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The impacts of climate change on water resource management, as well as increasingly severe natural disasters over the last decades, have caught global attention. Reliable and accurate hydrological forecasts are essential for efficient water resource management and the mitigation of natural disasters. While the notorious nonlinear hydrological processes make accurate forecasts a very challenging task, it requires advanced techniques to build accurate forecast models and reliable management systems. One of the newest techniques for modeling complex systems is artificial intelligence (AI). AI can replicate the way humans learn and has great capability to efficiently extract crucial information from large amounts of data to solve complex problems. The fourteen research papers published in this Special Issue contribute significantly to the uncertainty assessment of operational hydrologic forecasting under changing environmental conditions and the promotion of water resources management by using the latest advanced techniques, such as AI techniques. The fourteen contributions across four major research areas: (1) machine learning approaches to hydrologic forecasting; (2) uncertainty analysis and assessment on hydrological modeling under changing environments; (3) AI techniques for optimizing multi-objective reservoir operation; (4) adaption strategies of extreme hydrological events for hazard mitigation. The papers published in this issue will not only advance water sciences but also help policymakers to achieve more sustainable and effective water resource management.

Research & information: general --- water resources management --- landslide --- dammed lake --- flood risk --- time-varying parameter --- GR4J model --- changing environments --- temporal transferability --- western China --- cascade hydropower reservoirs --- multi-objective optimization --- TOPSIS --- gravitational search algorithm --- opposition learning --- partial mutation --- elastic-ball modification --- Snowmelt Runoff Model --- parameter uncertainty --- data-scarce deglaciating river basin --- climate change impacts --- generalized likelihood uncertainty estimation --- Yangtze River --- cascade reservoirs --- impoundment operation --- GloFAS-Seasonal --- forecast evaluation --- small and medium-scale rivers --- highly urbanized area --- flood control --- whole region perspective --- coupled models --- flood-risk map --- hydrodynamic modelling --- Sequential Gaussian Simulation --- urban stormwater --- probabilistic forecast --- Unscented Kalman Filter --- artificial neural networks --- Three Gorges Reservoir --- Mahalanobis-Taguchi System --- grey entropy method --- signal-to-noise ratio --- degree of balance and approach --- interval number --- multi-objective optimal operation model --- feasible search space --- Pareto-front optimal solution set --- loss–benefit ratio of ecology and power generation --- elasticity coefficient --- empirical mode decomposition --- Hushan reservoir --- data synthesis --- urban hydrological model --- Generalized Likelihood Uncertainty Estimation (GLUE) --- Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) --- uncertainty analysis --- NDVI --- Yarlung Zangbo River --- machine learning model --- random forest --- Internet of Things (IoT) --- regional flood inundation depth --- recurrent nonlinear autoregressive with exogenous inputs (RNARX) --- artificial intelligence --- machine learning --- multi-objective reservoir operation --- hydrologic forecasting --- uncertainty --- risk

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In the current context of the electronic governance of society, both administrations and citizens are demanding greater participation of all the actors involved in the decision-making process relative to the governance of society. This book presents collective works published in the recent Special Issue (SI) entitled “Optimization for Decision Making”. These works give an appropriate response to the new challenges raised, the decision-making process can be done by applying different methods and tools, as well as using different objectives. In real-life problems, the formulation of decision-making problems and application of optimization techniques to support decisions are particularly complex and a wide range of optimization techniques and methodologies are used to minimize risks, improve quality in making decisions, or, in general, to solve problems. In addition, a sensitivity or robustness analysis should be done to validate/analyze the influence of uncertainty regarding decision-making. This book brings together a collection of inter-/multi-disciplinary works applied to the optimization for decision making in a coherent manner.

probabilistic dual hesitant fuzzy sets --- distance measures --- aggregation operators --- consumer behavior --- multi-criteria decision-making --- maximum deviation method --- Monorail --- urban transportation planning --- Analytic Network Process --- Technique for Order Preference by Similarity to Ideal Solution --- shift scheduling --- goal programming --- ANP --- natural gas combined cycle power plant --- energy sector --- Analytic Hierarchy Process (AHP) --- group decision making --- consistency --- compatibility --- multiple criteria group decision making (MCGDM) problems --- picture fuzzy sets (PFSs) --- picture 2-tuple linguistic numbers (P2TLNs) --- picture 2-tuple linguistic sets (P2TLSs) --- EDAS model --- green supplier selection --- human development --- internal security --- MCDM --- weight balancing --- WEBIRA --- cluster analysis --- homogeneous groups --- Bayesian analysis --- multiple attribute decision-making (MADM) --- q-rung orthopair fuzzy sets (q-ROFSs) --- cosine function --- cosine similarity measure --- pattern recognition --- scheme selection --- group decision-making --- hesitant fuzzy set --- interval-valued probability --- muirhead mean and programming model --- dual hesitant Pythagorean fuzzy sets (DHPFSs) --- dual hesitant Pythagorean fuzzy generalized weighted Heronian mean (DHPFGWHM) operator --- dual hesitant Pythagorean fuzzy generalized geometric weighted Heronian mean (DHPFGGWHM) operator --- supply chain management --- hesitant fuzzy element (HFE) --- Hamacher operations --- hesitant fuzzy Hamacher power-aggregation operators --- multiple-attribute decision-making (MADM) --- air traffic management --- work-shift scheduling problem --- variable neighborhood search --- performance analysis --- optimization --- decision-making --- MADM --- SAW --- COPRAS --- TOPSIS --- PROMETHEE --- MOORA --- normalization --- stability

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In the current context of the electronic governance of society, both administrations and citizens are demanding greater participation of all the actors involved in the decision-making process relative to the governance of society. This book presents collective works published in the recent Special Issue (SI) entitled “Optimization for Decision Making”. These works give an appropriate response to the new challenges raised, the decision-making process can be done by applying different methods and tools, as well as using different objectives. In real-life problems, the formulation of decision-making problems and application of optimization techniques to support decisions are particularly complex and a wide range of optimization techniques and methodologies are used to minimize risks, improve quality in making decisions, or, in general, to solve problems. In addition, a sensitivity or robustness analysis should be done to validate/analyze the influence of uncertainty regarding decision-making. This book brings together a collection of inter-/multi-disciplinary works applied to the optimization for decision making in a coherent manner.

History of engineering & technology --- probabilistic dual hesitant fuzzy sets --- distance measures --- aggregation operators --- consumer behavior --- multi-criteria decision-making --- maximum deviation method --- Monorail --- urban transportation planning --- Analytic Network Process --- Technique for Order Preference by Similarity to Ideal Solution --- shift scheduling --- goal programming --- ANP --- natural gas combined cycle power plant --- energy sector --- Analytic Hierarchy Process (AHP) --- group decision making --- consistency --- compatibility --- multiple criteria group decision making (MCGDM) problems --- picture fuzzy sets (PFSs) --- picture 2-tuple linguistic numbers (P2TLNs) --- picture 2-tuple linguistic sets (P2TLSs) --- EDAS model --- green supplier selection --- human development --- internal security --- MCDM --- weight balancing --- WEBIRA --- cluster analysis --- homogeneous groups --- Bayesian analysis --- multiple attribute decision-making (MADM) --- q-rung orthopair fuzzy sets (q-ROFSs) --- cosine function --- cosine similarity measure --- pattern recognition --- scheme selection --- group decision-making --- hesitant fuzzy set --- interval-valued probability --- muirhead mean and programming model --- dual hesitant Pythagorean fuzzy sets (DHPFSs) --- dual hesitant Pythagorean fuzzy generalized weighted Heronian mean (DHPFGWHM) operator --- dual hesitant Pythagorean fuzzy generalized geometric weighted Heronian mean (DHPFGGWHM) operator --- supply chain management --- hesitant fuzzy element (HFE) --- Hamacher operations --- hesitant fuzzy Hamacher power-aggregation operators --- multiple-attribute decision-making (MADM) --- air traffic management --- work-shift scheduling problem --- variable neighborhood search --- performance analysis --- optimization --- decision-making --- MADM --- SAW --- COPRAS --- TOPSIS --- PROMETHEE --- MOORA --- normalization --- stability

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Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal developers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution. The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach. It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems. The theory is supported by numerous examples and computational illustrations. An essential book for anyone working on optimization and decision making under uncertainty, Robust Optimization also makes an ideal graduate textbook on the subject.

Robust optimization. --- Linear programming. --- 519.8 --- 681.3*G16 --- 681.3*G16 Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- 519.8 Operational research --- Operational research --- Robust optimization --- Linear programming --- Optimisation robuste --- Programmation linéaire --- Optimization, Robust --- RO (Robust optimization) --- Mathematical optimization --- Production scheduling --- Programming (Mathematics) --- 0O. --- Accuracy and precision. --- Additive model. --- Almost surely. --- Approximation algorithm. --- Approximation. --- Best, worst and average case. --- Bifurcation theory. --- Big O notation. --- Candidate solution. --- Central limit theorem. --- Chaos theory. --- Coefficient. --- Computational complexity theory. --- Constrained optimization. --- Convex hull. --- Convex optimization. --- Convex set. --- Cumulative distribution function. --- Curse of dimensionality. --- Decision problem. --- Decision rule. --- Degeneracy (mathematics). --- Diagram (category theory). --- Duality (optimization). --- Dynamic programming. --- Exponential function. --- Feasible region. --- Floor and ceiling functions. --- For All Practical Purposes. --- Free product. --- Ideal solution. --- Identity matrix. --- Inequality (mathematics). --- Infimum and supremum. --- Integer programming. --- Law of large numbers. --- Likelihood-ratio test. --- Linear dynamical system. --- Linear inequality. --- Linear map. --- Linear matrix inequality. --- Linear regression. --- Loss function. --- Margin classifier. --- Markov chain. --- Markov decision process. --- Mathematical optimization. --- Max-plus algebra. --- Maxima and minima. --- Multivariate normal distribution. --- NP-hardness. --- Norm (mathematics). --- Normal distribution. --- Optimal control. --- Optimization problem. --- Orientability. --- P versus NP problem. --- Pairwise. --- Parameter. --- Parametric family. --- Probability distribution. --- Probability. --- Proportionality (mathematics). --- Quantity. --- Random variable. --- Relative interior. --- Robust control. --- Robust decision-making. --- Semi-infinite. --- Sensitivity analysis. --- Simple set. --- Singular value. --- Skew-symmetric matrix. --- Slack variable. --- Special case. --- Spherical model. --- Spline (mathematics). --- State variable. --- Stochastic calculus. --- Stochastic control. --- Stochastic optimization. --- Stochastic programming. --- Stochastic. --- Strong duality. --- Support vector machine. --- Theorem. --- Time complexity. --- Uncertainty. --- Uniform distribution (discrete). --- Unimodality. --- Upper and lower bounds. --- Variable (mathematics). --- Virtual displacement. --- Weak duality. --- Wiener filter. --- With high probability. --- Without loss of generality.

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In the current competitive scenario, the banking industry must contend with multiple challenges tied to regulations, legacy systems, disruptive models/technologies, new competitors, and a restive customer base, while simultaneously pursuing new strategies for sustainable growth. Banking institutions that can address these emerging challenges and opportunities to effectively balance long-term goals with short-term performance pressures could be aptly rewarded. This book comprises a selection of papers addressing some of these relevant issues concerning the current challenges and opportunities for international banking institutions. Papers in this collection focus on the digital transformation of the banking industry and its effect on sustainability, the emergence of new competitors such as FinTech companies, the role of mobile banking in the industry, the connections between sustainability and financial performance, and other general sustainability and corporate social responsibility (CSR) topics related to the banking industry. The book is a Special Issue of the MDPI journal Sustainability, which has been sponsored by the Santander Financial Institute (SANFI), a Spanish research and training institution created as a collaboration between Santander Bank and the University of Cantabria. SANFI works to identify, develop, support, and promote knowledge, study, talent, and innovation in the financial sector.

Economics, finance, business & management --- stimulus-response model --- utilitarian value --- Hedonic value --- salesperson selling behaviors --- customer satisfaction --- loan expansion --- GDP --- NPL --- ARDL --- VECM --- Johansen test of co-integration --- unit root --- non-performing loans --- sovereign debt distress --- tail dependence --- gaussian copula regression --- mobile financial services (MFS) --- trust --- perceived risk --- structural equation modeling (SEM) --- multiple-criteria decision-making (MCDM) --- technique for order preference by similarity to ideal solution (TOPSIS) --- analytic hierarchy process (AHP) --- data envelopment analysis --- commercial banks --- product innovation --- performance evaluation --- innovation risk --- digital financial inclusion --- risk-coping ability --- vulnerability to poverty --- instrumental variable estimation --- emotional intelligence --- work-family conflict --- job burnout --- employees’ turnover intention --- perceived organizational support --- the Vietnamese banking industry --- stochastic DEA --- multi-attribute decision making --- ordinal variable --- cross-efficiency --- corporate social responsibility disclosure (CSRD) --- financial performance --- Islamic Banking Industry of Pakistan --- GRI --- AAOIFI --- CSRD index --- cost of equity --- IFRS adoption --- European banks --- corporate governance --- banking regulation --- CSP–CFP relationship --- banking sustainability --- glass ceiling --- board composition --- equal opportunity policy --- CSR --- communication --- discourse --- exposition --- narrative --- storytelling --- banking --- catering --- utilitarian service --- hedonic service --- sustainable finance --- sustainable financial products --- sustainable banking --- SDGs --- sustainable development --- Latin America --- ESG. --- digital transformation --- knowledge management --- digital government --- public sector --- public administration --- peer-to-peer lending --- bank risk --- insolvency risk --- illiquidity risk --- financial inclusion --- vulnerable rural areas --- sustainable solutions --- central bank digital currency --- social sustainability --- pharmacy network --- sustainable access to cash --- nonperforming loans --- macroeconomic factors --- econometric model --- exchange rate --- unemployment rate --- inflation rate --- MoM(micro-operating mechanism) --- regulatory sandbox --- fintech --- type by enterprise --- innovation competencies --- patents data --- evidence-based policy --- European financial services --- SMEs --- nonfinancial information --- sustainable reporting --- disclosure --- lexical analysis --- nonfinancial reporting --- dynamic provisioning --- macroprudential supervision --- counter-cyclical adjustment --- innovative solution --- mobile banking --- Nigeria --- sub-Saharan Africa (SSA) --- qualitative meta-synthesis (QMS) --- banking industry --- value in use approach --- FinTech innovation --- valuation --- patent application --- market power --- efficiency --- profitability --- risk --- CBDC --- digital currency --- bank run --- central bank --- economic sustainability --- organizational ambidexterity --- blended ambidexterity --- innovation process --- buy-now-pay-later --- regulatory failure --- regulation --- consumer behaviour --- bank --- barriers --- digitalisation --- management --- perception --- transformation --- social media --- admiration --- consumer loyalty --- sustainability