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Dynamic system models are complicated to infer due to the underlying large search space and high computational cost for simulation and verification. In this research we aim to infer both the structure and parameters of a dynamic system simultaneously by particle swarm optimization (PSO) improved by efficient stratified sampling approaches. More specifically, we enhance PSO with two modern stratified sampling techniques, i.e., Latin hyper cube sampling (LHS) and Latin hyper cube multi dimensional uniformity (LHSMDU). We propose and evaluate two novel swarm-inspired algorithms, LHS-PSO and LHSMDU-PSO, which can be used particularly to learn the model structure and parameters of complex dynamic systems efficiently. The performance of LHS-PSO and LHSMDU-PSO is further compared with the original PSO and genetic algorithm (GA). We chose real-world cancer biological model called Kinetochores to asses the learning performance of LHSMDU-PSO and LHS-PSO in comparison with GA and the original PSO. The experimental results show that LHSMDU-PSO can find promising models with reasonable parameters and structure, and it outperforms LHS-PSO, PSO, and GA in our experiments.<\/jats:p>","DOI":"10.1007\/s12293-020-00306-5","type":"journal-article","created":{"date-parts":[[2020,7,29]],"date-time":"2020-07-29T06:03:44Z","timestamp":1596002624000},"page":"267-282","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Inferring structure and parameters of dynamic system models simultaneously using swarm intelligence approaches"],"prefix":"10.1007","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6383-4323","authenticated-orcid":false,"given":"Muhammad","family":"Usman","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Pang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"George M.","family":"Coghill","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,7,29]]},"reference":[{"issue":"3","key":"306_CR1","doi-asserted-by":"publisher","first-page":"033902","DOI":"10.1063\/1.1953147","volume":"15","author":"P Melby","year":"2005","unstructured":"Melby P, Weber N, H\u00fcbler A (2005) Dynamics of self-adjusting systems with noise. 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Muhammad Usman, Wei Pang and George M.Coghill declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}