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Case-based reasoning. --- Case-based learning --- Reasoning

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Disasters are characterized by severe disruptions of the society’s functionality and adverse impacts on humans, the environment, and economy that cannot be coped with by society using its own resources. This work presents a decision support method that identifies appropriate measures for protecting the public in the course of a nuclear accident. The method particularly considers the issue of uncertainty in decision-making as well as the structured integration of experience and expert knowledge.

Entscheidungsunterstützung --- Katastrophenmanagement --- Fallbasiertes Schließen --- nuklearer Notfallschutz --- decision support --- disaster management --- case-based reasoning --- nuclear emergency management

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"This collection examines case-based reasoning in constitutional adjudication, that is, how courts decide on constitutional cases by referring to their own prior case law and the case law of other national, foreign and international courts. Argumentation based on judicial authority is now fundamental to the resolution of constitutional disputes. At the same time, it is the most common form of reasoning used by courts. This volume shows not only the strengths and weaknesses of such argumentation, but also its serious methodological shortcomings. The book is comparative in nature, with individual chapters examining similar problems that different courts have resolved in different ways. The research covers three types of courts, namely the civil law constitutional courts of Germany, Italy, Poland, Lithuania, and Hungary, the common law supreme courts of the United States, Canada, and Australia, and the European international courts represented by the European Court of Human Rights, and the Court of Justice of the European Union"-- Provided by the publisher.

Constitutional law --- Constitutional law. --- Philosophy. --- Constitutional limitations --- Constitutionalism --- Constitutions --- Limitations, Constitutional --- Public law --- Administrative law --- Interpretation and construction --- case-based reasoning --- constitutional adjudication --- constitutional courts --- European international courts --- precedents

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The book by Professors Avramenko and Kraslawski is unique in several important ways. First, it is an impressive and in-depth treatment of the essence of the case–based reasoning strategy and case-based design dwelling upon the algorithmic facet of the paradigm. Second, the authors provided an excellent applied research framework by showing how this development can be effectively utilized in real word complicated environment of process engineering- a pursuit that is rarely reported in the literature in such a comprehensive manner as done in this book. In a highly authoritative and systematic manner, the authors guide the reader through the essential features of the CBR machinery.

Case-based reasoning. --- Raisonnement par cas --- Case-based reasoning --- Production engineering --- Civil Engineering --- Applied Mathematics --- Computer Science --- Engineering & Applied Sciences --- Civil & Environmental Engineering --- Reasoning. --- Case-based learning --- Argumentation --- Ratiocination --- Engineering. --- Artificial intelligence. --- Applied mathematics. --- Engineering mathematics. --- Engineering design. --- Appl.Mathematics/Computational Methods of Engineering. --- Artificial Intelligence (incl. Robotics). --- Engineering Design. --- Design, Engineering --- Engineering --- Industrial design --- Strains and stresses --- Engineering analysis --- Mathematical analysis --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Design --- Mathematics --- Reason --- Thought and thinking --- Judgment (Logic) --- Logic --- Reasoning --- Mathematical and Computational Engineering. --- Artificial Intelligence. --- Production engineering. --- Manufacturing engineering --- Process engineering --- Industrial engineering --- Mechanical engineering

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Effective smart grid operation requires rapid decisions in a data-rich, but information-limited, environment. In this context, grid sensor data-streaming cannot provide the system operators with the necessary information to act on in the time frames necessary to minimize the impact of the disturbances. Even if there are fast models that can convert the data into information, the smart grid operator must deal with the challenge of not having a full understanding of the context of the information, and, therefore, the information content cannot be used with any high degree of confidence. To address this issue, data mining has been recognized as the most promising enabling technology for improving decision-making processes, providing the right information at the right moment to the right decision-maker. This Special Issue is focused on emerging methodologies for data mining in smart grids. In this area, it addresses many relevant topics, ranging from methods for uncertainty management, to advanced dispatching. This Special Issue not only focuses on methodological breakthroughs and roadmaps in implementing the methodology, but also presents the much-needed sharing of the best practices. Topics include, but are not limited to, the following:  Fuzziness in smart grids computing  Emerging techniques for renewable energy forecasting  Robust and proactive solution of optimal smart grids operation  Fuzzy-based smart grids monitoring and control frameworks  Granular computing for uncertainty management in smart grids  Self-organizing and decentralized paradigms for information processing

voltage regulation --- smart grid --- decentralized control architecture --- multi-agent systems --- t-SNE algorithm --- numerical weather prediction --- data preprocessing --- data visualization --- wind power generation --- partial discharge --- gas insulated switchgear --- case-based reasoning --- data matching --- variational autoencoder --- DSHW --- TBATS --- NN-AR --- time-series clustering --- decentral smart grid control (DSGC) --- interpretable and accurate DSGC-stability prediction --- data mining --- computational intelligence --- fuzzy rule-based classifiers --- multi-objective evolutionary optimization --- power systems resilience --- dynamic Bayesian network --- Markov model --- probabilistic modeling --- resilience models