A Time-Series Data Prediction Using TensorFlow Neural Network Libraries


KIPS Transactions on Computer and Communication Systems, Vol. 8, No. 4, pp. 79-86, Apr. 2019
https://doi.org/10.3745/KTCCS.2019.8.4.79,   PDF Download:
Keywords: Artificial Neural Networks, Time-Series Data, Data Prediction, Tensorflow
Abstract

This paper describes a time-series data prediction based on artificial neural networks (ANN). In this study, a batch based ANN model and a stochastic ANN model have been implemented using TensorFlow libraries. Each model are evaluated by comparing training and testing errors that are measured through experiment. To train and test each model, tax dataset was used that are collected from the government website of indiana state budget agency in USA from 2001 to 2018. The dataset includes tax incomes of individual, product sales, company, and total tax incomes. The experimental results show that batch model reveals better performance than stochastic model. Using the batch scheme, we have conducted a prediction experiment. In the experiment, total taxes are predicted during next seven months, and compared with actual collected total taxes. The results shows that predicted data are almost same with the actual data.


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Cite this article
[IEEE Style]
K. L. Muh and S. Jang, "A Time-Series Data Prediction Using TensorFlow Neural Network Libraries," KIPS Transactions on Computer and Communication Systems, vol. 8, no. 4, pp. 79-86, 2019. DOI: https://doi.org/10.3745/KTCCS.2019.8.4.79.

[ACM Style]
Kumbayoni Lalu Muh and Sung-Bong Jang. 2019. A Time-Series Data Prediction Using TensorFlow Neural Network Libraries. KIPS Transactions on Computer and Communication Systems, 8, 4, (2019), 79-86. DOI: https://doi.org/10.3745/KTCCS.2019.8.4.79.