Sinossi
Monitoring agricultural activities has benefited so much over last 20 years from the advances in Remote Sensing (RS). A crop growth model holds a vital role in agricultural monitoring system. To run crop models are quite useful especially for prediction, however, the parameter determination in large area is in practical a difficult task. A method was proposed by Ines, (2002) to optimize the input parameters of a one-dimensional crop model (SWAP) by assimilating simulated evapotranspiration with remote sensing data. The optimization is based on GA (Genetic Algorithm). However, it requires huge computational time, which is one of the constraints in practical implementation of the method. Cluster is a type of parallel and distributed processing system, provides us with increased computing capabilities and which can help to remove the computational time constraints. Thus, a parallel crop model (SWAP-GA) procedures for remote sensed images is considered. In this study, a numerical experiment with three different SWAP-GA cluster implementation schemes is presented to show the strengths and limitations of these proposed approaches using Optima, Magi and Maeka clusters.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
L'autore
Dr. Md. Shamim Akhter is the Head of Graduate Program and Assistant Professor,Faculty of Science & IT, American International University-Bangladesh (AIUB). His research interests are Evolutionary Algorithms & Models for their Parallelization, RS & GIS applications and High Performance Computing (HPC). He is a member of IEEE-CS, ACM and JARC-Net.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Distributed Crop Parameter Assimilation Models
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LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659270253
ISBN 13: 9783659270253
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Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Akhter Md. ShamimDr. Md. Shamim Akhter is the Head of Graduate Program and Assistant Professor,Faculty of Science & IT, American International University-Bangladesh (AIUB). His research interests are Evolutionary Algorithms & Models . Codice articolo 5144608
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Distributed Crop Parameter Assimilation Models
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VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2012
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ISBN 13: 9783659270253
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Distributed Crop Parameter Assimilation Models
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VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2012
ISBN 10: 3659270253
ISBN 13: 9783659270253
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Distributed Crop Parameter Assimilation Models
Editore:
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2012
ISBN 10: 3659270253
ISBN 13: 9783659270253
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Distributed Crop Parameter Assimilation Models : Part I
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LAP Lambert Academic Publishing, 2012
ISBN 10: 3659270253
ISBN 13: 9783659270253
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Monitoring agricultural activities has benefited so much over last 20 years from the advances in Remote Sensing (RS). A crop growth model holds a vital role in agricultural monitoring system. To run crop models are quite useful especially for prediction, however, the parameter determination in large area is in practical a difficult task. A method was proposed by Ines, (2002) to optimize the input parameters of a one-dimensional crop model (SWAP) by assimilating simulated evapotranspiration with remote sensing data. The optimization is based on GA (Genetic Algorithm). However, it requires huge computational time, which is one of the constraints in practical implementation of the method. Cluster is a type of parallel and distributed processing system, provides us with increased computing capabilities and which can help to remove the computational time constraints. Thus, a parallel crop model (SWAP-GA) procedures for remote sensed images is considered. In this study, a numerical experiment with three different SWAP-GA cluster implementation schemes is presented to show the strengths and limitations of these proposed approaches using Optima, Magi and Maeka clusters. Codice articolo 9783659270253
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Distributed Crop Parameter Assimilation Models: Part I
Editore:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659270253
ISBN 13: 9783659270253
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