Fuzzy neural network water quality evaluation
no vote
Evaluation is based on the assessment of water quality standards and water quality indicators values sampled water samples, sampling water samples through a mathematical model to determine water quality. Analysis of water quality indicators there are many, including ammonia, dissolved oxygen, chemical oxygen demand and permanganate index of six indicators, total phosphorus and total nitrogen. Using fuzzy theory and methods, theories and methods of water quality assessment based on comparisons on the basis of rigorous mathematical logic. Neural networks are effectively available directly from the sample study, it has parallel computing, fault-tolerant capability as well as self-learning function and so on. Fuzzy neural network combines the best aspects of neural networks and fuzzy systems, constructed with a neural networks Fuzzy systems using neural network learning method, based on the input and output sample from design and adjustment of fuzzy system design parameters, and implementa