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001			394193
003			ES-MaUEC
005			20230102123105.0
007			cr nn 008mamaa
008			221017s2022 sz | s |||| 0|eng d
020			_a9783031117138
024	7		_a10.1007/978-3-031-11713-8 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
245	1	0	_aMeta Heuristic Techniques in Software Engineering and Its Applications _bMETASOFT 2022 _cedited by Mihir Narayan Mohanty, Swagatam Das, Mitrabinda Ray, Bichitrananda Patra
250			_a1st edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (X, 358 páginas) _b209 ilustraciones, 129 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aArtificial Intelligence-Enhanced Software and Systems Engineering _x2731-6033 _v1
505	0		_aPerformance analysis of Heuristic optimization algorithms for Transportation problem -- Source Code Features Based Branch Coverage Prediction using Ensemble Technique -- Implicit Methods of Multi-Factor Authentication -- Comparative Analysis of different Classifiers Using Machine Learning Algorithm for Diabetes Mellitus -- Survey on Machine Learning Techniques for Software Reliability Accuracy Prediction -- Classification of Pest in Tomato Plants using CNN -- Deep Neural Network Approach For Identifying Good Answers in Community Platforms -- Time Series Analysis of SAR-Cov-2 virus in India using Facebook's Prophet -- Model-Based Smoke Testing Approach of Service Oriented Architecture (SOA) -- Role of Hybrid Evolutionary Approaches for Feature Selection in Classification: A Review -- Evaluation of Deep Learning Models for Detecting Breast Cancer using Mammograms -- Evaluation of Crop Yield Prediction using arsenal and Ensemble Machine learning algorithms -- Notification Based Multichannel MAC (NM-MAC) Protocol for Wireless Body Area Network -- A multi Brain Tumor Classification using a Deep Reinforcement Learning Model -- A Brief Analysis on Security in Healthcare Data using Blockchain -- A Review on Test Case Selection, Prioritization and Minimization in Regression Testing -- Artificial Intelligence Advancement in Pandemic Era -- Predictive technique for Identification of Diabetes using Machine Learning -- Prognosis of Prostate Cancer Using Machine Learning -- Sign language Detection Using Tensorflow Object Detection -- Automated Test Case Prioritization using Machine Learning -- A New Approach To Solve Linear Fuzzy Stochastic Differential Equation -- An Improved Software Reliability Prediction Model by Using Feature Selection and Extreme Learning Machine -- Signal Processing Approaches for Encoded Protein Sequences in Gynaecological Cancer Hotspot Prediction: A Review -- DepNet: Deep Neural Network based model for Estimating the Crowd Count -- Dynamic Stability enhancement of Power system by Sailfish Algorithm tuned fractional SSSC control action -- Application of Machine Learning Model Based Techniques for Prediction of Heart Diseases -- Software Effort and Duration Estimation using SVM and Logistic Regression -- A framework for ranking cloud services based on an integrated BWM-Entropy-TOPSIS Method -- An Efficient and Delay-Aware Path Construction Approach Using Mobile Sink in Wireless Sensor Network -- Application of Different Control Techniques of multi-area Power Systems -- Analysis of An Ensemble Model For Network Intrusion Detection -- D2D Resource Allocation for Joint Power Control in Heterogeneous Cellular Networks -- Prediction of Covid-19 Cases in Kerala based on meteorological parameters using BiLSTM Technique.
520			_aThis book discusses an integration of machine learning with metaheuristic techniques that provide more robust and efficient ways to address traditional optimization problems. Modern metaheuristic techniques, along with their main characteristics and recent applications in artificial intelligence, software engineering, data mining, planning and scheduling, logistics and supply chains, are discussed in this book and help global leaders in fast decision making by providing quality solutions to important problems in business, engineering, economics and science. Novel ways are also discovered to attack unsolved problems in software testing and machine learning. The discussion on foundations of optimization and algorithms leads beginners to apply current approaches to optimization problems. The discussed metaheuristic algorithms include genetic algorithms, simulated annealing, ant algorithms, bee algorithms and particle swarm optimization. New developments on metaheuristics attract researchers and practitioners to apply hybrid metaheuristics in real scenarios.
700	1		_aMohanty, Mihir Narayan _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aDas, Swagatam _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aRay, Mitrabinda _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aPatra, Bichitrananda _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9783031117121
776	0	8	_iPrinted edition: _z9783031117145
776	0	8	_iPrinted edition: _z9783031117695
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-11713-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aSpringer_Robotics_2022
999			_c394193 _d394193