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Journal of Engineering and Applied Sciences

Data Mining based Prediction of Unemployment Rate Data by using Radial Basis Function Neural Network (RBFNN)
Younis Kadthem Hameed, Wahab S. Mohammed and Fadhel Kadhem Zaidan

Abstract: Data mining is one of the knowledge discovery steps in database in which modeling techniques are applied. In this study, the unemployment rate in the Iraqi database prediction model is determined according to the RBF neural network where the principle and algorithm of the RBF is used. Our study also predicts the future unemployment rate in Iraq. To increase the efficiency of mining process, some pre-processing needs to be done to the data. Experimental results showed the good accuracy when applied to the adjust data.

How to cite this article
Younis Kadthem Hameed, Wahab S. Mohammed and Fadhel Kadhem Zaidan, 2019. Data Mining based Prediction of Unemployment Rate Data by using Radial Basis Function Neural Network (RBFNN). Journal of Engineering and Applied Sciences, 14: 6240-6244.

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