Evidence map›Paper›PMID 33774789›Full record

ArticleEnvironmental science and pollution research international2021

Real-time location algorithms of drinking water pollution sources based on domain knowledge.

Xuesong Yan, Zhengchen Zhou, Chengyu Hu, Wenyin Gong

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Article in Environmental science and pollution research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Environmental concerns and pollution control in the context of developing countries.Environmental science and pollution research international · 2021
    Article
4 · The record

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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

4 authors.

Xuesong YanSchool of Computer Science, China University of Geosciences, Wuhan, 430074, China.
Zhengchen ZhouSchool of Computer Science, China University of Geosciences, Wuhan, 430074, China.
Chengyu HuSchool of Computer Science, China University of Geosciences, Wuhan, 430074, China. huchengyu@cug.edu.cn.
Wenyin GongSchool of Computer Science, China University of Geosciences, Wuhan, 430074, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The real-time location of pollution sources is the process of inverting pollution sources based on the dynamic optimization model constructed by the time-varying pollution concentration detected by the water quality sensor. Due to the vast quantities of the water supply networks, the water quality sensors will only be placed on critical nodes, resulting in multiple solutions. However, the increased monitoring data enhances the uniqueness of the solution. Combined with the real-time location of pollution sources, this work proposed a multi-strategy dynamic multi-mode optimization algorithm based on domain knowledge, which could guide the population search and avoid trapped into local optimal. The merging mechanism was used to keep the diversity of the population and prevent sub-population clustering on the same optimal solution. The simulation results showed that the algorithm could effectively solve the real-time location problem of pollution sources in different pipe networks and pollution scenarios.

Indexed as

Water PollutionWater SupplyAlgorithmsComputer SimulationWater QualityDomain knowledgeDrinking water qualityDynamic multi-mode optimizationMulti-strategyPollution sourcesReal-time location algorithms

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Registered trials

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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.