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We are surrounded by data, numerical, categorical and otherwise, which must to be analyzed and processed to convert it into information that instructs, answers or aids understanding and decision making. Data analysts in many disciplines such as business, education or medicine, are frequently asked to analyze new data sets which are often composed of numerous tables possessing different properties. They try to find completely new correlations between attributes and show new possibilities for users.   Action rules mining discusses some of data mining and knowledge discovery principles and then describe representative concepts, methods and algorithms connected with action. The author introduces the formal definition of action rule, notion of a simple association action rule and a representative action rule, the cost of association action rule, and gives a strategy how to construct simple association action rules of a lowest cost. A new approach for generating action rules from datasets with numerical attributes by incorporating a tree classifier and a pruning step based on meta-actions is also presented. In this book we can find fundamental concepts necessary for designing, using and implementing action rules as well. Detailed algorithms are provided with necessary explanation and illustrative examples.

Data mining --- Engineering & Applied Sciences --- Computer Science --- Data mining. --- Association rule mining. --- Association mining --- Association rules mining --- Mining, Association rule --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Engineering. --- Artificial intelligence. --- Computational intelligence. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- 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 --- Database searching --- Artificial Intelligence.

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Data mining is one of the most rapidly growing research areas in computer science and statistics. In Volume 1of this three volume series, we have brought together contributions from some of the most prestigious researchers in the fundamental data mining tasks of clustering, association and classification. Each of the chapters is self contained. Theoreticians and applied scientists/ engineers will find this volume valuable. Additionally, it provides a sourcebook for graduate students interested in the current direction of research in these aspects of data mining.

Data mining. --- Engineering & Applied Sciences --- Computer Science --- Association rule mining. --- Classification rule mining. --- CRM (Classification rule mining) --- Mining, Classification rule --- Association mining --- Association rules mining --- Mining, Association rule --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Engineering. --- Artificial intelligence. --- Computational intelligence. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Intelligence, Computational --- Artificial intelligence --- 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 --- Soft computing --- Data mining --- Database searching --- Artificial Intelligence.

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This monograph is devoted to theoretical and experimental study of inhibitory decision and association rules. Inhibitory rules contain on the right-hand side a relation of the kind "attribut does not equal value". The use of inhibitory rules instead of deterministic (standard) ones allows us to describe more completely information encoded in decision or information systems and to design classifiers of high quality. The most important feature of this monograph is that it includes an advanced mathematical analysis of problems on inhibitory rules. We consider algorithms for construction of inhibitory rules, bounds on minimal complexity of inhibitory rules, and algorithms for construction of the set of all minimal inhibitory rules.We also discuss results of experiments with standard and lazy classifiers based on inhibitory rules. These results show that inhibitory decision and association rules can be used in data mining and knowledge discovery both for knowledge representation and for prediction. Inhibitory rules can be also used under the analysis and design of concurrent systems. The results obtained in the monograph can be useful for researchers in such areas as machine learning, data mining and knowledge discovery, especially for those who are working in rough set theory, test theory, and logical analysis of data (LAD). The monograph can be used under the creation of courses for graduate students and for Ph.D. studies.

Association rule mining --- Rough sets --- Mathematical analysis --- Computer algorithms --- Civil Engineering --- Computer Science --- Applied Mathematics --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Data processing --- Data mining. --- Rough sets. --- Rough set theory --- Theory of rough sets --- Computer science. --- Artificial intelligence. --- Computer-aided engineering. --- Applied mathematics. --- Engineering mathematics. --- Computer Science. --- Computer-Aided Engineering (CAD, CAE) and Design. --- Appl.Mathematics/Computational Methods of Engineering. --- Artificial Intelligence (incl. Robotics). --- CAE --- Engineering --- 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 --- Informatics --- Science --- Engineering analysis --- Mathematics --- Set theory --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Computer aided design. --- Mathematical and Computational Engineering. --- Artificial Intelligence. --- CAD (Computer-aided design) --- Computer-assisted design --- Computer-aided engineering --- Design

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This Special Issue aims at providing recent advancements on open data and models. Energy and environment are the fields of application.For all the aforementioned reasons, we encourage researchers and professionals to share their original works. Topics of primary interest include, but are not limited to:Open data and models for energy sustainability;Open data science and environment applications;Open science and open governance for Sustainable Development Goals;Key performance indicators of data-aware energy modelling, planning and policy;Energy, water and sustainability database for building, district and regional systems; andBest practices and case studies.

Research & information: general --- Technology: general issues --- electric vehicles --- electricity mix --- charging profile --- emissions --- energy --- energy scenarios --- photovoltaics --- wind --- EPLANopt --- multi-objective optimization --- climate-change --- bi-level optimisation method --- evolutionary algorithms --- renewable energy --- wave energy converter --- geometric parameters --- power take-off --- levelised cost of energy --- scroll-compressor --- experimental validation --- numerical model --- layout assessment --- wave energy conversion --- real wave model --- building energy management --- energy information systems --- anomaly detection and diagnosis --- classification tree --- symbolic aggregate approximation --- association rule mining --- energy modelling --- heating transition --- modelling practices --- data-driven policy design --- local policy --- municipality --- multi-model ecologies --- energy transitions --- energy analytics --- data-driven methods --- building performance analysis energy efficiency --- energy flexibility --- occupant-centric design --- open energy data --- thermal building performance --- satellite-based solar radiation data --- meteorological reanalysis data --- ISO 52016-1 --- single-zone infiltration --- digital construction --- artificial intelligence --- digital twin --- nZEB --- energy management --- energy efficiency --- edge computing --- electric vehicles --- electricity mix --- charging profile --- emissions --- energy --- energy scenarios --- photovoltaics --- wind --- EPLANopt --- multi-objective optimization --- climate-change --- bi-level optimisation method --- evolutionary algorithms --- renewable energy --- wave energy converter --- geometric parameters --- power take-off --- levelised cost of energy --- scroll-compressor --- experimental validation --- numerical model --- layout assessment --- wave energy conversion --- real wave model --- building energy management --- energy information systems --- anomaly detection and diagnosis --- classification tree --- symbolic aggregate approximation --- association rule mining --- energy modelling --- heating transition --- modelling practices --- data-driven policy design --- local policy --- municipality --- multi-model ecologies --- energy transitions --- energy analytics --- data-driven methods --- building performance analysis energy efficiency --- energy flexibility --- occupant-centric design --- open energy data --- thermal building performance --- satellite-based solar radiation data --- meteorological reanalysis data --- ISO 52016-1 --- single-zone infiltration --- digital construction --- artificial intelligence --- digital twin --- nZEB --- energy management --- energy efficiency --- edge computing