Machine Learning Algorithms for Prediction of Indian Summer Monsoon

Moumita Saha

ISBN 10: 365995652X / ISBN 13: 9783659956522

Verlag: LAP Lambert Academic Publishing, 2016

Beschreibung

nach der Bestellung gedruckt Neuware - Printed after ordering - Indian summer monsoon is a complex and non-linear climatic phenomenon. India being an agricultural country, the monsoon governs the pulse of life for its mankind along with the flora-fauna existing in the subcontinent. It has large impact on agriculture, renewal of fresh-water, and generation of hydro-electricity power. Monsoon is the driving force for development of economy of the country. An attempt is made to study, analyse, and predict Indian summer monsoon. Different machine learning algorithms are used for these purposes. Focus is towards identification of new predictors from different climatic variables influencing the monsoon of the sub-continent and improvement of monsoon prediction models to forecast monsoon with greater accuracy. Various clustering, community detection, and deep learning approaches are utilised to attain the goal.

Bestandsnummer des Verkäufers 9783659956522

Bibliografische Details

• Titel: Machine Learning Algorithms for Prediction of Indian Summer Monsoon
• Verlag: LAP Lambert Academic Publishing
• Erscheinungsjahr: 2016
• Sprache: Englisch
• ISBN-10: 365995652X
• ISBN-13: 9783659956522
• Einband: Taschenbuch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

Indian summer monsoon is a complex and non-linear climatic phenomenon. India being an agricultural country, the monsoon governs the pulse of life for its mankind along with the flora-fauna existing in the subcontinent. It has large impact on agriculture, renewal of fresh-water, and generation of hydro-electricity power. Monsoon is the driving force for development of economy of the country. An attempt is made to study, analyse, and predict Indian summer monsoon. Different machine learning algorithms are used for these purposes. Focus is towards identification of new predictors from different climatic variables influencing the monsoon of the sub-continent and improvement of monsoon prediction models to forecast monsoon with greater accuracy. Various clustering, community detection, and deep learning approaches are utilised to attain the goal.