Abstract
Temperature is one of the most principle factors affects aquaculture system. The water temperature is very important parameter for shrimp growth. It can cause stress and mortality or superior environment for growth and reproduction. The required temperature for optimal growth is 34oC, if temperature increase up to 38oC it causes death of the shrimp, so it is important to control water temperature. Solar thermal water heating system is designed to supply an aquaculture pond with the required hot water in Mersa Matruh in Egypt as presented in this paper. This paper introduces a complete mathematical modeling and MATLAB SIMULINK model for the solar thermal aquaculture system. Moreover the paper presents the control of pond water temperature using artificial intelligence technique. Neural networks are massively parallel processors that have the ability to learn patterns through a training experience. Because of this feature, they are often well suited for modeling complex and non-linear processes such as those commonly found in the heating system. They have been used to solve complicated practical problems. The simulation results indicate that, the control unit success in keeping water temperature constant at the desired temperature by controlling the hot water flow rate.
Highlights
The shrimp farming is an important economical activity in many countries [1]
This paper introduces a complete mathematical modeling and MATLAB SIMULINK model for the solar thermal aquaculture system
The study of artificial neural networks (ANN) is one of the two major branches of intelligence control, which is based on the concept of artificial intelligence (AI)
Summary
The shrimp farming is an important economical activity in many countries [1]. Intensive aquaculture is a modern cultivation way and it develops fast in many countries. The purpose for applying process control technology to aquaculture in developed countries encompasses many socioeconomic factors, including variable climate. Anticipated benefits for aquaculture process control systems are to be increased process efficiency, reduced energy and water losses, reduced labor costs, reduced stress and disease, improved accounting, improved understanding of the process [3]. The study of artificial neural networks (ANN) is one of the two major branches of intelligence control, which is based on the concept of artificial intelligence (AI). The ANNs are good for some tasks while lacking in some others They are good for tasks involving incomplete data sets, fuzzy or incomplete information and for highly complex and ill-defined problems, where humans usually decide on an intuitional basis [4,5,6]. ANN control is chosen to this task due to high efficiency in control application
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