Business Forecasting: Telecummunications & Gas/ Electric February 25 & 26 1999
Workshop Manual
by etc Et al


"Forecasting with Artificial Neural Network (ANN) Models: A Primer on ANN and their Application to Short-Term Forecasting Problems"

In recent years there has been a growing application of Artificial Neural Network (ANN) models for various energy and telecommunication forecasting problems. Applications include call volume forecasting, d aily gas send-out forecasting, spot price forecasting, and next-day hourly electric load forecasting. This workshop is designed to unravel the mystery of the ANN and to work through several utility forecasting applications using ANN models. Topics cove red in the workshop include: 1) Artificial Neural Network Model Structure - How Does it Work, 2) Comparison and Contrast of ANN Models with Regression Models, 3) ANN Model Terminology, 4) Building an ANN Model (i.e., Training and Learning), and 5) ANN "Next-Day" Forecasting Applications.

Manager, Boston Office

Manager, Forecasting Division



"How to Forecast in A Rapidly Changing Telecom Industry?"

The purpose of this workshop is to show, step by step, the forecasting approach to be used in the telecom industry which is getting more complex every day. Before going into the methodology, we will review the evolution which is taking place in this industry. We will discuss drivers and issues involved, and show world-class practices in the area. Due to the radical change in the market, a paradigm shift is needed in telecom forecasting. The industry needs a more holistic approach to forecasting than anything else. Furthermore, we will show how to integrate telecom forecasting with industry analysis and strategic planning. Also, we will explain how demand analysis and forecasting can add value to an increa singly complex decision making chain.

Senior Consultant

Institute of Business Forecasting

$ 45
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