Evidence map›Paper›PMID 36981330›Full record

ArticleEntropy (Basel, Switzerland)2023

Decision-Making Teaching Practice Based on the Maximum Entropy Method in a Water Engineering Economics Course.

Runjuan Zhou, Yingke Sun, Shuai Shao, Kuo Zhang, Ming Zhang

Full text read
In one paragraph

Article in Entropy (Basel, Switzerland), 2023. 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

5 authors.

Runjuan ZhouSchool of Chemical and Environmental Engineering, Anhui Polytechnic University, Wuhu 241000, China.ORCID 0000-0003-0999-3638
Yingke SunSchool of Chemical and Environmental Engineering, Anhui Polytechnic University, Wuhu 241000, China.
Shuai ShaoSchool of Chemical and Environmental Engineering, Anhui Polytechnic University, Wuhu 241000, China.
Kuo ZhangSchool of Chemical and Environmental Engineering, Anhui Polytechnic University, Wuhu 241000, China.
Ming ZhangSchool of Civil Engineering, Anhui Polytechnic University, Wuhu 241000, China.ORCID 0000-0002-7384-3362

Funding

Anhui Provincial Natural Science Foundation 2208085QE176, 2008085ME159Key project of the University Natural Science Research Project of Anhui Province KJ2021A0505Quality Engineering Project of Anhui Polytechnic University 2021jyxm55the Science and Technology Project of Wuhu City 2022jc15
6 · The paper itself

Abstract

The purpose of this paper is to put forward a decision model with wide applicability and differentiated decision scheme scores so as to improve the ability of students to learn during a water engineering economics course. The main novelty and contributions of this paper are that the multi-attribute decision-making method proposed is more objective and does not require rich subjective experience from decision-makers in the application process, which is particularly suitable for beginners who are learning in a water engineering economics course. The method involves standardizing each index value of the decision scheme first, constructing the objective function of maximum entropy distribution, calculating the weight of each index by the genetic algorithm, and finally ranking the pros and cons of the scheme according to the score of each scheme. The example results of three water engineering scheme decisions show that the maximum entropy model proposed in this paper can achieve reasonable decision results, and there is a large degree of differentiation between the decision schemes. The proposed scheme, a decision maximum entropy model, has wide applicability, can improve the rationality of the decisions made regarding water engineering schemes, and can be popularized and applied when teaching decision-making in water engineering economics courses.

Indexed as

decision-makinggenetic algorithmmaximum entropyteachingwater engineering economics

Identifiers

PMID36981330
PMCPMC10047882

What OpenQuestion holds

Textfull text, public
LicenceCC BY
Read underepoch 390

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.