{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T22:03:08Z","timestamp":1757541788697,"version":"3.38.0"},"reference-count":34,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[1989,3,1]],"date-time":"1989-03-01T00:00:00Z","timestamp":604713600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["SIMULATION"],"published-print":{"date-parts":[[1989,3]]},"abstract":"<jats:p> Qualitative methodology in simulation requires high level model ing constructs such as causal graphs, bond graphs, or natural language. Even though there exists a virtual continuum between qualitative and quantitative simulation methods, it is important to discuss qualitative methods since they relate to notions of pro cess abstraction and discovery during model evolution. We will refer to the evolutionary process as simulation model engineer ing. We define the basic notions of qualitative simulation, give specific examples for a pendulum system, and finally discuss various issues and directions for future work. <\/jats:p>","DOI":"10.1177\/003754978905200303","type":"journal-article","created":{"date-parts":[[2008,3,29]],"date-time":"2008-03-29T17:23:43Z","timestamp":1206811423000},"page":"95-101","source":"Crossref","is-referenced-by-count":31,"title":["Qualitative methodology in simulation model engineering*"],"prefix":"10.1177","volume":"52","author":[{"given":"Paul A.","family":"Fishwick","sequence":"first","affiliation":[{"name":"Department of Computer and Information Science University of Florida Bldg. 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