Publication: Development of a simple mobile determination system for potential drug in natural product based on artificial neural network
Date
2009-04-01
Authors
Tan, Bee Ling
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Abstract
The purpose of this project is to develop a mobile determination system of potential drug in natural product based on Artificial Neural Network (ANN). The project is divided into 2 parts. The first part is to find the most suitable neural network to be implemented in the potential drug determination system. This project compares the performance among the conventional Multilayered Perceptron (MLP) network trained with Back Propagation (BP), Levenberg Marquardt (LM) and Bayesian Regularization (BR) learning algorithms and the Hybrid Multilayered Perceptron (HMLP) network trained with Modified Recursive Prediction Error (MRPE) learning algorithm. The performance analysis is carried out based on the determination accuracy. The HMLP network with the MRPE algorithms obtained the best performance with accuracy of 82.03% as compared to that of the MLP network trained with BP, LM and BR with accuracy 78.56%, 80.47% and 81.25% respectively. Thus, the HMLP network is implemented in the potential drug determination system. The second part integrates the determination system in web based. The user need to login to the web site and register as a new user. After verified the email and passwords, the user can use the potential drug determination system and view the result from result page. Overall, this project has successfully developed a mobile system which can determine the potential drug of the natural product based on ANN.