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Swarm Intelligence in Data Mining (Studies in Computational Intelligence)

  • 267 Pages
  • 4.68 MB
  • 2692 Downloads
  • English

Springer
Applications of Computing, Engineering - General, Artificial Intelligence - General, Computers, Mathematics, Computer Books: General, Applied, Data Mining, Mathematics / Applied, Swarm Intelli
ContributionsAjith Abraham (Editor), Crina Grosan (Editor), Vitorino Ramos (Editor)
The Physical Object
FormatHardcover
ID Numbers
Open LibraryOL9056603M
ISBN 103540349553
ISBN 139783540349556

Data Mining is an analytic process designed to explore large amounts of data in search of consistent patterns and/or systematic relationships between variables, and then to validate the findings by applying the detected patterns to new subsets of data.

This book deals with the application of swarm intelligence in data mining.

Download Swarm Intelligence in Data Mining (Studies in Computational Intelligence) EPUB

Data Mining is an analytic process designed to explore large amounts of data in search of consistent patterns and/or systematic relationships between variables, and then to validate the findings by applying the detected patterns to new subsets of data.

This book deals with the application of swarm intelligence in data mining.4/5(1). Cheng S, Shi Y, Qin Q and Bai R Swarm Intelligence in Big Data Analytics Proceedings of the 14th International Conference on Intelligent Data Engineering and Automated Learning IDEAL - Volume().

The purpose of this book is to collect contributions that are at the intersection of multi-objective optimization, swarm intelligence (specifically, particle swarm optimization and ant colony optimization) and data mining. Such a collection intends to illustrate the potential of multi-objective.

Grosan et al.: Swarm Intelligence in Data Mining, Studies in Computational Intelligence (SCI) 34, 1–20 () c Springer-V erlag Berlin Heidelberg Swarm intelligence in data mining / Crina Grosan, This book deals with the application of swarm intelligence in data mining.

Addressing the various issues of swarm intelligence and data mining using different intelligent approaches is the novelty of this edited volume. This volume comprises of 11 chapters including an introductory chapter. Sousa T, Neves A, Silva A () Swarm Optimisation as a New Tool for Data Mining, International Parallel and Distributed Processing Symposium (IPDPS’03), b Google Scholar Sousa T, Silva A, Neves A () Particle Swarm based Data Mining Algorithms for classification tasks, Parallel Computing, Vol IssuesCrossRef.

Description Swarm Intelligence in Data Mining (Studies in Computational Intelligence) PDF

In book: Advances in Swarm Intelligence (pp) algorithms and data mining techniques, we understand better the insights of data analytics, and design more efficient algorithms to. The purpose of this book is to collect contributions that are at the intersection of multi-objective optimization, swarm intelligence (specifically, particle swarm optimization and ant colony optimization) and data mining.

This paper explores various applications that employ Swarm Intelligence with data mining in healthcare in terms of methods and results obtained. Swarm Intelligence algorithms have been used for prognosis of major diseases like cancer, heart diseases, tumors, and cardiology.

Swarm Intelligence for Resource Management in the Internet of Things presents a new approach in Artificial Intelligence that can be used for resources management in IoT, which is considered a critical issue for this network. The authors demonstrate these resource management applications using swarm intelligence techniques.

Swarm Intelligence for Multi-Objective Problems in Data Mining by Carlos Coello Coello (Editor) starting at $ Swarm Intelligence for Multi-Objective Problems in Data Mining has 2 available editions to buy at Half Price Books Marketplace.

Swarm Intelligence in Cloud Computing is an invaluable treatise for researchers involved in delivering intelligent optimized solutions for reliable deployment, infrastructural stability, and security issues of cloud-based resources. Starting with a bird’s eye view on the prevalent state-of-the-art techniques, this book enriches the readers with the knowledge of evolving swarm intelligent.

Details Swarm Intelligence in Data Mining (Studies in Computational Intelligence) FB2

Book Description. Swarm Intelligence: Principles, Advances, and Applications delivers in-depth coverage of bat, artificial fish swarm, firefly, cuckoo search, flower pollination, artificial bee colony, wolf search, and gray wolf optimization algorithms.

The book begins with a brief introduction to mathematical optimization, addressing basic concepts related to swarm intelligence, such as.

Bibliographic content of Swarm Intelligence in Data Mining. @inproceedings{GrosanSwarmII, title={Swarm Intelligence in Data Mining}, author={C. Grosan and A. Abraham and M.

Chis}, booktitle={Swarm Intelligence in Data Mining}, year={} } Devoted to novel optical measurement techniques that are applied both in industry and life sciences, this book. An Introduction to Swarm Intelligence for Multi-objective Problems in Data Mining / Satchidananda Dehuri, Susmita Ghosh, Carlos A.

Coello Coello --Multi-Criteria Ant Feature Selection Using Fuzzy Classifiers / Susana M. Vieira, Joao M.C. Sousa, Thomas A. Runkler --Multiobjective Particle Swarm Optimization in Classification-Rule Learning.

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 volume examines the application of swarm intelligence in data mining, addressing the issues of swarm intelligence and data mining using novel intelligent approaches. The book comprises 11 chapters including an introduction reviewing fundamental definitions and important research challenges.

Important features include a detailed overview of swarm intelligence and data mining paradigms. As a timely review, this book can serve as an ideal reference for graduates, lecturers, engineers and researchers in computer science, evolutionary computing, artificial intelligence, machine learning, computational intelligence, data mining, engineering optimization and designs.

The book will act as one-stop reference for readers to think and explore Swarm Intelligence and Evolutionary Algorithms seriously for real-time patient diagnosis, as the book provides solutions to various complex diseases found critical for medical practitioners to diagnose in real-world.

Swarm Intelligence systems are decentralized, self-organized algorithms used to resolve complex problems with dynamic properties, incomplete information, and limited computation capabilities.

This study provides an initial understanding of the technical aspects of swarm intelligence algorithms and their potential use in IoT-based applications.

Swarm Intelligence in Data Mining: : Abraham, Ajith, Grosan, Crina, Ramos, Vitorino: Libri in altre lingueAuthor: Ajith Abraham. The main challenge in distributing electronic health records (EHRs) for patient-centered research, market analysis, medicine investigation, healthcare data mining etc., is data privacy.

Handling the large-scale data and preserving the privacy of patients has been a challenge to researchers for a long period of time. – The quality and quantity of data are vital for the effectiveness of problem solving. Nowadays, big data analytics, which require managing an immense amount of data rapidly, has attracted more and more attention.

It is a new research area in the field of information processing techniques. It faces the big challenges and difficulties of a large amount of data, high dimensionality, and. CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Clustering aims at representing large datasets by a fewer number of prototypes or clusters.

It brings simplicity in modeling data and thus plays a central role in the process of knowledge discovery and data mining. Data mining tasks, in these days, require fast and accurate partitioning of huge datasets, which may. What is Swarm Intelligence Techniques. Definition of Swarm Intelligence Techniques: SI systems possess typically of a population of a number of agents interacting with each other within their environment.

These interactions between all agents lead to the emergence of “intelligent” global behavior, unknown to the individual agents.

‎The two-volume set of LNCS andconstitutes the proceedings of the 8th International Conference on Advances in Swarm Intelligence, ICSIheld in Fukuoka, Japan, in July/August The total of papers presented in these volumes was carefully reviewed and selected fro.

Part of book: Deterministic Artificial Intelligence. Survey of Data Mining and Applications (Review from to Now) By Adem Karahoca, Dilek Karahoca and Mert Şanver. Part of book: Data Mining Applications in Engineering and Medicine. Sinusoidal Trajectory Generation Methods for Spacecraft Feedforward Control.

By Kyle A. Baker. His areas of expertise include: artificial neural networks, swarm intelligence, evolutionary computation, data mining and artificial immune systems. He has been active in this area since and he is one of the few people in the field leading a very active research group in Swarm Intelligence, specifically in Particle Swarm Optimization (PSO).

Swarm intelligence for data mining classification tasks: an experimental study using medical decision problems. Author(s): Jose A. Saez and Emilio Corchado DOI: /PBCEH_ch14 For access to this article, please select a purchase option.He was the general chair of joint general chair of 1st&2nd BRICS CCI, program committee co-chair of IEEE WCCIpublicity chair of IEEE SSCIetc.

Prof. Ying Tan’s main interests include computational intelligence, swarm intelligence, swarm robotics, data mining, and intelligent information processing for information security.Edit this book: Order a printed copy Data mining Predictive analytics Predictive modelling Business intelligence Swarm intelligence and methods there Particular algorithms: Particle_swarm_optimization Ant colony optimization algorithms Artificial immune system Firefly algorithm, Cuckoo search,