Comparison of ANN approach and analytical approaches - Ahmed, Khaled
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Evaluation of performance of irrigation systems is one from many solutions of water problems. This study compares the artificial neural network (ANN) approach with analytical solutions namely exact solution and dimensionless analysis, in order to predict of the performance and energy losses of irrigation systems. Three irrigation systems were chosen for their widely used now days in EGYPT; those systems were gated (perforated) pipes system, solid set sprinkler system and surface trickle irrigation system. A computer friendly user interfaces were developed to help agricultural and extension…mehr

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Produktbeschreibung
Evaluation of performance of irrigation systems is one from many solutions of water problems. This study compares the artificial neural network (ANN) approach with analytical solutions namely exact solution and dimensionless analysis, in order to predict of the performance and energy losses of irrigation systems. Three irrigation systems were chosen for their widely used now days in EGYPT; those systems were gated (perforated) pipes system, solid set sprinkler system and surface trickle irrigation system. A computer friendly user interfaces were developed to help agricultural and extension engineers in decision making, planning and designing irrigation system. The results showed the higher accuracy of using ANN models than analytical models in respect of field data. In addition, this study showed usefulness of using ANN technique as extension tool. Finally, this study recommended more studies well be helpful in improving ANN models and using them for agricultural and extension engineering.
Autorenporträt
Dr. Khaled Ahmed has obtained his PHD degree in Agricultural Engineering in 2006 from Ain Shams University, Cairo, Egypt.Since 2010 he has been working for King Saud University at Chair of Dates Technologies& industry (CDIT), SA. He has many articles in reputed journals and is a member of many technical working group.