首页|Model Integration: A Case Study of Integrative Computations of Hybrid Models to Assess Water Quality of River
Model Integration: A Case Study of Integrative Computations of Hybrid Models to Assess Water Quality of River
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Process integration method is used to establish a composite model to perform computations of hybrid models for water quality assessment of Haihe River,and a resolution is presented to clear the long-term obscurity about the differences between single-factor assessment (SFA) and multifactor assessment (MFA) of water quality in this paper.Symbolic models were introduced to describe the types and orders of computations involved in SFA and such MFAs as Nemerow comprehensive index (NCI) and fuzzy comprehensive assessment (FCA).Facilitated by paired t-tests,the composite model of absolute distance (AD) was established to test the differences between SFA and MFAs on four water quality indicators (WQI).Matlab (R14) programs for these models were developed to perform integrative computations on 3 217 batches of water data obtained from seven monitoring sites of Haihe River from 2008 to 2017.Paired t-tests show that results of our SFA model (SFA-4) are not significantly different (p=0.926) from that of SFA based on all WQI,however,extremely significantly different from results ofNCI (p=0) and FCA (p=0).SFA-4 is proved by AD model to be farther away from FCA (AD-S--,F=1.075) than from NCI (AD-S→N=0.634).More than proving the deduction of SFA≥NCI≥FCA in most cases (p=0.885),the results from AD show that MFAs approach SFA when surface water becomes good (SFA=1) or worst (SFA=6),whereas depart to the farthest distance from SFA when surface water becomes worse (SFA=3).To sum up,the integrative computations involved in AD model on the water data are effective and efficient (improved by 44.2％).Furthermore,AD model shows the differences between SFA and MFAs clearly.
process integrationabsolute distancesymbolic modelsingle-factor assessmentmultifactor assessment
LIU Simin、JIA Jianhua
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School of Information Engineering, Jingdezhen Ceramic Institute, Jingdezhen 333403, Jiangxi, China
Supported by the National Natural Science Foundation of China
NETL
NSTL
万方数据
维普
