{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T10:32:25Z","timestamp":1762079545675,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,12,9]],"date-time":"2022-12-09T00:00:00Z","timestamp":1670544000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Humanities and Social Sciences Project of the Ministry of Education of China","award":["61602202","BK20160428","20KJA520008","XYDXX-034"],"award-info":[{"award-number":["61602202","BK20160428","20KJA520008","XYDXX-034"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61602202","BK20160428","20KJA520008","XYDXX-034"],"award-info":[{"award-number":["61602202","BK20160428","20KJA520008","XYDXX-034"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["61602202","BK20160428","20KJA520008","XYDXX-034"],"award-info":[{"award-number":["61602202","BK20160428","20KJA520008","XYDXX-034"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Education Department of Jiangsu Province","award":["61602202","BK20160428","20KJA520008","XYDXX-034"],"award-info":[{"award-number":["61602202","BK20160428","20KJA520008","XYDXX-034"]}]},{"DOI":"10.13039\/501100010014","name":"The six talent peaks project in Jiangsu Province","doi-asserted-by":"publisher","award":["61602202","BK20160428","20KJA520008","XYDXX-034"],"award-info":[{"award-number":["61602202","BK20160428","20KJA520008","XYDXX-034"]}],"id":[{"id":"10.13039\/501100010014","id-type":"DOI","asserted-by":"publisher"}]},{"name":"China Scholarship Council","award":["61602202","BK20160428","20KJA520008","XYDXX-034"],"award-info":[{"award-number":["61602202","BK20160428","20KJA520008","XYDXX-034"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Air quality has a significant influence on people\u2019s health. Severe air pollution can cause respiratory diseases, while good air quality is beneficial to physical and mental health. Therefore, the prediction of air quality is very important. Since the concentration data of air pollutants are time series, their time characteristics should be considered in their prediction. However, the traditional neural network for time series prediction is limited by its own structure, which makes it very easy for it to fall into a local optimum during the training process. The empirical mode decomposition fuzzy forecast model for air quality, which is based on the extreme learning machine, is proposed in this paper. Empirical mode decomposition can analyze the changing trend of air quality well and obtain the changing trend of air quality under different time scales. According to the changing trend under different time scales, the extreme learning machine is used for fast training, and the corresponding prediction value is obtained. The adaptive fuzzy inference system is used for fitting to obtain the final air quality prediction result. The experimental results show that our model improves the accuracy of both short-term and long-term prediction by about 30% compared to other models, which indicates the remarkable efficacy of our approach. The research of this paper can provide the government with accurate future air quality information, which can take corresponding control measures in a targeted manner.<\/jats:p>","DOI":"10.3390\/e24121803","type":"journal-article","created":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T02:15:33Z","timestamp":1670811333000},"page":"1803","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["An Empirical Mode Decomposition Fuzzy Forecast Model for Air Quality"],"prefix":"10.3390","volume":"24","author":[{"given":"Wenxin","family":"Jiang","sequence":"first","affiliation":[{"name":"Faculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huai\u2019an 223003, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6185-2368","authenticated-orcid":false,"given":"Guochang","family":"Zhu","sequence":"additional","affiliation":[{"name":"Faculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huai\u2019an 223003, China"}]},{"given":"Yiyun","family":"Shen","sequence":"additional","affiliation":[{"name":"Faculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huai\u2019an 223003, China"}]},{"given":"Qian","family":"Xie","sequence":"additional","affiliation":[{"name":"Faculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huai\u2019an 223003, China"}]},{"given":"Min","family":"Ji","sequence":"additional","affiliation":[{"name":"Faculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huai\u2019an 223003, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7204-9346","authenticated-orcid":false,"given":"Yongtao","family":"Yu","sequence":"additional","affiliation":[{"name":"Faculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huai\u2019an 223003, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.inffus.2016.11.015","article-title":"Air quality data clustering using EPLS method","volume":"36","author":"Chen","year":"2017","journal-title":"Inf. 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