through social media usage. However, while these new lines of communication are helpful to many, challenges such as social media addiction, cyberbullying, and misinformation lurk on the internet and threaten forces both within and beyond the internet. The Research Anthology on Usage, Identity, and Impact of Social Media on Society and Culture is a comprehensive resource on the impact social media has on an individuals’ identity formation as well as its usage within society and cultures. It explores new research methodologies and findings into the behavior of users on social media as well as the effects of social media on society and culture as a whole. Covering topics such as cultural diversity, online deception, and youth impact, this major reference work is an essential resource for computer scientists, online community moderators, sociologists, business leaders and managers, marketers, advertising agencies, government officials, libraries, students and faculty of higher education, researchers, and academicians.
Author: Chakchai So In
Publisher: Springer Nature
ISBN: 9819986125
Category :
Languages : en
Pages : 609
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Book Description
Author: Xin-She Yang
Publisher: Elsevier
ISBN: 0124167454
Category : Computers
Languages : en
Pages : 277
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Book Description
Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, as well as multi-objective optimization. This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences. It can also serve a source of inspiration for new applications. Researchers and engineers as well as experienced experts will also find it a handy reference. - Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature - Provides a theoretical understanding as well as practical implementation hints - Provides a step-by-step introduction to each algorithm
Author: Gupta, P.K.
Publisher: IGI Global
ISBN: 1522562117
Category : Computers
Languages : en
Pages : 316
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Book Description
With the recent growth of big data and the internet of things (IoT), individuals can now upload, retrieve, store, and collect massive amounts of information to help drive decisions and optimize processes. Due to this, a new age of predictive computing is taking place, and data can now be harnessed to predict unknown occurrences or probabilities based on data collected in real time. Predictive Intelligence Using Big Data and the Internet of Things highlights state-of-the-art research on predictive intelligence using big data, the IoT, and related areas to ensure quality assurance and compatible IoT systems. Featuring coverage on predictive application scenarios to discuss these breakthroughs in real-world settings and various methods, frameworks, algorithms, and security concerns for predictive intelligence, this book is ideally designed for academicians, researchers, advanced-level students, and technology developers.
