Title :
Combined forecasting and cognitive Decision Support System for Indian green coffee supply chain predictive analytics
Author :
Ayyanathan, N. ; Kannammal, A.
Author_Institution :
Dept. of Comput. Applic., K.L.N. Coll. of Inf. Technol., Madurai, India
Abstract :
This research on cognitive Decision Support System for the stake holders of Indian green coffee supply chain provides the necessary business intelligence required for the improvement of market retention capability quality metrics of Indian coffee in the international market. The combined forecast model comprises of traditional extrapolative models, ARIMA model and Least square Support vector machine model. Performance criteria like, tracking signal spectrums is used for the assessment of the time series data forecast accuracy for all countries. Demand data volume in metric tonnes for all the importing nations and prediction of exporters´ share price movement in the stock market are the target vectors of this cognitive Decision support System modeling.
Keywords :
autoregressive moving average processes; decision support systems; extrapolation; forecasting theory; least squares approximations; stock markets; supply chain management; support vector machines; time series; ARIMA model; Indian green coffee supply chain predictive analytics; Least square Support vector machine model; business intelligence; cognitive decision support system; combined forecast model; stock market; time series data forecast accuracy; traditional extrapolative models; Decision support systems; Mathematical model; Predictive models; Share prices; Supply chains; Support vector machines; ARIMA model; Cognition driven Decision Support System; Combined forecast; Extrapolative models. Supply chain demand forecast and tracking signals; Least square Support vector machine; Time series forecasting;
Conference_Titel :
Cognitive Computing and Information Processing (CCIP), 2015 International Conference on
Conference_Location :
Noida
DOI :
10.1109/CCIP.2015.7100735
