A case study of knowledge modelling in an air pollution control decision support system
AI Communications - Binding Environmental Sciences and AI
River flow estimation using adaptive neuro fuzzy inference system
Mathematics and Computers in Simulation
Artificial neural networks as support for leaf area modelling in crop canopies
ICCOMP'08 Proceedings of the 12th WSEAS international conference on Computers
An application of artificial neural networks in environmental pollution forecasting
AIA '08 Proceedings of the 26th IASTED International Conference on Artificial Intelligence and Applications
The neural network-based forecasting in environmental systems
WSEAS Transactions on Systems and Control
| Hi-index | 0.00 |
One of the main environmental problem that need efficient software tools is the prediction problem. More concrete, it can mean meteorological prediction, air/soil/water pollution prediction, flood prediction and so on. In the last decade several methods based on artificial intelligence were proposed by taken into account that they can offer more informed methods that use domain specific knowledge and provide solutions faster than the traditional methods, those based on a mathematical formalism. In this paper we present two case studies of applying feedforward artificial neural networks to air pollution forecast and to flood forecast in a hydrographic basin. Some experimental results are also discussed. The neural based prediction can be integrated in a more complex real time monitoring, analysis, and control system for environmental pollution or hydrological processes.