2014 | OriginalPaper | Buchkapitel
Neuro-Fuzzy Data Mining Mexico’s Economic Data
verfasst von : Gustavo Becerra-Gaviño, Liliana Ibeth Barbosa-Santillán
Erschienen in: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Verlag: Springer International Publishing
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Given the increase of data being collected, there is a need to explore the use of tools to automate the recognition and extraction of patterns within some targeted data. The present work explores the use of a neuro-fuzzy classifier for the multi-factor productivity from the manufacturing sector in the Mexican economy. The chosen data set contains the time series for the variables: Sale Value of products, Wages, Work Force, Days Worked, and Hours Worked. The data is taken from the Banco de Información Económica at the Instituto Nacional de Estadística y Geografía. The neuro-fuzzy system is implemented on top of the Neuroph library extending on the ideas behind the Neuro-Fuzzy Reasoner. A sample run tends to assign the same values given by a visual inspection.