temporal association rule based di prakashkumar rana (10 risultati)

Condizione: New. 1st edition NO-PA16APR2015-KAP.

Paperback. Condizione: Brand New. 168 pages. 8.66x5.91x0.38 inches. In Stock.

Taschenbuch. Condizione: Neu. Temporal Association Rule Based Models for Weather Prediction | Concept and Stepwise Model Preparation | Dipti Prakashkumar Rana (u. a.) | Taschenbuch | 168 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9786202076166 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -From the starting era of computers, computerized systems are extensively utilized in weather forecasting. Due to the boom of internet and online environment of sensors and technology, the huge and variety of weather data is available for prediction. Traditional weather prediction approaches are no longer adequate with respect to time. Thus research work for weather attracts new generation of researchers to achieve a new metric of success by the fast, accurate and efficient solution by inclusion of indirect weather data, novelty and automation. This book, therefore, provides a new metric of success for temporal weather data prediction and supplemental parameters to consider in the traditional weather analysis for accurate prediction. The book covers the analysis and explanation to prepare the models gradually using geo-spatial temporal weather data. The analysis should help shed some light on exciting weather environment and mining. The book should be especially useful to professionals in weather forecasting and researchers, or anyone else who may be considering the research on online weather data using data mining, machine learning, etc 168 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Prakashkumar Rana DiptiDr. Dipti Prakashkumar Rana, is a faculty member at Computer Engineering Department, Sardar Vallabhbhai National Institute of Technology (SVNIT), Surat, India. She is having teaching experience of more than 17 .

Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -From the starting era of computers, computerized systems are extensively utilized in weather forecasting. Due to the boom of internet and online environment of sensors and technology, the huge and variety of weather data is available for prediction. Traditional weather prediction approaches are no longer adequate with respect to time. Thus research work for weather attracts new generation of researchers to achieve a new metric of success by the fast, accurate and efficient solution by inclusion of indirect weather data, novelty and automation. This book, therefore, provides a new metric of success for temporal weather data prediction and supplemental parameters to consider in the traditional weather analysis for accurate prediction. The book covers the analysis and explanation to prepare the models gradually using geo-spatial temporal weather data. The analysis should help shed some light on exciting weather environment and mining. The book should be especially useful to professionals in weather forecasting and researchers, or anyone else who may be considering the research on online weather data using data mining, machine learning, etcBooks on Demand GmbH, Überseering 33, 22297 Hamburg 168 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - From the starting era of computers, computerized systems are extensively utilized in weather forecasting. Due to the boom of internet and online environment of sensors and technology, the huge and variety of weather data is available for prediction. Traditional weather prediction approaches are no longer adequate with respect to time. Thus research work for weather attracts new generation of researchers to achieve a new metric of success by the fast, accurate and efficient solution by inclusion of indirect weather data, novelty and automation. This book, therefore, provides a new metric of success for temporal weather data prediction and supplemental parameters to consider in the traditional weather analysis for accurate prediction. The book covers the analysis and explanation to prepare the models gradually using geo-spatial temporal weather data. The analysis should help shed some light on exciting weather environment and mining. The book should be especially useful to professionals in weather forecasting and researchers, or anyone else who may be considering the research on online weather data using data mining, machine learning, etc.