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"Online decision making under uncertainty and time constraints represents one of the most challenging problems for robust intelligent agents. In an increasingly dynamic, interconnected, and real-time world, intelligent systems must adapt dynamically to uncertainties, update existing plans to accommodate new requests and events, and produce high-quality decisions under severe time constraints. Such online decision-making applications are becoming increasingly common: ambulance dispatching and emergency city-evacuation routing, for example, are inherently online decision-making problems; other applications include packet scheduling for Internet communications and reservation systems. This book presents a novel framework, online stochastic optimization, to address this challenge. This framework assumes that the distribution of future requests, or an approximation thereof, is available for sampling, as is the case in many applications that make either historical data or predictive models available. It assumes additionally that the distribution of future requests is independent of current decisions, which is also the case in a variety of applications and holds significant computational advantages. The book presents several online stochastic algorithms implementing the framework, provides performance guarantees, and demonstrates a variety of applications. It discusses how to relax some of the assumptions in using historical sampling and machine learning and analyzes different underlying algorithmic problems. And finally, the book discusses the framework's possible limitations and suggests directions for future research."--Publisher's website.

Stochastic processes --- Combinatorial optimization --- Online algorithms --- Operations research --- Processus stochastiques --- Optimisation combinatoire --- Recherche opérationnelle --- Stochastic processes. --- Combinatorial optimization. --- Online algorithms. --- Operations research. --- 681.3*G13 --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Computer algorithms --- Online data processing --- Optimization, Combinatorial --- Combinatorial analysis --- Mathematical optimization --- Random processes --- Probabilities --- Numerical linear algebra: conditioning; determinants; eigenvalues and eigenvectors; error analysis; linear systems; matrix inversion; pseudoinverses; singular value decomposition; sparse, structured, and very large systems (direct and iterative methods) --- COMPUTER SCIENCE/General

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The present book contains five papers accepted and published in the Special Issue, “Fuzzy Natural Logic in IFSA-EUSFLAT 2021”, of the journal Mathematics (MDPI). These papers are extended versions of the contributions presented in the conference “The 19th World Congress of the International Fuzzy Systems Association and the 12th Conference of the European Society for Fuzzy Logic and Technology jointly with the AGOP, IJCRS, and FQAS conferences”, which took place in Bratislava (Slovakia) from September 19 to September 24, 2021. Fuzzy Natural Logic (FNL) is a system of mathematical fuzzy logic theories that enables us to model natural language terms and rules while accounting for their inherent vagueness and allows us to reason and argue using the tools developed in them. FNL includes, among others, the theory of evaluative linguistic expressions (e.g., small, very large, etc.), the theory of fuzzy and intermediate quantifiers (e.g., most, few, many, etc.), and the theory of fuzzy/linguistic IF–THEN rules and logical inference. The papers in this Special Issue use the various aspects and concepts of FNL mentioned above and apply them to a wide range of problems both theoretically and practically oriented. This book will be of interest for researchers working in the areas of fuzzy logic, applied linguistics, generalized quantifiers, and their applications.

Research & information: general --- Mathematics & science --- fuzzy Peterson’s syllogisms --- fuzzy intermediate quantifiers --- graded Peterson’s cube of opposition --- linguistic universals --- linguistic complexity --- evaluative expressions --- fuzzy grammar --- linguistic gradience --- linguistic constraints --- grammaticality --- sentiment analysis --- closeness --- closeness matrix --- closeness space --- function similarity --- fuzzy partition --- fuzzy transform --- preimage problem --- singular value decomposition --- evolving fuzzy neural network --- or-neuron --- auction fraud --- knowledge extraction --- n/a --- fuzzy Peterson's syllogisms --- graded Peterson's cube of opposition

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This Special Issue presents the latest state-of-the-art research on solid fuels technology with dedicated, focused research papers. There are a variety of topics to choose from among the seven published re-search works to bring you up to date with the current trends in academia and industry.

peak shaving --- battery storage --- peak demand pricing --- lithium-ion --- tariff structure --- receiving-end system --- multi-infeed HVDCs --- security assessment --- emergency control strategy --- electromagnetic transient (EMT)-transient stability (TS) hybrid simulation --- impedance determination --- lossy compression algorithms --- singular value decomposition --- wavelet transformation --- voltage control --- deep deterministic policy gradient --- deep reinforcement learning --- model uncertainties --- energy communities --- machine learning --- forecasting --- abnormal data --- wind power --- outliers --- electricity consumption representative profiles --- self-consumption

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Sparse matrices --- Iterative methods (Mathematics) --- Differential equations, Partial --- Matrices éparses --- Itération (Mathématiques) --- Equations aux dérivées partielles --- Numerical solutions --- Solutions numériques --- Sparse matrices. --- Numerical solutions. --- Iterative methods (Mathematics). --- Matrices éparses --- Itération (Mathématiques) --- Equations aux dérivées partielles --- Solutions numériques --- Numerical solutions of algebraic equations --- 519.61 --- 681.3*G13 --- -Iterative methods (Mathematics) --- Spare matrix techniques --- Iteration (Mathematics) --- Numerical methods of algebra --- Numerical linear algebra: conditioning; determinants; eigenvalues and eigenvectors; error analysis; linear systems; matrix inversion; pseudoinverses; singular value decomposition; sparse, structured, and very large systems (direct and iterative methods) --- 519.61 Numerical methods of algebra --- Matrices --- Numerical analysis --- Partial differential equations --- Differential equations, Partial - Numerical solutions

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519.6 --- 681.3*G13 --- Computational mathematics. Numerical analysis. Computer programming --- Numerical linear algebra: conditioning; determinants; eigenvalues and eigenvectors; error analysis; linear systems; matrix inversion; pseudoinverses; singular value decomposition; sparse, structured, and very large systems (direct and iterative methods) --- 519.6 Computational mathematics. Numerical analysis. Computer programming --- Computer science --- Mathematical optimization --- Parallel algorithms --- Operations research --- Optimisation mathématique --- Algorithmes parallèles --- Recherche opérationnelle --- Algorithms --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Simulation methods --- System analysis --- Optimisation mathématique. --- Algorithmes parallèles. --- Recherche opérationnelle. --- Optimisation mathématique. --- Algorithmes parallèles. --- Recherche opérationnelle.