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020 _a9789811509940
024 7 _a10.1007/978-981-15-0994-0
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aQ325.5
_b2020 EB
245 0 0 _aOptimization in Machine Learning and Applications
_cedited by Anand J. Kulkarni, Suresh Chandra Satapathy.
250 _a1st ed. 2020.
264 1 _aSingapore
_bSpringer Singapore :
_bImprint: Springer
_c2020.
300 _a1 recurso en línea (IX, 197 páginas)
_b57 ilustraciones, 25 ilustraciones a color.
336 _2rdacontent
_aTexto
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
347 _atext file
_bPDF
490 0 _aAlgorithms for Intelligent Systems
_x2524-7565
490 0 _aIntelligent Technologies and Robotics (Springer-42732)
505 0 _aUse of Artificial Neural Network for Abnormality Detection in Medical Images -- Deep Learning Techniques for Crime Hotspot Detection -- Optimization Techniques for Machine Learning -- A Package Including Pre-Processing, Feature Extraction, Feature Reduction, and Classification for MRI Classification -- Predictive Analysis of Lake Water Quality Using an Evolutionary Algorithm -- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swam Optimization -- A Hybridized Data Clustering for Breast Cancer Prognosis and Risk Exposure using Fuzzy C-Means and Cohort Intelligence -- Development of Algorithm for Spatial Modelling of Climate Data for Agriculture Management for the Semi-Arid Area of Maharashtra in India -- A Survey on Human Group Activity Recognition by Analyzing Person Action from Video Sequences using Machine Learning Techniques -- Artificial Intelligence in Journalism: A Boon or Bane? -- A Perspective of Artificial Intelligence in Public Relations: The Way Forward -- Roulette Wheel Selection Based Computational Intelligence Technique to Design an Efficient Transmission Policy for Energy Harvesting Sensors.
520 3 _aThis book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The book also presents formulations of real-world machine learning problems, and discusses AI solution methodologies as standalone or hybrid approaches. Lastly, it proposes novel metaheuristic methods to solve complex machine learning problems. Featuring valuable insights, the book helps readers explore new avenues leading toward multidisciplinary research discussions.
988 _aPrimersemestre_2020_Robotics
650 7 _2embne
_aAprendizaje automático
_9166090
700 1 _aKulkarni, Anand J.
_eeditor
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aSatapathy, Suresh Chandra.
_eeditor
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_998975
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9789811509933
776 0 8 _iPrinted edition:
_z9789811509957
776 0 8 _iPrinted edition:
_z9789811509964
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-15-0994-0
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
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_n0
998 _b03/2020
_dz
_ek
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