000			03885cam a22004338i 4500
001			21874241
003			CSPC
005			20250306153541.0
008			210121s2021 flu b 001 0 eng
010			_a 2021001773
020			_a9780367610920 _q(hbk)
040			_aDLC _beng _erda _cDLC _dCSPC
042			_apcc
050	0	0	_aTJ808 _b.I66 2021
082	0	0	_a621.042028563 _bIn891 _223
245	0	0	_aIntroduction to AI techniques for renewable energy system / _cedited by Suman Lata Tripathi, [and 3 others].
250			_aFirst edition.
263			_a2106
264		1	_aBoca Raton, FL ; _aAbingdon, Oxon : _bCRC Press, _c2021.
300			_axii, 410 pages ; _c24 cm.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
504			_aIncludes bibliographical references and index.
505	0		_aArtificial intelligence : a new era in renewable energy systems -- Role of AI in renewable energy management -- AI-based renewable energy with emerging applications: issues and challenges -- Foundations of machine learning -- Introduction of AI techniques and approaches -- A comprehensive overview of hybrid renewable energy systems -- Dynamic modeling and performance analysis of switched-mode controller for hybrid energy systems -- Artificial intelligence and machine learning methods for renewable energy -- Artificial neural network-based power optimizer for solar photovoltaic system: an integrated approach with genetic algorithm -- Predictive maintenance: AI behind equipment failure prediction -- AI techniques for the challenges in smart energy systems -- Energy efficiency -- Renewable (bio-based) energy from natural resources (plant biomass matters) --Evolving trends for smart grid using artificial intelligent techniques -- Introduction to AI techniques for photovoltaic energy conversion system -- Deep learning-based fault identification of microgrid transformers -- Power quality improvement for grid-integrated renewable energy sources: a comparative analysis of UPQC topologies -- AI-based energy-efficient fault mitigation technique for reliability enhancement of wireless sensor network -- AI techniques applied to wind energy -- Comparative performance analysis of multi-objective metaheuristic approaches for parameter identification of three-diode-modeled photovoltaic cells -- Artificial intelligence techniques in smart grid -- Parameter identification of a new reverse two-diode model by moth flame optimizer -- Time series energy prediction and improved decision-making -- Machine learning-enabled cyber security in smart grids.
520			_a"The book summarizes commonly used AI methodologies in renewal energy, with a particular emphasis on neural networks, fuzzy logic, and genetic algorithms. Book outlines selected AI applications for renewable energy. In particular, discusses methods using the AI approach for the following applications using suitable examples: prediction and modeling of solar radiation, seizing, performances, and controls of the solar photovoltaic (PV) systems"-- _cProvided by publisher.
650		0	_aRenewable energy sources.
650		0	_aPower-plants _xAutomatic control.
650		0	_aArtificial intelligence.
700	1		_aTripathi, Suman Lata, _eeditor.
700	1		_aDubey, Mithilesh Kumar, _eeditor.
700	1		_aRishiwal, Vinay, _eeditor.
700	1		_aPadmanaban, Sanjeevikumar, _eeditor.
776	0	8	_iOnline version: _tIntroduction to AI techniques for renewable energy system _bFirst edition _dBoca Raton : CRC Press, 2021 _z9781003104445 _w(DLC) 2021001774
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBK _e23 _h621.042028563 _iIn891 _kENG _m2021 _n0
999			_c29034 _d29034