Crop Climate Simulation Modelling by Rahman Sayedur (6 results)

Taschenbuch. Condition: Neu. Crop Climate Simulation Modelling | Environmental Strategies and Agricultural Development of Bangladesh | M. Sayedur Rahman (u. a.) | Taschenbuch | 220 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783848496228 | 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. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A stochastic model based on first-order Markov chain was developed to simulate daily rainfall. The model is capable of simulating daily rainfall data of any length, based on the estimated transitional probabilities, mean, standard deviation and skew coefficients of rainfall amounts. A study of rainfall probability is an approach to sound planning for any variation of rainfall either small or large. The simulation model has been used successfully to estimate daily rainfall. The Multivariate logistic regression is used to estimate the probability that it is raining. The logistic regression technique is used to compare between the actual and simulation results for a rainfall from January to December in Bangladesh. The probability of occurrence of rainfall is of vital importance in efficient planning and execution of water use program. This study describes a crop-climate simulation model under rainfed conditions in Bangladesh to be used as a tool for analyzing growth and yield to help planning and management of rice production. 220 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Rahman M. SayedurM. Sayedur Rahman received M.Sc., M. Phil and Ph.D. degree in Statistics. He was joined as a lecturer in 1988, University of Rajshahi, and subsequently he promoted as Professor in 2003. He is involved in many natio.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -A stochastic model based on first-order Markov chain was developed to simulate daily rainfall. The model is capable of simulating daily rainfall data of any length, based on the estimated transitional probabilities, mean, standard deviation and skew coefficients of rainfall amounts. A study of rainfall probability is an approach to sound planning for any variation of rainfall either small or large. The simulation model has been used successfully to estimate daily rainfall. The Multivariate logistic regression is used to estimate the probability that it is raining. The logistic regression technique is used to compare between the actual and simulation results for a rainfall from January to December in Bangladesh. The probability of occurrence of rainfall is of vital importance in efficient planning and execution of water use program. This study describes a crop-climate simulation model under rainfed conditions in Bangladesh to be used as a tool for analyzing growth and yield to help planning and management of rice production.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 220 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A stochastic model based on first-order Markov chain was developed to simulate daily rainfall. The model is capable of simulating daily rainfall data of any length, based on the estimated transitional probabilities, mean, standard deviation and skew coefficients of rainfall amounts. A study of rainfall probability is an approach to sound planning for any variation of rainfall either small or large. The simulation model has been used successfully to estimate daily rainfall. The Multivariate logistic regression is used to estimate the probability that it is raining. The logistic regression technique is used to compare between the actual and simulation results for a rainfall from January to December in Bangladesh. The probability of occurrence of rainfall is of vital importance in efficient planning and execution of water use program. This study describes a crop-climate simulation model under rainfed conditions in Bangladesh to be used as a tool for analyzing growth and yield to help planning and management of rice production.