文章基本信息

标题：Overview of the artificial neural networks and fuzzy logic applications in operational hydrological forecasting systems
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作者：Jitendra P. Dave¹ ; Divyakant T. Meva²
期刊名称：Oriental Journal of Computer Science and Technology
印刷版ISSN：0974-6471
出版年度：2009
卷号：2
期号：2
页码：127-132
出版社：Oriental Scientific Publishing Company
摘要：Damage due to flooding has increase in many countries in the last years, and due to the globalclimate change, which is now recognized as a real threat, an increase in the occurrence of floodingevents and especially of flash flooding events is likely to continue into the future. In those conditionsand because building new flood defences structures for defending vulnerable areas has serious financialimplications, the timely forecasting of floods is becoming more important for flood defence and ingeneral for water management purposes. The complexity of natural systems and of hydrologicalprocesses that influence river levels evolutions make the traditional modelling approaches, based onmirroring natural processes with physically based equations very difficult. Despite the fact that in thelast decades the Operational Hydrological Forecasting Systems were significantly developed, becomingmore and more complex systems, ingesting and processing in real time a great amount of data fromautomated hydrometrical and meteorological stations networks and high resolution grided data fromradars and satellites, together with the use of distributed hydrological models, the warning and forecastsimprovements are not very significant, in many cases the performance of the new physically baseddistributed models being comparable with the "older" conceptual lumped models. The paper presentsan overview of some alternative and complementary modelling approaches, artificial neural networksand fuzzy logic systems, possible applications for the improvements of the Operational HydrologicalForecasting Systems, and presenting also some example of rainfall-runoff modelling implementations
关键词：Artificial neural networks; fuzzy logic applications; forecasting systems.