Mixed Forecast of Air Quality Index with a Bibranch Parallel Architecture Considering Seasonal Heterogeneity.

Huibin Zeng, Ying Liu, Hongbin Dai, Xue Zhao, Ning Tian

Abstract read

In one paragraph

Article in Entropy (Basel, Switzerland), 2026. 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

5 authors.

Huibin ZengSchool of Economics and Management, Chongqing Normal University, Chongqing 401331, China.ORCID 0000-0001-5499-9217

Ying LiuSchool of Economics and Management, Chongqing Normal University, Chongqing 401331, China.

Hongbin DaiCollege of Computer and Information Science, Chongqing Normal University, Chongqing 401331, China.

Xue ZhaoSchool of Management, Xi'an University of Architecture and Technology, Xi'an 710055, China.

Ning TianSchool of Management, Xi'an University of Architecture and Technology, Xi'an 710055, China.

Funding

2025 Chongqing Social Science Popularization Project 2025KP026Chongqing Natural Science Foundation CSTB2025NSCQ-GPX0990Chongqing Social Science Planning Doctoral Project 2024BS083Foundation Program of Chongqing Normal University 24XWB042Science and Technology Research Program of Chongqing Municipal Education Commission KJQN202500503,KJQN202500502

6 · The paper itself

Abstract

Accurate prediction of the air quality index (AQI) is crucial for understanding urban pollution dynamics and protecting public health. This study proposes a dual-branch fusion framework (CL-XGB-Season) to address seasonal heterogeneity in AQI prediction by integrating temporal dynamic features and static patterns. The CNN-LSTM branch captures short-term temporal fluctuations, while a seasonally split XGBoost branch fits long-term static patterns via independent submodels for spring, summer, autumn, and winter. SHAP-based interpretability analysis revealed the dominant drivers across different seasons: the "temperature × O

Indexed as

AQI predictiondual-branch architectureinterpretabilitylearnable fusion layerSHAP

Identifiers

PMID42072544

DOI10.3390/e28040419

PMCPMC13114637

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

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.