{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T23:00:29Z","timestamp":1773615629401,"version":"3.50.1"},"reference-count":18,"publisher":"Allerton Press","issue":"4","license":[{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Aut. Control Comp. Sci."],"published-print":{"date-parts":[[2021,7]]},"DOI":"10.3103\/s0146411621040040","type":"journal-article","created":{"date-parts":[[2021,9,3]],"date-time":"2021-09-03T09:01:43Z","timestamp":1630659703000},"page":"346-357","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["The Artificial Fish Swarm Algorithm Optimized by RNA Computing"],"prefix":"10.3103","volume":"55","author":[{"family":"Liyi Zhang","sequence":"first","affiliation":[]},{"given":"Mingyue","family":"Fu","sequence":"additional","affiliation":[]},{"given":"Teng","family":"Fei","sequence":"additional","affiliation":[]},{"given":"Jingyi","family":"Liang","sequence":"additional","affiliation":[]}],"member":"1627","published-online":{"date-parts":[[2021,9,2]]},"reference":[{"key":"7358_CR1","first-page":"32","volume":"22","author":"Xiaolei Li","year":"2002","unstructured":"Li Xiaolei, Shao Zhijiang, and Qian Jixin, An optimizing method based on autonomous animals: Fish swarm algorithm, Syst. Eng.: Theory Pract., 2002, vol. 22, no. 11, pp. 32\u201338.","journal-title":"Syst. Eng.: Theory Pract."},{"key":"7358_CR2","first-page":"1","volume":"8","author":"Xiao-lei Li","year":"2003","unstructured":"Li Xiao-lei and Qian Ji-xin, Studies on artificial fish swarm optimization algorithm based on decomposition and coordination techniques, J. Circuits Syst., 2003, vol. 8, no. 1, pp. 1\u20136.","journal-title":"J. Circuits Syst."},{"key":"7358_CR3","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1016\/j.knosys.2010.11.001","volume":"24","author":"W. Shen","year":"2011","unstructured":"Shen, W., Guo, X., Wu, C., and Wu, D., Forecasting stock indices using radial basis function neural networks optimized by artificial fish swarm algorithm, Knowl.-Based Syst., 2011, vol. 24, no. 3, pp. 378\u2013385.","journal-title":"Knowl.-Based Syst."},{"key":"7358_CR4","first-page":"281","volume":"44","author":"Dong-lin Liu","year":"2017","unstructured":"Liu Dong-lin and Li Le-le, New improved artificial fish swarm algorithm, Comput. Sci., 2017, vol. 44, no. 4, pp.\u00a0281\u2013287.","journal-title":"Comput. Sci."},{"key":"7358_CR5","unstructured":"Li Zhen-hao, Li Ying-na, Zhang Chang-sheng, and Li Chuan, Ultrasonic localization method of partial discharge based on immune memory AFSA algorithm, Transducer Microsyst. Technol., 2017, vol. 36, no. 3, pp. 73\u201375, 83."},{"key":"7358_CR6","unstructured":"Liu Quanming, He Jianqiang, and Zhang Hu, Improved genetic artificial fish swarm optimization algorithm based on the cultural algorithm, J. Shanxi Univ. (Nat. Sci. Ed.), 2018, vol. 41, no. 2, pp. 308\u2013316."},{"key":"7358_CR7","first-page":"53","volume":"35","author":"Jian-bo Xu","year":"2018","unstructured":"Xu Jian-bo, Dai Yue-ming, and Yan Da-hu, Double adaptive artificial fish swarm optimization algorithm, Microelectron. Comput., 2018, vol. 35, no. 4, pp. 53\u201357.","journal-title":"Microelectron. Comput."},{"key":"7358_CR8","first-page":"232","volume":"35","author":"Li Jun","year":"2018","unstructured":"Li Jun and Liang Xi-ming, Artificial fish swarm algorithm convergence speed improvement optimization simulation, Comput. Simul., 2018, vol. 35, no. 1, pp. 232\u2013238.","journal-title":"Comput. Simul."},{"key":"7358_CR9","first-page":"179","volume":"54","author":"Lingbo Yao","year":"2018","unstructured":"Yao Lingbo, Dai Yueming, and Wang Yan, Opposite adaptive and Gauss mutation artificial fish swarm algorithm, Comput. Eng. Appl., 2018, vol. 54, no. 1, pp. 179\u2013185.","journal-title":"Comput. Eng. Appl."},{"key":"7358_CR10","unstructured":"Jia Yimin, Shi Liping, and Yan Xin, Transformer fault diagnosis based on wavelet neural network with improved artificial fish-swarm algorithm, J. Henan Polytech. Univ. (Natl. Sci.), 2019, vol. 38, no. 2, pp. 103\u2013109."},{"key":"7358_CR11","unstructured":"Zhang Xiao-bo, Peng Jin-ye, and Liu Tian, Adaptive visual field and step length of chaotic artificial fish swarm algorithm, Microelectron. Comput., 2019, vol. 36, no. 6, pp. 5\u20139, 14."},{"key":"7358_CR12","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1016\/S0303-2647(99)00030-1","volume":"52","author":"A.R. Cukras","year":"1999","unstructured":"Cukras, A.R., Faulhammer, D., Lipton, R.J., and Landweber, L.F., Chess games: A model for RNA based computation, BioSystems, 1999, vol. 52, no. 1, pp. 35\u201345.","journal-title":"BioSystems"},{"key":"7358_CR13","doi-asserted-by":"publisher","first-page":"1385","DOI":"10.1073\/pnas.97.4.1385","volume":"97","author":"D. Faulhammer","year":"2000","unstructured":"Faulhammer, D., Cukras, A.R., Lipton, R.J., and Landweber, L.F., Molecular computation: RNA solutions to chess problems, Proc. Natl. Acad. Sci. U. S. A., 2000, vol. 97, no. 4, pp. 1385\u20131389.","journal-title":"Proc. Natl. Acad. Sci. U. S. A."},{"key":"7358_CR14","first-page":"461","volume":"19","author":"Shu-chao Li","year":"2003","unstructured":"Li Shu-chao, Xu Jin, and Pan Lin-qiang, Operational rules for digital coding of RNA sequences based on DNA computing in high dimensional space, Bull. Sci. Technol., 2003, vol. 19, no. 6, pp. 461\u2013465.","journal-title":"Bull. Sci. Technol."},{"key":"7358_CR15","first-page":"50","volume":"45","author":"Lin Chun","year":"2009","unstructured":"Lin Chun, Li An-gui, and Liu Qin-sheng, Genetic fuzzy C-means algorithm adding in computing of RNA, Comput. Eng. Appl., 2009, vol. 45, no. 24, pp. 50\u201352.","journal-title":"Comput. Eng. Appl."},{"key":"7358_CR16","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1016\/j.cej.2010.12.036","volume":"167","author":"Kangtai Wang","year":"2010","unstructured":"Wang Kangtai and Wang Ning, A protein inspired RNA genetic algorithm for parameter estimation in hydrocracking of heavy oil, Chem. Eng. J., 2010, vol. 167, no. 1, pp. 228\u2013239.","journal-title":"Chem. Eng. J."},{"key":"7358_CR17","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1007\/s00366-002-0248-5","volume":"39","author":"Shuchao Li","year":"2003","unstructured":"Li Shuchao and Xu Jin, Digital coding for RNA based on DNA computing, Comput. Eng. Appl., 2003, vol. 39, no. 5, pp. 45\u201347.","journal-title":"Comput. Eng. Appl."},{"key":"7358_CR18","unstructured":"Fei Teng, Zhang Liyi, Bai Yu, and Chen Lei, Improved artificial fish swarm algorithm based on DNA, J. Tianjin Univ. (Sci. Technol.), 2016, vol. 49, no. 6, pp. 581\u2013588."}],"container-title":["Automatic Control and Computer Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.3103\/S0146411621040040.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.3103\/S0146411621040040","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.3103\/S0146411621040040.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T22:02:31Z","timestamp":1773612151000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.3103\/S0146411621040040"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7]]},"references-count":18,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2021,7]]}},"alternative-id":["7358"],"URL":"https:\/\/doi.org\/10.3103\/s0146411621040040","relation":{},"ISSN":["0146-4116","1558-108X"],"issn-type":[{"value":"0146-4116","type":"print"},{"value":"1558-108X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7]]},"assertion":[{"value":"27 August 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 December 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 December 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 September 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no conflict of interest.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"CONFLICT OF INTEREST"}}]}}