Growth Estimation with Artificial Neural Network Considering Weather Parameters Using Factor and Principal Component Analysis

The production of a plant in terms of fruit generation plays a major role in economic and financial condition of the state and the country. If the information related to fruit generation is available before time, the planners of the state in various fields find it easy to perform their work in various fields related to them. By observing the initial growth of shoot length it is needed to predict the shoot length at the maturity. An effort has been made to predict the growth of shoot length using the method of artificial neural network using the fuzzy data. The performance of that model has been verified using certain statistical models (least square technique based on linear, exponential, asymptotic, logistic equation). For estimation of growth of shoot length, the effect of maximum and minimum temperature, rainfall, maximum and minimum humidity has also been considered using the method of factor analysis and principal component analysis.

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