This paper proposes an intelligent forecasting system based on a feedforward-neural-network-aided grey model (FNAGM), which integrates a first-order single variable grey model (GM(1,1)) and a feedforward neural network. There are three phases in the system process, including initialization phase, GM(1,1) prediction phase and FNAGM prediction phase. First, some parameters required in the FNAGM a...

In this paper the properties of a hydrometeorological forecasting system for forecasting river flows have been analysed using a probabilistic forecast convergence score (FCS). The focus on fixed event forecasts provides a forecaster’s approach to system behaviour and adds an important perspective to the suite of forecast verification tools commonly used in this field. A low FCS indicates a more...

Flood forecasting in rivers and coastal waters demands careful attention both to the reliability of the forecasts and the safety of the decisions made on the basis of the results. Advances in data driven modelling have improved the accuracy of forecasts made using physically based models. The hybrid modelling approach combines the best features of physically based and data driven modelling, eit...

The systematic decline of in situ networks for hydrologic measurements has been recognized as a crucial limitation to advancing hydrologic monitoring in medium to large basins, especially those that are already sparsely instrumented. As a collective response, sections of the hydrologic community have recently forged partnerships for the development of space-borne missions for cost-effective, ye...

DeciDe, born as a project funded by ESA/ESRIN, is now a system for flood forecasting at the city of Florence based on the integration of heterogeneous data sources. For DeciDe a specific technique has been developed to use couples of ERS-2 PRI images from the same frame and track for comparison with corresponding moisture maps computed from rainfall fields. Couples of data sets are used to negl...

An accurate and stable short-term traffic forecasting model is very important for intelligent transportation systems (ITS). The forecasting results can be used to relieve traffic congestion and improve the mobility of transportation. This paper proposes a new hybrid model of grey system theory and neural networks with particle swarm optimization, namely, GNN-PSO. The proposed hybrid model can e...

Sales forecasting is one of the most crucial issues addressed in business. Control and evaluation of future sales still seem concerned both researchers and policy makers and managers of companies. this research propose an intelligent hybrid sales forecasting system Delphi-FCBPN sales forecast based on Delphi Method, fuzzy clustering and Back-propagation (BP) Neural Networks with adaptive learni...

A watershed simulation and forecasting system is widely used in Finland for simulation of hydrological cycle and for making real-time forecasts. The system is based on a watershed model. This was based originally on the HBV-model and simulates the hydrological cycle using standard meteorological data. The model simulates the whole land area of Finland, including cross-border watersheds. This is...