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This book deals with uncertainty forecasting based on a fuzzy time series approach, including fuzzy random processes and artificial neural networks. A consideration of data and measurement uncertainty enhances forecasting in a wide range of applications, particularly in the fields of engineering, environmental science and civil engineering. Uncertain data are described by means of a new incremental fuzzy representation which permits a complete and accurate estimation of uncertainty. The book is aimed at engineers as well as professionals working in related fields. Descriptive, modeling and forecasting methods pertaining to fuzzy time series are introduced and explained in detail. Emphasis is placed on forecasting with the aid of fuzzy random processes, such as fuzzy ARMA processes and fuzzy white-noise processes, as well as forecasting based on artificial neural networks. All numerical algorithms are comprehensively described and demonstrated by way of practical examples.
Engineering --- Uncertainty. --- Fuzzy mathematics. --- Mathematical models. --- Mathematics --- Reasoning --- Statistics. --- Mechanics, applied. --- Distribution (Probability theory. --- Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. --- Theoretical and Applied Mechanics. --- Monitoring/Environmental Analysis. --- Building Construction and Design. --- Probability Theory and Stochastic Processes. --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Applied mechanics --- Engineering, Mechanical --- Engineering mathematics --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Statistics . --- Mechanics. --- Mechanics, Applied. --- Environmental monitoring. --- Buildings—Design and construction. --- Building. --- Construction. --- Engineering, Architectural. --- Probabilities. --- Biomonitoring (Ecology) --- Ecological monitoring --- Environmental quality --- Monitoring, Environmental --- Applied ecology --- Environmental engineering --- Pollution --- Classical mechanics --- Newtonian mechanics --- Physics --- Dynamics --- Quantum theory --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Architectural engineering --- Buildings --- Construction --- Construction science --- Engineering, Architectural --- Structural design --- Structural engineering --- Architecture --- Construction industry --- Measurement --- Monitoring --- Design and construction --- Architecture. --- Engineering. --- Industrial arts --- Technology --- Architecture, Western (Western countries) --- Building design --- Western architecture (Western countries) --- Art --- Building --- Architecture, Primitive
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Engineering --- Fuzzy mathematics. --- Uncertainty. --- Mathematical models.
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Operational research. Game theory --- Classical mechanics. Field theory --- Statistical physics --- Engineering sciences. Technology --- Computer. Automation --- Building materials. Building technology --- Heating, climatisation, ventilation and air conditioning --- statistische kwaliteitscontrole --- industriële statistieken --- toegepaste mechanica --- stochastische analyse --- airconditioning --- algoritmen --- kansrekening --- mechanica --- HVAC (heating ventilation airconditioning) --- numerieke analyse
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This book deals with uncertainty forecasting based on a fuzzy time series approach, including fuzzy random processes and artificial neural networks. A consideration of data and measurement uncertainty enhances forecasting in a wide range of applications, particularly in the fields of engineering, environmental science and civil engineering. Uncertain data are described by means of a new incremental fuzzy representation which permits a complete and accurate estimation of uncertainty. The book is aimed at engineers as well as professionals working in related fields. Descriptive, modeling and forecasting methods pertaining to fuzzy time series are introduced and explained in detail. Emphasis is placed on forecasting with the aid of fuzzy random processes, such as fuzzy ARMA processes and fuzzy white-noise processes, as well as forecasting based on artificial neural networks. All numerical algorithms are comprehensively described and demonstrated by way of practical examples.
Operational research. Game theory --- Classical mechanics. Field theory --- Statistical physics --- Engineering sciences. Technology --- Computer. Automation --- Building materials. Building technology --- Heating, climatisation, ventilation and air conditioning --- statistische kwaliteitscontrole --- industriële statistieken --- toegepaste mechanica --- stochastische analyse --- airconditioning --- algoritmen --- kansrekening --- mechanica --- HVAC (heating ventilation airconditioning) --- numerieke analyse
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