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Shiguo Xu,Yixiao Cui,Chuanxi Yang,Shujing Wei,Wenping Dong,Lihui Huang,Changqing Liu,Zongming Ren,Weiliang Wang 대한환경공학회 2021 Environmental Engineering Research Vol.26 No.2
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 1<SUP>st</SUP> 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.
Yunjian Xu,Shiguo Peng,Aiyin Guo 제어·로봇·시스템학회 2018 International Journal of Control, Automation, and Vol.16 No.2
This paper investigates the leader-following consensus problem for a class of nonlinear delayed multiagent systems with randomly occurring uncertainties and stochastic disturbances under impulsive control inputs. For this class of multi-agent system, we present a novel impulsive control protocol which can effectively reduce the control cost and is easy to implement. Two consensus criteria are derived for ensuring global exponential consensus of nonlinear delayed multi-agent systems under non-uniformly distributed impulsive control signals based on comparison principle and average impulsive interval. Compared with the consensus criteria which are derived by the upper bound or lower bound of the impulse intervals in existing results, the obtained criteria are proved to be easier to be satisfied. Simulation results illustrate the effectiveness of the theoretical results.