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
A fuzzy logic based system for heavy metals loaded wastewaters monitoring
CI'10 Proceedings of the 4th WSEAS international conference on Computational intelligence
Applying artificial neural networks in environmental prediction systems
ICAI'10 Proceedings of the 11th WSEAS international conference on Automation & information
| Hi-index | 0.00 |
The forecasting problem is one of the main environmental problems that need efficient software tools. More concrete, it can mean meteorological/weather forecasting, air/soil/water pollution forecasting, flood forecasting and so on. 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 the application of neural network-based forecasting methods, as well as their combination with fuzzy logic in air pollution forecast and flood forecast in a hydrographic basin. The neuro-fuzzy based forecasting can be integrated in a more complex real time monitoring, analysis, and control system for environmental pollution or hydrological processes.