Abstract
The rapid growth in the number and variety of applications of the fuzzy logic controller and neural networks reflects the advantages of the intelligent techniques applications. Neuro-fuzzy modeling is aimed at solving real world decision making, modeling and control system problems, witch are usually imprecisely designed and require human operator intervention. In this paper neuro-fuzzy method with their ability to incorporate human knowledge are used in the conception and design of hybrid intelligent systems and models. Implementation of the neuro-fuzzy models and algorithms by using the weighting sums method is proposed
Cuvinte cheie
neural network
pollution
GIS
fuzzy
hybrid
water