Download or read book Computational Intelligence for Network Structure Analytics written by Maoguo Gong and published by Springer. This book was released on 2017-09-19 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest research advances in complex network structure analytics based on computational intelligence (CI) approaches, particularly evolutionary optimization. Most if not all network issues are actually optimization problems, which are mostly NP-hard and challenge conventional optimization techniques. To effectively and efficiently solve these hard optimization problems, CI based network structure analytics offer significant advantages over conventional network analytics techniques. Meanwhile, using CI techniques may facilitate smart decision making by providing multiple options to choose from, while conventional methods can only offer a decision maker a single suggestion. In addition, CI based network structure analytics can greatly facilitate network modeling and analysis. And employing CI techniques to resolve network issues is likely to inspire other fields of study such as recommender systems, system biology, etc., which will in turn expand CI’s scope and applications. As a comprehensive text, the book covers a range of key topics, including network community discovery, evolutionary optimization, network structure balance analytics, network robustness analytics, community-based personalized recommendation, influence maximization, and biological network alignment. Offering a rich blend of theory and practice, the book is suitable for students, researchers and practitioners interested in network analytics and computational intelligence, both as a textbook and as a reference work.

Download or read book Big Data and Computational Intelligence in Networking written by Yulei Wu and published by CRC Press. This book was released on 2017-12-14 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents state-of-the-art solutions to the theoretical and practical challenges stemming from the leverage of big data and its computational intelligence in supporting smart network operation, management, and optimization. In particular, the technical focus covers the comprehensive understanding of network big data, efficient collection and management of network big data, distributed and scalable online analytics for network big data, and emerging applications of network big data for computational intelligence.

Download or read book Fundamentals of Computational Intelligence written by James M. Keller and published by John Wiley & Sons. This book was released on 2016-07-13 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise computational intelligence are written by specialists in one discipline, this book is co-written by current former Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, a former Editor-in-Chief of IEEE Transactions on Fuzzy Systems, and the founding Editor-in-Chief of IEEE Transactions on Evolutionary Computation. The coverage across the three topics is both uniform and consistent in style and notation. Discusses single-layer and multilayer neural networks, radial-basis function networks, and recurrent neural networks Covers fuzzy set theory, fuzzy relations, fuzzy logic interference, fuzzy clustering and classification, fuzzy measures and fuzzy integrals Examines evolutionary optimization, evolutionary learning and problem solving, and collective intelligence Includes end-of-chapter practice problems that will help readers apply methods and techniques to real-world problems Fundamentals of Computational intelligence is written for advanced undergraduates, graduate students, and practitioners in electrical and computer engineering, computer science, and other engineering disciplines.

Download or read book Social Networks A Framework of Computational Intelligence written by Witold Pedrycz and published by Springer. This book was released on 2013-12-09 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides the audience with an updated, in-depth and highly coherent material on the conceptually appealing and practically sound information technology of Computational Intelligence applied to the analysis, synthesis and evaluation of social networks. The volume involves studies devoted to key issues of social networks including community structure detection in networks, online social networks, knowledge growth and evaluation, and diversity of collaboration mechanisms. The book engages a wealth of methods of Computational Intelligence along with well-known techniques of linear programming, Formal Concept Analysis, machine learning, and agent modeling. Human-centricity is of paramount relevance and this facet manifests in many ways including personalized semantics, trust metric, and personal knowledge management; just to highlight a few of these aspects. The contributors to this volume report on various essential applications including cyber attacks detection, building enterprise social networks, business intelligence and forming collaboration schemes. Given the subject area, this book is aimed at a broad audience of researchers and practitioners. Owing to the nature of the material being covered and a way it is organized, the volume will appeal to the well-established communities including those active in various disciplines in which social networks, their analysis and optimization are of genuine relevance. Those involved in operations research, management, various branches of engineering, and economics will benefit from the exposure to the subject matter.

Download or read book Computational Intelligence in Communications and Business Analytics written by Paramartha Dutta and published by Springer Nature. This book was released on 2021-05-25 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Conference on Computational Intelligence, Communications, and Business Analytics, CICBA 2021, held in Santiniketan, India, in January 2021. The 12 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 84 submissions. The papers are organized in topical sections on computational forensic (privacy and security); computational intelligence; data science and advanced data analytics; and intelligent data mining and data warehousing.

Download or read book Computational Intelligence for Big Data Analysis written by D.P. Acharjya and published by Springer. This book was released on 2015-04-21 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The theoretical advancements are supported with illustrative examples and its applications in handling real life problems. The applications are mostly undertaken from real life situations. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing. An elaborate bibliography is provided at the end of each chapter. The material in this book includes concepts, figures, graphs, and tables to guide researchers in the area of big data analysis and cloud computing.

Download or read book Big Data and Computational Intelligence in Networking written by Yulei Wu and published by . This book was released on 2018 with total page 529 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents state-of-the-art solutions to the theoretical and practical challenges stemming from the leverage of big data and its computational intelligence in supporting smart network operation, management, and optimization. In particular, the technical focus covers the comprehensive understanding of network big data, efficient collection and management of network big data, distributed and scalable online analytics for network big data, and emerging applications of network big data for computational intelligence.

Download or read book Big Data Analytics and Computational Intelligence for Cybersecurity written by Mariya Ouaissa and published by Springer Nature. This book was released on 2022-09-01 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of state-of-the-art artificial intelligence and big data analytics approaches to cybersecurity intelligence. It illustrates the latest trends in AI/ML-based strategic defense mechanisms against malware, vulnerabilities, cyber threats, as well as proactive countermeasures. It also introduces other trending technologies, such as blockchain, SDN, and IoT, and discusses their possible impact on improving security. The book discusses the convergence of AI/ML and big data in cybersecurity by providing an overview of theoretical, practical, and simulation concepts of computational intelligence and big data analytics used in different approaches of security. It also displays solutions that will help analyze complex patterns in user data and ultimately improve productivity. This book can be a source for researchers, students, and practitioners interested in the fields of artificial intelligence, cybersecurity, data analytics, and recent trends of networks.

Download or read book Data Mining with Computational Intelligence written by Lipo Wang and published by Springer Science & Business Media. This book was released on 2005-12-08 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, banking, retail, and many others. Wang and Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications. They focus on three main data mining tasks: data dimensionality reduction, classification, and rule extraction. The book is targeted at researchers in both academia and industry, while graduate students and developers of data mining systems will also profit from the detailed algorithmic descriptions.

Download or read book Computational Intelligence Applications in Business Intelligence and Big Data Analytics written by Vijayan Sugumaran and published by CRC Press. This book was released on 2017-06-26 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are a number of books on computational intelligence (CI), but they tend to cover a broad range of CI paradigms and algorithms rather than provide an in-depth exploration in learning and adaptive mechanisms. This book sets its focus on CI based architectures, modeling, case studies and applications in big data analytics, and business intelligence. The intended audiences of this book are scientists, professionals, researchers, and academicians who deal with the new challenges and advances in the specific areas mentioned above. Designers and developers of applications in these areas can learn from other experts and colleagues through this book.

Download or read book Computational Intelligence for Business Analytics written by Witold Pedrycz and published by Springer Nature. This book was released on 2021-10-26 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Corporate success has been changed by the importance of new developments in Business Analytics (BA) and furthermore by the support of computational intelligence- based techniques. This book opens a new avenues in these subjects, identifies key developments and opportunities. The book will be of interest for students, researchers and professionals to identify innovative ways delivered by Business Analytics based on computational intelligence solutions. They help elicit information, handle knowledge and support decision-making for more informed and reliable decisions even under high uncertainty environments.Computational Intelligence for Business Analytics has collected the latest technological innovations in the field of BA to improve business models related to Group Decision-Making, Forecasting, Risk Management, Knowledge Discovery, Data Breach Detection, Social Well-Being, among other key topics related to this field.

Download or read book Mining and Control of Network Traffic by Computational Intelligence written by Federico Montesino Pouzols and published by Springer Science & Business Media. This book was released on 2011-02-10 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: As other complex systems in social and natural sciences as well as in engineering, the Internet is hard to understand from a technical point of view. Packet switched networks defy analytical modeling. The Internet is an outstanding and challenging case because of its fast development, unparalleled heterogeneity and the inherent lack of measurement and monitoring mechanisms in its core conception. This monograph deals with applications of computational intelligence methods, with an emphasis on fuzzy techniques, to a number of current issues in measurement, analysis and control of traffic in the Internet. First, the core building blocks of Internet Science and other related networking aspects are introduced. Then, data mining and control problems are addressed. In the first class two issues are considered: predictive modeling of traffic load as well as summarization of traffic flow measurements. The second class, control, includes active queue management schemes for Internet routers as well as window based end-to-end rate and congestion control. The practical hardware implementation of some of the fuzzy inference systems proposed here is also addressed. While some theoretical developments are described, we favor extensive evaluation of models using real-world data by simulation and experiments.

Download or read book Hybrid Computational Intelligence written by Siddhartha Bhattacharyya and published by Academic Press. This book was released on 2020-03-05 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Big Data Analytics written by Mrutyunjaya Panda and published by CRC Press. This book was released on 2018-12-12 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social networking has increased drastically in recent years, resulting in an increased amount of data being created daily. Furthermore, diversity of issues and complexity of the social networks pose a challenge in social network mining. Traditional algorithm software cannot deal with such complex and vast amounts of data, necessitating the development of novel analytic approaches and tools. This reference work deals with social network aspects of big data analytics. It covers theory, practices and challenges in social networking. The book spans numerous disciplines like neural networking, deep learning, artificial intelligence, visualization, e-learning in higher education, e-healthcare, security and intrusion detection.

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.

Download or read book Business and Consumer Analytics New Ideas written by Pablo Moscato and published by Springer. This book was released on 2019-05-30 with total page 1005 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume handbook presents a collection of novel methodologies with applications and illustrative examples in the areas of data-driven computational social sciences. Throughout this handbook, the focus is kept specifically on business and consumer-oriented applications with interesting sections ranging from clustering and network analysis, meta-analytics, memetic algorithms, machine learning, recommender systems methodologies, parallel pattern mining and data mining to specific applications in market segmentation, travel, fashion or entertainment analytics. A must-read for anyone in data-analytics, marketing, behavior modelling and computational social science, interested in the latest applications of new computer science methodologies. The chapters are contributed by leading experts in the associated fields.The chapters cover technical aspects at different levels, some of which are introductory and could be used for teaching. Some chapters aim at building a common understanding of the methodologies and recent application areas including the introduction of new theoretical results in the complexity of core problems. Business and marketing professionals may use the book to familiarize themselves with some important foundations of data science. The work is a good starting point to establish an open dialogue of communication between professionals and researchers from different fields. Together, the two volumes present a number of different new directions in Business and Customer Analytics with an emphasis in personalization of services, the development of new mathematical models and new algorithms, heuristics and metaheuristics applied to the challenging problems in the field. Sections of the book have introductory material to more specific and advanced themes in some of the chapters, allowing the volumes to be used as an advanced textbook. Clustering, Proximity Graphs, Pattern Mining, Frequent Itemset Mining, Feature Engineering, Network and Community Detection, Network-based Recommending Systems and Visualization, are some of the topics in the first volume. Techniques on Memetic Algorithms and their applications to Business Analytics and Data Science are surveyed in the second volume; applications in Team Orienteering, Competitive Facility-location, and Visualization of Products and Consumers are also discussed. The second volume also includes an introduction to Meta-Analytics, and to the application areas of Fashion and Travel Analytics. Overall, the two-volume set helps to describe some fundamentals, acts as a bridge between different disciplines, and presents important results in a rapidly moving field combining powerful optimization techniques allied to new mathematical models critical for personalization of services. Academics and professionals working in the area of business anyalytics, data science, operations research and marketing will find this handbook valuable as a reference. Students studying these fields will find this handbook useful and helpful as a secondary textbook.

Download or read book Data Science New Issues Challenges and Applications written by Gintautas Dzemyda and published by Springer Nature. This book was released on 2020-02-13 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains 16 chapters by researchers working in various fields of data science. They focus on theory and applications in language technologies, optimization, computational thinking, intelligent decision support systems, decomposition of signals, model-driven development methodologies, interoperability of enterprise applications, anomaly detection in financial markets, 3D virtual reality, monitoring of environmental data, convolutional neural networks, knowledge storage, data stream classification, and security in social networking. The respective papers highlight a wealth of issues in, and applications of, data science. Modern technologies allow us to store and transfer large amounts of data quickly. They can be very diverse - images, numbers, streaming, related to human behavior and physiological parameters, etc. Whether the data is just raw numbers, crude images, or will help solve current problems and predict future developments, depends on whether we can effectively process and analyze it. Data science is evolving rapidly. However, it is still a very young field. In particular, data science is concerned with visualizations, statistics, pattern recognition, neurocomputing, image analysis, machine learning, artificial intelligence, databases and data processing, data mining, big data analytics, and knowledge discovery in databases. It also has many interfaces with optimization, block chaining, cyber-social and cyber-physical systems, Internet of Things (IoT), social computing, high-performance computing, in-memory key-value stores, cloud computing, social computing, data feeds, overlay networks, cognitive computing, crowdsource analysis, log analysis, container-based virtualization, and lifetime value modeling. Again, all of these areas are highly interrelated. In addition, data science is now expanding to new fields of application: chemical engineering, biotechnology, building energy management, materials microscopy, geographic research, learning analytics, radiology, metal design, ecosystem homeostasis investigation, and many others.