{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:40:42Z","timestamp":1777704042475,"version":"3.51.4"},"reference-count":15,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2019,11,5]],"date-time":"2019-11-05T00:00:00Z","timestamp":1572912000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2020,2,6]]},"abstract":"<jats:p>In order to better solve the problem of gas outburst prediction, based on the in-depth study of ant colony algorithm, the ant colony clustering algorithm is improved, and the population classification and ant sensory perception characteristics are applied to make the ant colony the most likely to find. The optimal solution effectively avoids the possibility of local optimization, improves the global optimization performance and convergence speed of the algorithm, and reduces the influence of human subjective factors. Based on the prominent basic speech and actual working conditions, the paper selects five indexes of gas velocity, initial gas velocity, gas content, gas pressure and coal firmness coefficient as clustering attributes, and uses ant colony clustering algorithm to judge outstanding the state of occurrence. The paper uses MATLAB programming language to write a coal and gas outburst prediction program based on improved ant colony clustering algorithm, and predicts a coal mine. The final result is the same as the actual observation.<\/jats:p>","DOI":"10.3233\/jifs-179501","type":"journal-article","created":{"date-parts":[[2019,11,8]],"date-time":"2019-11-08T13:28:12Z","timestamp":1573219692000},"page":"1381-1390","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["Application of ant colony clustering algorithm in coal mine gas accident analysis under the background of big data research"],"prefix":"10.1177","volume":"38","author":[{"given":"Kang","family":"Yu","sequence":"first","affiliation":[{"name":"Department of Safety Engineering, Heilongjiang University of Science and Technology, Harbin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wu","family":"Qiang","sequence":"additional","affiliation":[{"name":"Department of Safety Engineering, Heilongjiang University of Science and Technology, Harbin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2019,11,5]]},"reference":[{"issue":"3","key":"e_1_3_2_2_2","doi-asserted-by":"crossref","first-page":"1625","DOI":"10.1007\/s11069-014-1561-1","article-title":"Forecasting of rockbursts in deep underground engineering based on abstraction ant colony clustering algorithm","volume":"76","author":"Gao","year":"2015","unstructured":"Gao and Wei, Forecasting of rockbursts in deep underground engineering based on abstraction ant colony clustering algorithm, Natural Hazards 76(3) (2015), 1625\u20131649.","journal-title":"Natural Hazards"},{"issue":"10","key":"e_1_3_2_3_2","doi-asserted-by":"crossref","first-page":"3223","DOI":"10.1166\/jctn.2015.4105","article-title":"Association rules mining algorithm using sharing mechanism niche leaping ant colony based on apriori algorithm","volume":"12","author":"Wang Y.","year":"2015","unstructured":"WangY., XuY., LiG. and WangH., Association rules mining algorithm using sharing mechanism niche leaping ant colony based on apriori algorithm, Journal of Computational & Theoretical Nanoscience 12(10) (2015), 3223\u20133231.","journal-title":"Journal of Computational & Theoretical Nanoscience"},{"issue":"6","key":"e_1_3_2_4_2","doi-asserted-by":"crossref","first-page":"997","DOI":"10.1080\/17415977.2014.973872","article-title":"Improved ant colony algorithm for parameter estimation on the bisq model","volume":"23","author":"Zhang X.-M.","year":"2015","unstructured":"ZhangX.-M., SongW. and FengW.-w., Improved ant colony algorithm for parameter estimation on the bisq model, Inverse Problems in Science & Engineering 23(6) (2015), 997\u20131010.","journal-title":"Inverse Problems in Science & Engineering"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1063\/1.5085430"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11277-018-5415-0"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.5004\/dwt.2018.22362"},{"issue":"19","key":"e_1_3_2_8_2","first-page":"1","article-title":"Ant colony classification mining algorithm based on pheromone attraction and exclusion","volume":"21","author":"Yang L.","year":"2016","unstructured":"YangL., LiK., ZhangW. and KeZ., Ant colony classification mining algorithm based on pheromone attraction and exclusion, Soft Computing 21(19) (2016), 1\u201313.","journal-title":"Soft Computing"},{"issue":"11","key":"e_1_3_2_9_2","first-page":"1","article-title":"An improved ant colony algorithm for robot path planning","volume":"1","author":"Liu J.","year":"2016","unstructured":"LiuJ., YangJ., LiuH., TianX. and GaoM., An improved ant colony algorithm for robot path planning, Soft Computing 1(11) (2016), 1\u201311.","journal-title":"Soft Computing"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11721-015-0112-z"},{"issue":"6","key":"e_1_3_2_11_2","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1049\/iet-spr.2014.0529","article-title":"Ant-colony algorithm with interference cancellation for cooperative transmission","volume":"10","author":"Abdul Aziz N.H.","year":"2016","unstructured":"Abdul AzizN.H., Ab GhaniH., SyahaliS. and HamzahM.H., Ant-colony algorithm with interference cancellation for cooperative transmission, Iet Signal Processing 10(6) (2016), 603\u2013610.","journal-title":"Iet Signal Processing"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10773-017-3619-9"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2019.01.115"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijinfomgt.2018.12.001"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1002\/dac.3953"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11554-019-00879-6"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/JIFS-179501","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.3233\/JIFS-179501","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/JIFS-179501","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:40:15Z","timestamp":1777455615000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/JIFS-179501"}},"subtitle":[],"editor":[{"given":"Mohamed","family":"Elhoseny","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]},{"given":"X.","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2019,11,5]]},"references-count":15,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2020,2,6]]}},"alternative-id":["10.3233\/JIFS-179501"],"URL":"https:\/\/doi.org\/10.3233\/jifs-179501","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,11,5]]}}}