Adverse effects of inaccurate demand forecasts; stockouts, overstocks, customer loss have led academia and the business world towards accurate demand forecasting methods. Artificial Neural Network (ANN) is capable of highly accurate forecasts integrated with many variables. The use of Price and Promotion variables have increased the accuracy while the addition of other relevant variables would decrease the occurrences of errors. The use of the Federal Funds Rate as an additional macroeconomic variable to ANN forecasting models has been discussed in this research by the means of the accuracy measuring method: Average Relative Mean Absolute Error
Purpose: This work aims to evaluate demand forecasting models to determine if using exogenous factor...
The objective of this research is to obtain an accurate forecasting model for the demand for automob...
Purpose: This work aims to evaluate demand forecasting models to determine if using exogenous factor...
Adverse effects of inaccurate demand forecasts; stockouts, overstocks, customer loss have led academ...
Adverse effects of inaccurate demand forecasts; stockouts, overstocks, customer loss have led academ...
Adverse effects of inaccurate demand forecasts; stockouts, overstocks, customer loss have led academ...
Most exchange rates are volatile and mainly rely on the principle of supply and demand. Millions of ...
Research has shown that Neural Networks (NNs) when trained appropriately are the best forecasting sy...
This thesis evaluates the utility of Artificial Neural Networks (ANNs) applied to financial market a...
Forecasting accuracy drives the performance of inventory management. This study is to investigate an...
The importance of demand forecasting as a management tool is a well documented issue. However, it is...
This thesis evaluates the utility of Artificial Neural Networks (ANNs) applied to financial market a...
This study shows that neural networks have been advocated as an alternative to traditional statistic...
Forecasting is predicting or estimating a future event or trend. Supply chains have been constantly ...
The objective of this research is to obtain an accurate forecasting model for the demand for automob...
Purpose: This work aims to evaluate demand forecasting models to determine if using exogenous factor...
The objective of this research is to obtain an accurate forecasting model for the demand for automob...
Purpose: This work aims to evaluate demand forecasting models to determine if using exogenous factor...
Adverse effects of inaccurate demand forecasts; stockouts, overstocks, customer loss have led academ...
Adverse effects of inaccurate demand forecasts; stockouts, overstocks, customer loss have led academ...
Adverse effects of inaccurate demand forecasts; stockouts, overstocks, customer loss have led academ...
Most exchange rates are volatile and mainly rely on the principle of supply and demand. Millions of ...
Research has shown that Neural Networks (NNs) when trained appropriately are the best forecasting sy...
This thesis evaluates the utility of Artificial Neural Networks (ANNs) applied to financial market a...
Forecasting accuracy drives the performance of inventory management. This study is to investigate an...
The importance of demand forecasting as a management tool is a well documented issue. However, it is...
This thesis evaluates the utility of Artificial Neural Networks (ANNs) applied to financial market a...
This study shows that neural networks have been advocated as an alternative to traditional statistic...
Forecasting is predicting or estimating a future event or trend. Supply chains have been constantly ...
The objective of this research is to obtain an accurate forecasting model for the demand for automob...
Purpose: This work aims to evaluate demand forecasting models to determine if using exogenous factor...
The objective of this research is to obtain an accurate forecasting model for the demand for automob...
Purpose: This work aims to evaluate demand forecasting models to determine if using exogenous factor...