Welfare classification using CMAC neural networks

Igli Hakrama, I. O. Bucak, Ozcan Asilkan
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Abstract

The aim of this study is to create an Artificial Neural Network (ANN) for the prediction of welfare classification of world countries using an application of the Cerebellar Model Articulation Controller (CMAC). Firstly, welfare ranking and its importance in the economy and the usage of the CMAC algorithm are introduced. In the methodology part, the application that uses CMAC is described and implemented. Trained data are put into the application before predicting the results. Finally, the results are discussed and some suggestions are supplied to be used for further studies.
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基于CMAC神经网络的福利分类
本研究的目的是利用小脑模型发音控制器(CMAC)建立一个用于预测世界各国福利分类的人工神经网络。首先介绍了福利排序及其在经济中的重要性,以及CMAC算法的应用。在方法部分,描述并实现了使用CMAC的应用程序。在预测结果之前,将经过训练的数据输入应用程序。最后,对研究结果进行了讨论,并提出了进一步研究的建议。
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