{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T22:30:25Z","timestamp":1742941825557,"version":"3.40.3"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030493356"},{"type":"electronic","value":"9783030493363"}],"license":[{"start":{"date-parts":[[2020,8,13]],"date-time":"2020-08-13T00:00:00Z","timestamp":1597276800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,8,13]],"date-time":"2020-08-13T00:00:00Z","timestamp":1597276800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-49336-3_16","type":"book-chapter","created":{"date-parts":[[2020,8,12]],"date-time":"2020-08-12T12:05:28Z","timestamp":1597233928000},"page":"156-164","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Data Clustering Using Environmental Adaptation Method"],"prefix":"10.1007","author":[{"given":"Tribhuvan","family":"Singh","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Krishn Kumar","family":"Mishra","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Ranvijay","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,8,13]]},"reference":[{"key":"16_CR1","volume-title":"Introduction to Machine Learning","author":"E Alpaydin","year":"2014","unstructured":"Alpaydin, E.: Introduction to Machine Learning. MIT press, Cambridge (2014)"},{"issue":"2","key":"16_CR2","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1016\/j.compbiomed.2007.09.002","volume":"38","author":"W Halberstadt","year":"2008","unstructured":"Halberstadt, W., Douglas, T.S.: Fuzzy clustering to detect tuberculous meningitis-associated hyperdensity in CT images. Comput. Biol. Med. 38(2), 165\u2013170 (2008)","journal-title":"Comput. Biol. Med."},{"key":"16_CR3","volume-title":"Introduction to Data Mining","author":"PN Tan","year":"2018","unstructured":"Tan, P.N.: Introduction to Data Mining. Pearson Education India, Chennai (2018)"},{"key":"16_CR4","unstructured":"Chen, C.Y., Ye, F.: Particle swarm optimization algorithm and its application to clustering analysis. In: 2012 Proceedings of 17th Conference on Electrical Power Distribution, pp. 789\u2013794. IEEE (2012)"},{"issue":"3","key":"16_CR5","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1145\/331499.331504","volume":"31","author":"AK Jain","year":"1999","unstructured":"Jain, A.K., Murty, M.N., Flynn, P.J.: Data clustering: a review. ACM Comput. Surv. (CSUR) 31(3), 264\u2013323 (1999)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"16_CR6","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/j.patrec.2017.10.031","volume":"115","author":"N Kushwaha","year":"2018","unstructured":"Kushwaha, N., Pant, M., Kant, S., Jain, V.K.: Magnetic optimization algorithm for data clustering. Pattern Recogn. Lett. 115, 59\u201365 (2018)","journal-title":"Pattern Recogn. Lett."},{"key":"16_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.engappai.2016.11.003","volume":"61","author":"XH Han","year":"2017","unstructured":"Han, X.H., Quan, L., Xiong, X.Y., Almeter, M., Xiang, J., Lan, Y.: A novel data clustering algorithm based on modified gravitational search algorithm. Eng. Appl. Artif. Intell. 61, 1\u20137 (2017)","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"3","key":"16_CR8","doi-asserted-by":"publisher","first-page":"1569","DOI":"10.1016\/j.aej.2017.04.013","volume":"57","author":"AN Jadhav","year":"2018","unstructured":"Jadhav, A.N., Gomathi, N.: WGC: hybridization of exponential grey wolf optimizer with whale optimization for data clustering. Alex. Eng. J. 57(3), 1569\u20131584 (2018)","journal-title":"Alex. Eng. J."},{"key":"16_CR9","doi-asserted-by":"crossref","unstructured":"Singh, T., Shukla, A., Mishra, K.K.: Improved environmental adaption method with real parameter encoding for solving optimization problems. In: Advances in Computer and Computational Sciences, pp. 13\u201320. Springer, Cham (2018)","DOI":"10.1007\/978-981-10-3773-3_2"},{"issue":"8","key":"16_CR10","doi-asserted-by":"publisher","first-page":"651","DOI":"10.1016\/j.patrec.2009.09.011","volume":"31","author":"AK Jain","year":"2010","unstructured":"Jain, A.K.: Data clustering: 50 years beyond k-means. Pattern Recogn. Lett. 31(8), 651\u2013666 (2010)","journal-title":"Pattern Recogn. Lett."},{"issue":"2","key":"16_CR11","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1007\/s00521-015-1870-7","volume":"27","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili, S., Mirjalili, S.M., Hatamlou, A.: Multi-verse optimizer: a nature-inspired algorithm for global optimization. Neural Comput. Appl. 27(2), 495\u2013513 (2016)","journal-title":"Neural Comput. Appl."},{"key":"16_CR12","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1016\/j.advengsoft.2017.07.002","volume":"114","author":"S Mirjalili","year":"2017","unstructured":"Mirjalili, S., Gandomi, A.H., Mirjalili, S.Z., Saremi, S., Faris, H., Mirjalili, S.M.: Salp swarm algorithm: a bio-inspired optimizer for engineering design problems. Adv. Eng. Softw. 114, 163\u2013191 (2017)","journal-title":"Adv. Eng. Softw."},{"key":"16_CR13","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","volume":"69","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili, S., Mirjalili, S.M., Lewis, A.: Grey wolf optimizer. Adv. Eng. Softw. 69, 46\u201361 (2014)","journal-title":"Adv. Eng. Softw."},{"issue":"3","key":"16_CR14","doi-asserted-by":"publisher","first-page":"715","DOI":"10.1007\/s00500-018-3102-4","volume":"23","author":"S Arora","year":"2019","unstructured":"Arora, S., Singh, S.: Butterfly optimization algorithm: a novel approach for global optimization. Soft. Comput. 23(3), 715\u2013734 (2019)","journal-title":"Soft. Comput."},{"key":"16_CR15","unstructured":"Blake, C.L., Merz, C.J.: UCI repository of machine learning databases (1998)"}],"container-title":["Advances in Intelligent Systems and Computing","Hybrid Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-49336-3_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,12]],"date-time":"2020-08-12T22:04:59Z","timestamp":1597269899000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-49336-3_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,13]]},"ISBN":["9783030493356","9783030493363"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-49336-3_16","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2020,8,13]]},"assertion":[{"value":"13 August 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"HIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Hybrid Intelligent Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sehore","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 December 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 December 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"his2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.mirlabs.net\/his19\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}