The fuzzy comprehensive evaluation (FCE) and the principal component analysis (PCA) model simulation and its applications in water quality assessment of Nansi Lake Basin, China

Abstract

The Fuzzy Comprehensive Evaluation (FCE) and the Principal Component Analysis (PCA) were simulated to assess water quality of the Nansi Lake Basin, China. The membership functions were established via the Nor-Half Sinusoidal Distribution Method, and the weight was calculated via the Exceeding Standard Multiple Method. To enhance the efficiency of extracting principal pollutant, the eigenequation was solved through the Jacobi Method, and the principal components were extracted based on eigenvalue, contribution ratio, accumulating contribution ratio, principal component loading and score. Water quality classification based on “National Surface Water Environmental Quality Standards of China (GB3838-2002) was used to assess the water quality. Considering the difference of the temporal and spatial distribution in average, water quality of Level I was 28.9%, 28.1%, 25.1%, 25.6%, respectively in spring, summer, autumn, and winter, which suggested that water quality in spring and summer was better than in autumn and winter. The order of water quality was Zhaoyang Lake (Level I) > Nanyang Lake (Level I) > Dushan Lake (Level III) > Weishan Lake (Level III and IV). There were four extracted principal components that can replace the fourteen pollutant indexes for assessing water quality. According to the annual mean data of the 1st principal components, the most important pollutions were heavy metals, including As (0.933), Hg (0.931), Cd (0.929), Cr(VI) (0.926), Pb (0.925), and Cu (0.534). It is proved that the combined FCE-PCA model could provide valuable information in the water quality assessment for the Nansi Lake Basin.

Environmental Safety Analysis of Red Mud-Based Cemented Backfill on Groundwater

“…The mathematical model B of the fuzzy comprehensive evaluation of groundwater with RMCB [45,51] can be then expressed as Equation ( 10…”

“…The evaluation set V is a set used to evaluate the impacts of various contaminants on the groundwater environment, and the evaluation set was set to V = {v 1 , v 2 , v 3 , v 4 , v 5 } = {I, II, III, IV, V}. The fuzzy comprehensive evaluation of water quality is a comprehensive evaluation of multiple factors [45]. Therefore, the basis of multifactor fuzzy comprehensive evaluation consists of establishing the membership function of a single factor, determining the membership, and obtaining the corresponding membership degree function [46].…”

A Review of Principal Component Analysis Algorithm for Dimensionality Reduction

“…The work of [85] provided the built-in the Fuzzy Comprehensive Evaluation-Principal Component Analysis (FCE-PCA) Model useful water quality evaluation details. The model was applied to the waters of the Lake Nancy Basin in China.…”

An effective classification approach for big data with parallel generalized Hebbian algorithm

“…Hence, it is only considered for small dimension. Implementation on PCA neural network (NN) is another alternative for PCA implementation [55]. This is done using the GHA [56] but the problem is the slow convergency of GHA which make it mandatory to perform several iterations, thereby prolonging the computational time for most GHA-based algorithms.…”