Evidence map›Paper›PMID 36059409›Full record

ArticleComputational intelligence and neuroscience2022

Analysis of College Course Scheduling Problem Based on Ant Colony Algorithm.

Ruqun Ge, Jingyi Chen

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. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Ruqun GeHoHai University, Nanjing 211100, China.ORCID https://orcid.org/0000-0002-2139-9992
Jingyi ChenHoHai University, Nanjing 211100, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ant colony algorithm is a new evolutionary algorithm, which is gradually applied due to its easy robustness with other methods and excellent distributed computing mechanism. Currently, the application field of ant colony algorithm has been infiltrated by a single TSP problem. Ant colony algorithm moves the algorithm toward the optimal solution through the combination of positive feedback and negative feedback. This paper briefly analyzes the basic characteristics of the basic idea and principle of the ant colony algorithm to apply it to the ant colony problem. Abstract the course scheduling problem, transform the course arrangement problem into the maximum matching problem of solving the bipartite diagram, and discharge the high-quality curriculum that basically meet the needs.

Indexed as

AlgorithmsHumansUniversities

Identifiers

PMID36059409
PMCPMC9436534

What OpenQuestion holds

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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.