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Univ. of Alaska-Fairbanks: "Hybrid neural network/expert systems for mesoscale weather forecasting: Transferring technology to the operational forecaster"

Final Report

This Partners Project with the NWS Fairbanks office was a follow-up to a previous project on using neural networks, along with expert systems, to predict lightning in certain regions of Alaska during the summer months. This later project had four main objectives:

In relation to the first objective, a CPN was trained to predict lightning. The performance of the best CPN was better than that of the best BPN, and the researchers concluded that CPN is an effective network technology. Work on the second objective was not complete when the Partners Project ended but is continuing. As part of the third objective, the researchers used data for training the CPN which was not preselected or prescreened in contrast to what was done on the previous study using the BPN. The CPN's performance statistics on this data showed the robustness of the network in an operational environment. Additionally, the system output was modified and integrated with ARONET, the Alaska Region Operational NETwork, which is the main interface tool to forecast data used by Fairbanks forecasters. Finally, the workshop was held during the week of June 12-16, 1995.