Performance comparison of techniques for water demand forecasting

Long-Term Water Demand Forecasting

This chapter reviews existing long term water demand forecasting methodologies. Based on an extensive literature review, it shows that the domain has benefited from contributions by economists, engineers and system modelers, producing a wide range of tools, many of which have been tested and adopted by practitioners. It illustrates, via three detailed case studies in the USA, the UK and Austral...

A spectrum comparison method for demand forecasting

Almost all demand forecasting methods work in the time domain. We describe a method that operates in the frequency domain. Using discrete Fourier transform, we decompose a given set of demand data into a set of sine and cosine functions. The Fourier coefficients contain information about the frequencies and amplitudes in these sinusoids and allow us to reconstruct the original given demand data...

Travel Demand Forecasting: Parameters and Techniques

Application of machine learning techniques for supply chain demand forecasting

Full collaboration in supply chains is an ideal that the participant firms should try to achieve. However, a number of factors hamper real progress in this direction. Therefore, there is a need for forecasting demand by the participants in the absence of full information about other participants’ demand. In this paper we investigate the applicability of advanced machine learning techniques, inc...

A Classification Approach for Selecting Forecasting Techniques for Intermittent Demand

The intermittent demand forecasting problem involves the forecasting of demand series that are characterized by the time between demands being significantly larger than the unit of time used for the forecast period. This causes the time series associated with the demand to have a large percentage of periods for which there are no demands. These types of series are often found in spare parts inv...