Evidence map›Paper›PMID 28488149›Full record

ArticleEnvironmental science and pollution research international2017

Identification of water quality management policy of watershed system with multiple uncertain interactions using a multi-level-factorial risk-inference-based possibilistic-probabilistic programming approach.

Jing Liu, Yongping Li, Guohe Huang, Haiyan Fu, Junlong Zhang, Guanhui Cheng

Abstract read
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In one paragraph

Article in Environmental science and pollution research international, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jing LiuDepartment of Environmental Engineering, Xiamen University of Technology, Xiamen, 361024, China.
Yongping LiDepartment of Environmental Engineering, Xiamen University of Technology, Xiamen, 361024, China. yongping.li@iseis.org.
Guohe HuangInstitute for Energy, Environment, and Sustainable Communities, University of Regina, Sask, Regina, S4S 0A2, Canada.
Haiyan FuDepartment of Environmental Engineering, Xiamen University of Technology, Xiamen, 361024, China.
Junlong ZhangSino-Canada Energy and Environmental Research Center, North China Electric Power University, Beijing, 102206, China.
Guanhui ChengInstitute for Energy, Environment, and Sustainable Communities, University of Regina, Sask, Regina, S4S 0A2, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, a multi-level-factorial risk-inference-based possibilistic-probabilistic programming (MRPP) method is proposed for supporting water quality management under multiple uncertainties. The MRPP method can handle uncertainties expressed as fuzzy-random-boundary intervals, probability distributions, and interval numbers, and analyze the effects of uncertainties as well as their interactions on modeling outputs. It is applied to plan water quality management in the Xiangxihe watershed. Results reveal that a lower probability of satisfying the objective function (θ) as well as a higher probability of violating environmental constraints (q

Indexed as

Models, TheoreticalUncertaintyWater QualityRiskWaterWater SupplyWaterMultiple interactionsMultiple uncertaintiesOptimizationRiskWater quality management

Identifiers

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.