Evidence map›Paper›PMID 36120700›Full record

ArticleComputational intelligence and neuroscience2022

A Closed-Loop Method for Multiperiod Intelligent Information Processing with Cost Constraints under the Fuzzy Environment.

Ming Fu, Lifang Wang, Xueneng Cao, Bingyun Zheng, Xianxian Zhou, Shishu Yin

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. 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.

Ming FuSchool of Management Science and Engineering, Anhui University of Finance & Economics, Bengbu 233030, Anhui, China.ORCID https://orcid.org/0000-0002-1957-5563
Lifang WangSchool of International Trade and Economics, Anhui University of Finance & Economics, Bengbu 233030, Anhui, China.ORCID https://orcid.org/0000-0001-5052-4943
Xueneng CaoSchool of Management Science and Engineering, Anhui University of Finance & Economics, Bengbu 233030, Anhui, China.ORCID https://orcid.org/0000-0002-3569-1097
Bingyun ZhengSchool of Management Science and Engineering, Anhui University of Finance & Economics, Bengbu 233030, Anhui, China.ORCID https://orcid.org/0000-0001-5133-1801
Xianxian ZhouSchool of Management Science and Engineering, Anhui University of Finance & Economics, Bengbu 233030, Anhui, China.ORCID https://orcid.org/0000-0003-3469-0313
Shishu YinSchool of Management Science and Engineering, Anhui University of Finance & Economics, Bengbu 233030, Anhui, China.ORCID https://orcid.org/0000-0002-5397-4170

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

From trivial matters in life to major scientific projects related to the fate of mankind, decision-making is everywhere. Whether high-quality decisions can be made often directly affects the development of affairs, especially when sudden disasters occur. As the basis of decision-making, data are crucial. The continuously probabilistic linguistic set, a data structure of the fuzzy mathematics, is selected in the paper to collect original data after careful comparisons, because this data structure can fully consider the hesitation of decision-makers and the fuzziness of complex problems. Although all alternatives are costly, the costs of different alternatives still vary greatly; obviously, the low-cost alternative is better than others when the same predetermined goal can be achieved, which is one of the research objectives and characteristics of this paper. Different from other researchers who only take the cost as one of the decision-making indicators, the algorithm proposed in the paper pays much more attention on the cost reduction. When dealing with an emergency, it is often difficult to solve the problem by taking measures only once; usually, multiple rounds of measures are needed. Each round of decision-making has both connections and differences, and the multiround decision-making model is proposed and built in the paper. Different from traditional linear structures, the model mainly adopts the closed-loop structure, which divides the whole process into multiple sub-decision-making points, the severities measured at the current time point will be compared with the values estimated at the latter time point, and then, the differences will be input into the system, the corresponding automatic adjustment modules will be activated immediately according to the values. The accuracy of the system can be verified and adjusted in time by the closed-loop control module. Finally, several experiments are carried out and the results show that the algorithm proposed in the paper is more effective and the cost is lower.

Indexed as

Decision MakingFuzzy LogicAlgorithmsLinguistics

Identifiers

PMID36120700
PMCPMC9473872

What OpenQuestion holds

Textmetadata
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.