{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T17:00:42Z","timestamp":1781110842643,"version":"3.54.1"},"reference-count":40,"publisher":"IGI Global Scientific Publishing","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,7,1]]},"abstract":"<p>In this article, fuzzy logic and gravitational search algorithms have been amalgamated and explored for feature selection in the automated prediction of diseases. The gravitational search algorithm has been used for search optimization while fuzzy logic had been used for its parameter tuning. Feature selection has been considered as a dual objective problem in the article, i.e. selecting minimum number of features without compromising the accuracy of classification, which is performed using K-Nearest Neighbour classifier. The improved algorithm has been tested with various publicly available medical datasets to analyse its effectiveness. The results indicate that the approach not only reduces the feature set by an average of 67.66% but also increases the accuracy by an average of 12%. Further, the results have also been compared with the prior work wherein the feature selection has been done using other evolutionary techniques. It is observed that the proposed approach is able to generate better results in most of the cases.<\/p>","DOI":"10.4018\/ijsir.2020070106","type":"journal-article","created":{"date-parts":[[2020,5,19]],"date-time":"2020-05-19T11:50:58Z","timestamp":1589889058000},"page":"89-103","source":"Crossref","is-referenced-by-count":0,"title":["Fuzzy Optimized Gravitational Search Algorithm for Disease Prediction"],"prefix":"10.4018","volume":"11","author":[{"given":"Utkarsh","family":"Yadav","sequence":"first","affiliation":[{"name":"CRED, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Twishi","family":"Tyagi","sequence":"additional","affiliation":[{"name":"Samsung R&D, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sushama","family":"Nagpal","sequence":"additional","affiliation":[{"name":"Netaji Subhas University of Technology, Delhi, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJSIR.2020070106-0","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-015-2103-9"},{"key":"IJSIR.2020070106-1","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511569920.007"},{"key":"IJSIR.2020070106-2","doi-asserted-by":"crossref","unstructured":"Askari, H., & Zahiri, S. (2011). Data Classification Using Fuzzy-GSA. Proceedings of the 1st International eConference on Computer and Knowledge Engineering (pp. 6\u201311). Academic Press.","DOI":"10.1109\/ICCKE.2011.6413315"},{"issue":"4","key":"IJSIR.2020070106-3","first-page":"473","article-title":"Firefly based feature selection approach.","volume":"8","author":"H.Banati","year":"2011","journal-title":"International Journal of Computer Science Issues"},{"key":"IJSIR.2020070106-4","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2013.11.024"},{"key":"IJSIR.2020070106-5","doi-asserted-by":"publisher","DOI":"10.1109\/CSB.2003.1227396"},{"key":"IJSIR.2020070106-6","doi-asserted-by":"crossref","unstructured":"Farsangi, S. E., Rashedi, E., & Farsangi, M. M. (2017). Multi-objective VAr Planning Using Fuzzy-GSA. Proceedings of the2nd Conference on Swarm Intelligence and Evolutionary Computation (pp. 147-151). Academic Press.","DOI":"10.1109\/CSIEC.2017.7940180"},{"key":"IJSIR.2020070106-7","unstructured":"Fister, I., Yang, X. S., Brest, J., and Fister, D. (2013). A brief review of nature-inspired algorithms for optimization. Elektroteh. Vestnik [Electrotechnical Rev.], 80(3), 116\u2013122."},{"key":"IJSIR.2020070106-8","doi-asserted-by":"publisher","DOI":"10.4018\/978-1-4666-7258-1.ch020"},{"key":"IJSIR.2020070106-9","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijepes.2013.02.022"},{"key":"IJSIR.2020070106-10","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-016-2385-6"},{"issue":"1","key":"IJSIR.2020070106-11","first-page":"32","article-title":"A new algorithm based on the cuckoo search with dynamic adaptation of parameters using Fuzzy systems.","volume":"1","author":"M.Guerrero","year":"2018","journal-title":"Journal of Universal Mathematics"},{"key":"IJSIR.2020070106-12","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2011.11.020"},{"issue":"2","key":"IJSIR.2020070106-13","first-page":"727","article-title":"A New Hybrid Feature Selection Method Based on Association Rules and Pca for Detection of Breast Cancer.","volume":"9","author":"O.Inan","year":"2013","journal-title":"International Journal of Innovative Computing, Information, & Control"},{"key":"IJSIR.2020070106-14","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2012.01.011"},{"key":"IJSIR.2020070106-15","author":"N.Kokash","year":"2005","journal-title":"An introduction to heuristic algorithms"},{"key":"IJSIR.2020070106-16","doi-asserted-by":"publisher","DOI":"10.1016\/j.enconman.2010.07.012"},{"key":"IJSIR.2020070106-17","doi-asserted-by":"publisher","DOI":"10.1109\/IADCC.2015.7154727"},{"key":"IJSIR.2020070106-18","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2017.09.133"},{"key":"IJSIR.2020070106-19","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2903137"},{"key":"IJSIR.2020070106-20","doi-asserted-by":"publisher","DOI":"10.1109\/NaBIC.2013.6617875"},{"key":"IJSIR.2020070106-21","doi-asserted-by":"publisher","DOI":"10.1109\/SIS.2014.7011780"},{"key":"IJSIR.2020070106-22","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2018.10.025"},{"key":"IJSIR.2020070106-23","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2011.5946916"},{"key":"IJSIR.2020070106-24","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2009.03.004"},{"key":"IJSIR.2020070106-25","doi-asserted-by":"publisher","DOI":"10.1007\/s11047-009-9175-3"},{"key":"IJSIR.2020070106-26","doi-asserted-by":"publisher","DOI":"10.1142\/S021812661750061X"},{"key":"IJSIR.2020070106-27","doi-asserted-by":"publisher","DOI":"10.4018\/IJFSA.2017040102"},{"key":"IJSIR.2020070106-28","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1007\/978-981-10-0308-0_3","article-title":"Computational Intelligence Approach for Prediction of Breast Cancer using Particle Swarm Optimization: A Comparative Study of the Results with Reduced Set of Attributes","author":"K.Satishkumar","year":"2016","journal-title":"Computational Intelligence Techniques in Health Care"},{"key":"IJSIR.2020070106-29","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2015.10.005"},{"key":"IJSIR.2020070106-30","doi-asserted-by":"publisher","DOI":"10.1109\/CEC.2013.6557685"},{"key":"IJSIR.2020070106-31","doi-asserted-by":"publisher","DOI":"10.1155\/2013\/419187"},{"key":"IJSIR.2020070106-32","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2014.04.015"},{"key":"IJSIR.2020070106-33","doi-asserted-by":"publisher","DOI":"10.1142\/S1469026814500096"},{"key":"IJSIR.2020070106-34","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2015.2504420"},{"key":"IJSIR.2020070106-35","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2012.2227469"},{"key":"IJSIR.2020070106-36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-25948-0_31"},{"key":"IJSIR.2020070106-37","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1007\/978-1-4615-5725-8_8","article-title":"Feature subset selection using a genetic algorithm","author":"J.Yang","year":"1998","journal-title":"Feature extraction, construction and selection"},{"key":"IJSIR.2020070106-38","unstructured":"Yang, Y., & Pedersen, J. O. (1997). A comparative study on feature selection in text categorization. Proceedings of the Fourteenth International Conference on Machine Learning ICML \u201997 (pp. 412\u2013420). Academic Press."},{"key":"IJSIR.2020070106-39","unstructured":"Zahiri, S.H. (2012). Fuzzy gravitational search algorithm an approach for data mining. Iranian journal of fuzzy systems, 9(1), 21-37."}],"container-title":["International Journal of Swarm Intelligence Research"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=255711","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,6]],"date-time":"2022-05-06T14:47:13Z","timestamp":1651848433000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/IJSIR.2020070106"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2020,7,1]]},"references-count":40,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2020,7]]}},"URL":"https:\/\/doi.org\/10.4018\/ijsir.2020070106","relation":{},"ISSN":["1947-9263","1947-9271"],"issn-type":[{"value":"1947-9263","type":"print"},{"value":"1947-9271","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,7,1]]}}}