Babak safa (8 Ergebnisse)
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Taschenbuch. Zustand: Neu. Prediction of Wheat Yield and Phenological Stages using Neural Network | Babak Safa | Taschenbuch | 60 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783330039957 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de |…Anbieter: preigu.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Rain-fed crop production, and the time of crop phenological stages occurrence, apart from its relationship to the genetic of cultivator, soil conditions, effect of pests and pathology and weeds, and the management and control quality…during the growing season etc., deeply depends on climatic events . Among them, the nature of rainfall interval, temperature variation during growth stages, speed and direction of wind and evapotranspiration are very important. Therefore, it is not very unlikely to achieve relations or systems that can predict the yield and the occurrence date of each phonological stage with higher accuracy using meteorological data. In this book, Artificial Neural Networks application in order to predict the rain-fed wheat yield and the occurrence date prediction of each phonological stage using meteorological factors were considered. We designed the artificial neural network that correctly encompasses the relations of climatic factors affecting on wheat phenological stages and yield, so that it can be used to estimate wheat production in long or short term with sufficient useful data for the specific area. 60 pp. Englisch.
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Safa BabakBabak Safa joined the Water for Food Global Institute as a Postdoctoral Research Associate in 2016. He specializes in agricultural meteorology, micro-meteorology and vegetation-atmosphere intera…ction. Safa holds a doctorate.
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Rain-fed crop production, and the time of crop phenological stages occurrence, apart from its relationship to the genetic of cultivator, soil conditions, effect of pests and pathology and weeds, and the management and control quality duri…ng the growing season etc., deeply depends on climatic events . Among them, the nature of rainfall interval, temperature variation during growth stages, speed and direction of wind and evapotranspiration are very important. Therefore, it is not very unlikely to achieve relations or systems that can predict the yield and the occurrence date of each phonological stage with higher accuracy using meteorological data. In this book, Artificial Neural Networks application in order to predict the rain-fed wheat yield and the occurrence date prediction of each phonological stage using meteorological factors were considered. We designed the artificial neural network that correctly encompasses the relations of climatic factors affecting on wheat phenological stages and yield, so that it can be used to estimate wheat production in long or short term with sufficient useful data for the specific area.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch.
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Rain-fed crop production, and the time of crop phenological stages occurrence, apart from its relationship to the genetic of cultivator, soil conditions, effect of pests and pathology and weeds, and the management and control quality durin…g the growing season etc., deeply depends on climatic events . Among them, the nature of rainfall interval, temperature variation during growth stages, speed and direction of wind and evapotranspiration are very important. Therefore, it is not very unlikely to achieve relations or systems that can predict the yield and the occurrence date of each phonological stage with higher accuracy using meteorological data. In this book, Artificial Neural Networks application in order to predict the rain-fed wheat yield and the occurrence date prediction of each phonological stage using meteorological factors were considered. We designed the artificial neural network that correctly encompasses the relations of climatic factors affecting on wheat phenological stages and yield, so that it can be used to estimate wheat production in long or short term with sufficient useful data for the specific area.
