Inhaltsangabe
This book discusses the rainfall prediction. Rainfall prediction is an active topic for researchers to facilitate taking decision about crop and irrigation cycles in understanding weather and climate patterns. In the context of India's frequent changing climatic conditions the research on the rainfall prediction has gained lot of importance in recent days. In recent past rainfall prediction models using soft computing techniques have been very popular among the researchers however these models found to be complex and present poor generalization ability and generates less accuracy in prediction. This motivated to further investigate and improve the model development. In this work few machine learning techniques and evolutionary techniques are effectively used to obtain competitive results for long range rainfall prediction.
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Über die Autorin bzw. den Autor
Dr. Kavitha Rani is presently working as professor in Department of CSE at CMR Technical Campus, Hyderabad, India. She has published 15 papers in reputed National, International journals and conferences. Her area of interests is Data Mining, Machine learning, Deep Learning and Data Analytics.
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New Approach Using Machine Learning Techniques for Rainfall Prediction
Verlag:
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139449448
ISBN 13: 9786139449446
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Taschenbuch. Zustand: Neu. New Approach Using Machine Learning Techniques for Rainfall Prediction | Kavitha Rani Balmuri (u. a.) | Taschenbuch | 132 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786139449446 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Artikel-Nr. 115846850
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New Approach Using Machine Learning Techniques for Rainfall Prediction
Verlag:
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139449448
ISBN 13: 9786139449446
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Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book discusses the rainfall prediction. Rainfall prediction is an active topic for researchers to facilitate taking decision about crop and irrigation cycles in understanding weather and climate patterns. In the context of Indiäs frequent changing climatic conditions the research on the rainfall prediction has gained lot of importance in recent days. In recent past rainfall prediction models using soft computing techniques have been very popular among the researchers however these models found to be complex and present poor generalization ability and generates less accuracy in prediction. This motivated to further investigate and improve the model development. In this work few machine learning techniques and evolutionary techniques are effectively used to obtain competitive results for long range rainfall prediction. Artikel-Nr. 34027404/1
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