Evidence map›Paper›PMID 33973115›Full record

ArticleEnvironmental science and pollution research international2021

Application of interval-valued Pythagorean fuzzy VIKOR approach for petroleum sludge treatment technology evaluation and selection.

Weidong Wu, Peng Huang, Shuai Geng

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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

The trial behind it

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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

2 citing papers in PubMed.

  1. Article
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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

3 authors.

Weidong WuSchool of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu, 610500, China.
Peng HuangSchool of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu, 610500, China.
Shuai GengSchool of Management Engineering, Shandong Jianzhu University, Jinan, 250000, China. gengshuai1208@163.com.

Funding

Doctoral foundation of Shandong Jianzhu University X19003S
6 · The paper itself

Abstract

Petroleum sludge is produced during oilfield development and production and can negatively impact the production area and surrounding environment. With increasing attention to the environmental protection of oilfields, finding an energy-efficient, environmentally sound, cost-effective and socially acceptable sludge treatment method is crucial to the sustainable development of oil companies. However, there are several problems in the selection process: ① there is no effective index system for the evaluation of treatment technologies; ② there is data uncertainty and loss of information; ③ experts in the field often make one-sided decisions; and ④ the common decision models fail to balance the general effect and local dominance of a treatment technology. This study is innovative in the following aspects: ① a decision index system of petroleum sludge treatment technology is established; ② the interval-valued Pythagorean fuzzy set effectively managed data uncertainty and loss of information; ③ the redundancy-based expert weighting method is used to avoid one-sided decisions; and ④ using the basic ideas of the VIKOR model to balance the general effect and local dominance of a technology. Example verification proved the effectiveness of this method and a sensitivity analysis showed the results were reliable. Finally, this study compared the results obtained by three other similar methods, and comparative analysis demonstrated that this approach effectively evaluated and selected petroleum sludge treatment technologies. This study improves the rationality of petroleum sludge treatment technology selection and provides a necessary reference for the selection of treatment technology for other petroleum pollutants.

Indexed as

PetroleumSewageTechnologyUncertaintyPetroleumSewageInterval-valued Pythagorean fuzzy setPetroleum sludge treatmentRedundancy-based expert weighting methodTechnology selectionVIKOR

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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.