000			04088nam a22004813i 4500
001			EBC6434351
003			MiAaPQ
005			20240724114815.0
006			m o d |
007			cr cnu||||||||
008			240724s2020 xx o ||||0 eng d
020			_a9781000318821 _q(electronic bk.)
020			_z9780367439255
035			_a(MiAaPQ)EBC6434351
035			_a(Au-PeEL)EBL6434351
035			_a(OCoLC)1228046673
040			_aMiAaPQ _beng _erda _epn _cMiAaPQ _dMiAaPQ
050		4	_aTK7872.D48 .E446 2021
082	0		_a006.3
100	1		_aElhoseny, Mohamed.
245	1	0	_aArtificial Intelligence Techniques in IoT Sensor Networks.
250			_a1st ed.
264		1	_aMilton : _bCRC Press LLC, _c2020.
264		4	_c©2022.
300			_a1 online resource (232 pages)
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	1		_aChapman and Hall/CRC Distributed Sensing and Intelligent Systems Series
505	0		_aCover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- About the Editors -- Chapter 1: Adaptive Regularized Gaussian Kernel FCM for the Segmentation of Medical Images: An Artificial Intelligence-Based IoT Implementation for Teleradiology Network -- Chapter 2: Artificial Intelligence-Based Fuzzy Logic with Modified Particle Swarm Optimization Algorithm for Internet of Things-Enabled Logistic Transportation Planning -- Chapter 3: Butterfly Optimization-Based Feature Selection with Gradient Boosting Tree for Big Data Analytics in Social Internet of Things -- Chapter 4: An Energy-Efficient Fuzzy Logic-Based Clustering with Data Aggregation Protocol for WSN-Assisted IoT System -- Chapter 5: Analysis of Smart Home Recommendation System from Natural Language Processing Services with Clustering Technique -- Chapter 6: Metaheuristic-Based Kernel Extreme Learning Machine Model for Disease Diagnosis in Industrial Internet of Things Sensor Networks -- Chapter 7: Fuzzy Support Vector Machine with SMOTE for Handling Class Imbalanced Data in IoT-Based Cloud Environment -- Chapter 8: Energy-Efficient Unequal Clustering Algorithm Using Hybridization of Social Spider with Krill Herd in IoT-Assisted Wireless Sensor Networks -- Chapter 9: IoT Sensor Networks with 5G-Enabled Faster RCNN-Based Generative Adversarial Network Model for Face Sketch Synthesis -- Chapter 10: Artificial Intelligence-Based Textual Cyberbullying Detection for Twitter Data Analysis in Cloud-Based Internet of Things -- Chapter 11: An Energy-Efficient Quasi-Oppositional Krill Herd Algorithm-Based Clustering Protocol for Internet of Things Sensor Networks -- Chapter 12: An Effective Social Internet of Things (SIoT) Model for Malicious Node Detection in Wireless Sensor Networks.
505	8		_aChapter 13: IoT-Based Automated Skin Lesion Detection and Classification Using Gray Wolf Optimization with Deep Neural Network -- Index.
520			_aThis book explores the frontiers and challenges of applying Artificial Intelligence (AI) techniques to Sensor Networks. It covers how sensor networks are widely used to collect environmental parameters in homes, buildings, vehicles, etc., and how they are used as a source of information to aid decision-making processes.
588			_aDescription based on publisher supplied metadata and other sources.
590			_aElectronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
650		0	_aSensor networks.
655		4	_aElectronic books.
700	1		_aShankar, K.
700	1		_aAbdel-Basset, Mohamed.
776	0	8	_iPrint version: _aElhoseny, Mohamed _tArtificial Intelligence Techniques in IoT Sensor Networks _dMilton : CRC Press LLC,c2020 _z9780367439255
797	2		_aProQuest (Firm)
830		0	_aChapman and Hall/CRC Distributed Sensing and Intelligent Systems Series
856	4	0	_uhttps://ebookcentral.proquest.com/lib/orpp/detail.action?docID=6434351 _zClick to View
999			_c23413 _d23413