An Application Of Radial Basis Function In Identifying Banana Maturity Level

Noor Zarith Aqmar, Mohamad (2008) An Application Of Radial Basis Function In Identifying Banana Maturity Level. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

This project approach the alternative way in identifying the banana maturity’s level by using Radial Basis Function (RBF) network. Radial Basis Function is one of Artificial Neural Network (ANN) algorithm that used the application of function approximation. This approximation depends on several parameters such as input, target, spread and goal. As an input, an array of seven neurons will corresponds to the average, variance and standard deviation of banana maturity’s level and four indicator related to each banana maturity’s level. After went through the learning process the network able to give an accurate result during training phase. At the end, after doing testing phase the Radial Basis Function networks give better performance and best approximation in identifying banana maturity’s level in order to overcome the conventional method.

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