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Multiple-Criteria Decision-Making (MCDM) Techniques for Business Processes Information Management

Authors: --- ---
ISBN: 9783038976424 Year: Pages: 320 DOI: 10.3390/books978-3-03897-643-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-03-08 11:42:05
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Abstract

Information management is a common paradigm in modern decision-making. A wide range of decision-making techniques have been proposed in the literature to model complex business and engineering processes. In this Special Issue, 16 selected and peer-reviewed original research articles contribute to business information management in various current real-world problems by proposing crisp or uncertain multiple-criteria decision-making (MCDM) models and techniques, mostly including multi-attribute decision-making (MADM) approaches, in addition to a single paper proposing an interactive multi-objective decision-making (MODM) approach. Particular attention is devoted to information aggregation operators; 65% of papers dealt with this item. The topics of this Special Issue gained attention in Europe and Asia. A total of 48 authors from seven countries contributed to this Issue. The papers are mainly concentrated in three application areas: supplier selection and rational order allocation, the evaluation and selection of goods or facilities, and personnel selection/partner selection. A number of new approaches are proposed that are expected to attract great interest from the research community.

Keywords

multi-criteria decision-making --- group decision-making --- subcontractor evaluation --- MCDM --- MADM --- fuzzy sets --- fuzzy EDAS --- multi-attribute decision making --- projection model --- bi-directional projection model --- Pythagorean uncertain linguistic variable --- rough number --- rough weighted aggregated sum product assessment (WASPAS) --- rough analytical hierarchical process (AHP) --- multiple criteria decision making (MCDM) --- supplier --- supplier selection --- order allocation --- multiobjective optimization --- interactive approach --- desirability function --- Pythagorean fuzzy set --- Muirhead mean --- multiple criteria group decision-making --- multiple attributes decision-making --- group decision-making --- unbalanced linguistic set --- prioritized average operator --- maximizing deviation model --- Pythagorean fuzzy set --- Muirhead mean --- interaction operational laws --- multi-attribute group decision-making --- green supplier --- rough ANP --- trapezoidal fuzzy number --- rough boundary interval --- evidence theory --- trust interval --- multiple attribute decision making --- linguistic cubic variable --- Dombi operations --- linguistic cubic variable Dombi weighted arithmetic average (LCVDWAA) operator --- linguistic cubic variable Dombi weighted geometric average (LCVDWGA) operator --- single-valued linguistic neutrosophic interval linguistic number --- score function --- weighted aggregation operator --- decision making --- multiple attribute decision making --- nonnegative normal neutrosophic number --- aggregation operator --- multi-criteria decision-making --- multi-hesitant fuzzy sets --- aggregation operators --- hesitant probabilistic fuzzy element (HPFE) --- Einstein operations --- hesitant probabilistic fuzzy Einstein aggregation operators --- multiple attribute decision making (MADM). --- ANFIS --- warehouse --- queuing systems --- logistics --- uncertain group decision-making support systems --- multiple criteria decision-making --- reliable group decision-making --- interval multiplicative preference relations --- rough sets --- binary discernibility matrices --- deterministic finite automata --- multiple-criteria decision-making (MCDM) --- multi-attribute decision-making (MADM) --- fuzzy sets --- neutrosophic sets --- rough sets --- aggregation operators --- adaptive neuro-fuzzy inference system (ANFIS)

Flood Forecasting Using Machine Learning Methods

Authors: --- ---
ISBN: 9783038975489 Year: Pages: 376 DOI: 10.3390/books978-3-03897-549-6 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2019-03-08 11:42:05
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Abstract

This book is a printed edition of the Special Issue Flood Forecasting Using Machine Learning Methods that was published in Water

Keywords

data scarce basins --- runoff series --- data forward prediction --- ensemble empirical mode decomposition (EEMD) --- stopping criteria --- method of tracking energy differences (MTED) --- deep learning --- convolutional neural networks --- superpixel --- urban water bodies --- high-resolution remote-sensing images --- monthly streamflow forecasting --- artificial neural network --- ensemble technique --- phase space reconstruction --- empirical wavelet transform --- hybrid neural network --- flood forecasting --- self-organizing map --- bat algorithm --- particle swarm optimization --- flood routing --- Muskingum model --- machine learning methods --- St. Venant equations --- rating curve method --- nonlinear Muskingum model --- hydrograph predictions --- flood routing --- Muskingum model --- hydrologic models --- improved bat algorithm --- Wilson flood --- Karahan flood --- flood susceptibility modeling --- ANFIS --- cultural algorithm --- bees algorithm --- invasive weed optimization --- Haraz watershed --- ANN-based models --- flood inundation map --- self-organizing map (SOM) --- recurrent nonlinear autoregressive with exogenous inputs (RNARX) --- ensemble technique --- artificial neural networks --- uncertainty --- streamflow predictions --- sensitivity --- flood forecasting --- extreme learning machine (ELM) --- backtracking search optimization algorithm (BSA) --- the upper Yangtze River --- deep learning --- LSTM network --- water level forecast --- the Three Gorges Dam --- Dongting Lake --- Muskingum model --- wolf pack algorithm --- parameters --- optimization --- flood routing --- flash-flood --- precipitation-runoff --- forecasting --- lag analysis --- random forest --- machine learning --- flood prediction --- flood forecasting --- hydrologic model --- rainfall–runoff, hybrid & --- ensemble machine learning --- artificial neural network --- support vector machine --- natural hazards & --- disasters --- adaptive neuro-fuzzy inference system (ANFIS) --- decision tree --- survey --- classification and regression trees (CART), data science --- big data --- artificial intelligence --- soft computing --- extreme event management --- time series prediction --- LSTM --- rainfall-runoff --- flood events --- flood forecasting --- data assimilation --- particle filter algorithm --- micro-model --- Lower Yellow River --- ANN --- hydrometeorology --- flood forecasting --- real-time --- postprocessing --- machine learning --- early flood warning systems --- hydroinformatics --- database --- flood forecast --- Google Maps

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eng (2)


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2019 (2)