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988			_aSpringer_Robotics_2020
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020			_a9783030237561
024	7		_a10.1007/978-3-030-23756-1 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9 .B45 _b2020 EB
245	0	0	_aIntelligent and Fuzzy Techniques in Big Data Analytics and Decision Making : _bProceedings of the INFUS 2019 Conference, Istanbul, Turkey, July 23-25, 2019 _cedited by Cengiz Kahraman, Selcuk Cebi, Sezi Cevik Onar, Basar Oztaysi, A. Cagri Tolga, Irem Ucal Sari
250			_aFirst edition
264		1	_aCham _bSpringer International Publishing _c2020
300			_a1 recurso en línea (XIX, 1392 páginas) _b242 ilustraciones
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	1		_aAdvances in Intelligent Systems and Computing _x2194-5357 _v1029
490	0		_aTechnologies and Robotics (Springer-42732)
505	0		_aBipolar models for a more realistic representation and processing of human judgments, intentions and preferences: a role of fuzzy logic -- An Improved Fuzzy Cognitive Mapping Method -- A new community detection algorithm based on fuzzy measures -- A predictive modeling approach to debt collection process -- Intelligent Visual Analysis in Employee Fraud Detection -- A linguistic system of defining and controlling project success -- A Hesitant Fuzzy Correspondence Analysis -- Customer Segmentation Method Determination Using Neutrosophic Sets -- Evaluating Innovation Projects in Air Cargo Sector with Fuzzy COPRAS -- Application of Fuzzy TOPSIS for credit scoring -- Supplier Selection Using Fuzzy Analytic Network Process -- A Fuzzy Based Risk Assessment Model with a Real Case Study -- Intuitionistic Fuzzy c-Control Charts Using Fuzzy Comparison Methods -- Fuzzy Evaluation of a New Search Engine Project to Fundraise NGOs -- Machine Criticality Level Assignment with Fuzzy Inference System for RCM -- Human Reliability Analysis in Healthcare: A Scenario Analysis.
520	3		_aThis book includes the proceedings of the Intelligent and Fuzzy Techniques INFUS 2019 Conference, held in Istanbul, Turkey, on July 23-25, 2019. Big data analytics refers to the strategy of analyzing large volumes of data, or big data, gathered from a wide variety of sources, including social networks, videos, digital images, sensors, and sales transaction records. Big data analytics allows data scientists and various other users to evaluate large volumes of transaction data and other data sources that traditional business systems would be unable to tackle. Data-driven and knowledge-driven approaches and techniques have been widely used in intelligent decision-making, and they are increasingly attracting attention due to their importance and effectiveness in addressing uncertainty and incompleteness. INFUS 2019 focused on intelligent and fuzzy systems with applications in big data analytics and decision-making, providing an international forum that brought together those actively involved in areas of interest to data science and knowledge engineering. These proceeding feature about 150 peer-reviewed papers from countries such as China, Iran, Turkey, Malaysia, India, USA, Spain, France, Poland, Mexico, Bulgaria, Algeria, Pakistan, Australia, Lebanon, and Czech Republic.
650		7	_2embne _9495511 _aDatos masivos _xCongresos y asambleas
650		7	_2embne _aData mining _xCongresos y asambleas _9162648
650		7	_2embne _aConjuntos difusos _xCongresos y asambleas _9145903
700	1		_aKahraman, Cengiz _eeditor _4http://id.loc.gov/vocabulary/relators/edt _997689
700	1		_aCebi, Selcuk _eeditor _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aCevik Onar, Sezi _eeditor _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aOztaysi, Basar _eeditor _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aTolga, A. Cagri _eeditor _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aSari, Irem Ucal _eeditor _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9783030237554
776	0	8	_iPrinted edition: _z9783030237578
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-23756-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_aSI _cm _dz _feng _ggw _h0 _b01/2020 _eel _zSI