Application of variable fuzzy pattern recognition model with synthetic weight in the assessment of water quality dynamics
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Abstract:
Water quality evaluation includes the description of water state and variation process of water quality. Due to the char2 acteristics of water quality, such as fuzziness, uncertainty, and randomness, the variable pattern recognition model was applied to evaluate water quality dynamics. T he weight was determined using the coupling analytic hierarchy process and entropy method, so the original water quality data and scientific research can be combined together. T he Monte Carlo method was used to analyze the effects of index uncertainty on water quality evaluation, and the model was used to conduct monthly evaluation of water quality dynamics in the Biliu reservoir. The results showed that water quality in the Biliu reservoir is between level II and III, there are no significant changes between each month but water quality in August and September are worse, and the main pollu2 tion index is total nitrogen.
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