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000922674 019__ $$a1121273655$$a1125807043$$a1136388872
000922674 020__ $$a9783030285531$$q(electronic book)
000922674 020__ $$a3030285537$$q(electronic book)
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000922674 0247_ $$a10.1007/978-3-030-28553-1$$2doi
000922674 0247_ $$a10.1007/978-3-030-28
000922674 035__ $$aSP(OCoLC)on1120104414
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000922674 08204 $$a006.38$$223
000922674 24500 $$aNature-inspired computation in data mining and machine learning /$$cXin-She Yang, Xing-Shi He, editors.
000922674 264_1 $$aCham, Switzerland :$$bSpringer,$$c[2020]
000922674 300__ $$a1 online resource (xi, 273 pages) :$$billustrations.
000922674 336__ $$atext$$btxt$$2rdacontent
000922674 337__ $$acomputer$$bc$$2rdamedia
000922674 338__ $$aonline resource$$bcr$$2rdacarrier
000922674 4901_ $$aStudies in computational intelligence,$$x1860-9503 ;$$vvolume 855
000922674 504__ $$aIncludes bibliographical references.
000922674 5050_ $$aAdaptive Improved Flower Pollination Algorithm for Global Optimization -- Algorithms for Optimization and Machine Learning over Cloud -- Implementation of Machine Learning and Data Mining to Improve Cybersecurity and Limit Vulnerabilities to Cyber Attacks -- Comparative analysis of different classifiers on crisis-related tweets: An elaborate study -- An Improved Extreme Learning Machine Tuning by Flower Pollination Algorithm -- Prospects of Machine and Deep Learning in Analysis of Vital Signs for the Improvement of Healthcare Services -- A Comprehensive Review and Performance Analysis of Firefly Algorithm for Artificial Neural Networks -- 3D Object Categorization in Cluttered Scene Using Deep Belief Network Architectures -- Performance-Based Prediction of Chronic Kidney Disease Using Machine Learning for High-Risk Cardiovascular Disease Patients -- Extraction of Named Entities from Social Media Text in Tamil Language Using N-Gram Embedding for Disaster Management -- Classification and Clustering Algorithms of Machine Learning with their Applications -- Hybrid Binary Particle Swarm Optimization and Flower Pollination Algorithm Based on Rough Set Approach for Feature Selection Problem.
000922674 506__ $$aAccess limited to authorized users.
000922674 520__ $$aThis book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning algorithms over cloud, extreme learning machines, object categorization, particle swarm optimization, flower pollination and firefly algorithms, and neural networks, it also presents case studies and applications, including classifications of crisis-related tweets, extraction of named entities in the Tamil language, performance-based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and management sciences, artificial intelligence and machine learning.
000922674 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed September 9, 2019).
000922674 650_0 $$aNatural computation.
000922674 650_0 $$aData mining.
000922674 650_0 $$aMachine learning.
000922674 7001_ $$aYang, Xin-She,$$eeditor.
000922674 7001_ $$aHe, Xing-Shi,$$eeditor.
000922674 77608 $$z3030285529
000922674 830_0 $$aStudies in computational intelligence ;$$vv. 855.
000922674 852__ $$bebk
000922674 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-28553-1$$zOnline Access$$91397441.1
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000922674 980__ $$aBIB
000922674 982__ $$aEbook
000922674 983__ $$aOnline
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