in India. The order of the best ARIMA model was found to be (2,1,0). Further, efforts were made to forecast, as accurate …A time series modeling approach (Box-Jenkins’ ARIMA model) has been used in this study to forecast sugarcane production … as possible, the future sugarcane production for a period upto five years by fitting ARIMA(2,1,0) model to our time …

The forecasting of energy consumption is essential for any country to study the future energy demand and to introduce … the necessary government policies. This paper presents the formulation of forecasting models based on the Artificial … Neural Network (ANN) for the consumption of conventional energy sources. In India, the total energy consumption for coal, oil …

The forecasting of energy consumption is essential for any country to study the future energy demand and to introduce … the necessary government policies. This paper presents the formulation of forecasting models based on the Artificial … Neural Network (ANN) for the consumption of conventional energy sources. In India, the total energy consumption for coal, oil …

The rapid growth in banking indicators in the North Eastern region of India following nationalisation of 14 major banks …

Forecasting of prices of commodities specially those of agricultural commodities is very difficult because they are not … capacity, transportation etc. In this paper times series namely ARIMA (Autoregressive Integrated Moving Average) methodology … given by Box and Jenkins has been used for forecasting prices of edible oils and this approach has been compared with ANN …

ARIMA-SVM model is the best forecasting model to achieve high forecast accuracy and better returns. … three different hybrid models combining linear ARIMA and non-linear models such as support vector machines (SVM), artificial … neural network (ANN) and random forest (RF) models to predict the stock index returns. The performance of ARIMA-SVM, ARIMA …

price level. Based on different diagnostic and evaluation criteria, the best forecasting model for predicting inflation in …

There are many econometric methods for forecasting by different economic variables in the future. recently, the … procedures of dynamic forecasting either for univariate or multivariate models were available for estimation on the software … models, with respect to, estimation, choosing the best fit model for forecasting by the economic variables, i.e., labor and …

This study was designed: (a) to investigate a simple neural-network solution to forecasting the special class of time … special class of linear time series and that the two-layered network can be a useful forecasting alternative to the widely …

This paper presents a multistage supply chain model that is based on Autoregressive Integrated Moving Average (ARIMA …) time-series models. Given an ARIMA model of consumer demand and the lead times at each stage, it is shown that the orders … and inventories at each stage are also ARIMA, and closed-form expressions for these models are given. The paper also …