Publication Type:

Conference Paper


2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), IEEE, Chennai, India (2016)




40s Combed CONE, 40s Karded HANK, advanced analytics model, ARIMA, ARIMA models, autoregressive moving average processes, Business intelligence, Cotton, Cotton forecast, cotton price, Cotton Yarn prices, forecasting theory, K Nearest neighbors, KNN models, Market research, mathematical model, Multi variant regression, Predictive models, Price prediction, pricing, Production, Profitability, Shankar-6, Spinning, spinning (textiles), Textiles, Yarn, Yarn analytics, yarn price forecasting, yarn price prediction


<p>Making profits and investing the capital in an efficient way is really a tough task in the sectors like textiles and spinning, as the Cotton Yarn prices highly fluctuate. So, the main goal of this project is to forecast the yarn price (40s Karded HANK, 40s Combed CONE) using cotton price (Shankar-6) forecast and also other attributes that influence the yarn price. The unique aspect of this paper is that the accuracy is achieved by integrating seasonality, ARIMA and KNN models (i.e. values predicted using Seasonality and ARIMA are future used to predict yarn price using KNN Algorithm). Using the integrated model stated above, finally we are able to achieve the accuracy of 97% in yarn price prediction. Also the results are tabled in [TABLE XII.] and [TABLE XIV.] for the period of 3 months from Oct 2015 to Dec 2015. By knowing the future trends of the yarn price, the industry will decide to stock or sell the products to gain profits.</p>

Cite this Research Publication

Dr. Venkataraman D., Vinay, N., Vardhan, T. V. V., Boppudi, S. P., Reddy, R. Y., and Dr. P. Balasubramanian, “Yarn Price Prediction using Advanced Analytics Model”, in 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), Chennai, India, 2016.