Evidence map›Paper›PMID 36320783›Full record

ArticleModeling earth systems and environment2023

Modeling air pollution by integrating ANFIS and metaheuristic algorithms.

Aynur Yonar, Harun Yonar

Abstract read
In one paragraph

Article in Modeling earth systems and environment, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Improving PMScientific reports · 2023
    Article
  5. 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

2 authors.

Aynur YonarKonya, Turkey Faculty of Science, Department of Statistics, Selçuk University.ORCID 0000-0003-1681-9398
Harun YonarKonya, Turkey Faculty of Veterinary Medicine, Department of Biostatistics, Selçuk University.ORCID 0000-0003-1574-3993

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Air pollution is increasing for many reasons, such as the crowding of cities, the failure of planning to consider the benefit of society and nature, and the non-implementation of environmental legislation. In the recent era, the impacts of air pollution on human health and the ecosystem have become a primary global concern. Thus, the prediction of air pollution is a crucial issue. ANFIS is an artificial intelligence technique consisting of artificial neural networks and fuzzy inference systems, and it is widely used in estimating studies. To obtain effective results with ANFIS, the training process, which includes optimizing its premise and consequent parameters, is very important. In this study, ANFIS training has been performed using three popular metaheuristic methods: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Differential Evolution (DE) for modeling air pollution. Various air pollution parameters which are particular matters: PM

Indexed as

Air pollutionANFISArtificial intelligenceMetaheuristics

Identifiers

PMID36320783
PMCPMC9613450

What OpenQuestion holds

Textmetadata
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.