Einstein International Journal Organization(EIJO)

Abstract  

The solar collector is the heart of any solar energy collection system the performance of solar is totally depend upon the design of solar collector system, gaining optimum performance is required. There are several different kinds of performance approaches for solar collector systems. Artificial neural networks, also called neural networks, are one of the intelligence techniques used in modelling, simulation optimization, and system control.  Artificial neural network is very faster analysis and find out the complex and nonlinear problem as compare to another techniques. Artificial intelligence neural network applied in various field engineering, energy sector, business and manufacturing sector. The primary function of the artificial neural network tool is structure training, which is carried out through experimentation with enormous amounts of data. this research paper is all about the using machine learning and deep learning technique to make accurate and predict the performance of the solar collector, which depends upon various factor that include time, metal of solar collector, location, temperature, angle, weather condition.

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