{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T16:42:29Z","timestamp":1772815349305,"version":"3.50.1"},"reference-count":35,"publisher":"Wiley","license":[{"start":{"date-parts":[[2022,1,31]],"date-time":"2022-01-31T00:00:00Z","timestamp":1643587200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Healthcare Engineering"],"published-print":{"date-parts":[[2022,1,31]]},"abstract":"<jats:p>This study is associated to solve the nonlinear SIR dengue fever system using a computational methodology by operating the neural networks based on the designed Morlet wavelet (MWNNs), global scheme as genetic algorithm (GA), and rapid local search scheme as interior-point algorithm (IPA), i.e., GA-IPA. The optimization of fitness function based on MWNNs is performed for solving the nonlinear SIR dengue fever system. This MWNNs-based fitness function is accessible using the differential system and initial conditions of the nonlinear SIR dengue fever system. The designed procedures based on the MWNN-GA-IPA are applied to solve the nonlinear SIR dengue fever system to check the exactness, precision, constancy, and efficiency. The achieved numerical form of the nonlinear SIR dengue fever system via MWNN-GA-IPA was compared with the Runge\u2013Kutta numerical results that verify the significance of MWNN-GA-IPA. Moreover, statistical reflections through different measures for the nonlinear SIR dengue fever system endorse the precision and convergence of the computational MWNN-GA-IPA.<\/jats:p>","DOI":"10.1155\/2022\/9981355","type":"journal-article","created":{"date-parts":[[2022,1,31]],"date-time":"2022-01-31T16:35:12Z","timestamp":1643646912000},"page":"1-14","source":"Crossref","is-referenced-by-count":12,"title":["An Advance Computing Numerical Heuristic of Nonlinear SIR Dengue Fever System Using the Morlet Wavelet Kernel"],"prefix":"10.1155","volume":"2022","author":[{"given":"Muhammad","family":"Umar","sequence":"first","affiliation":[{"name":"Department of Mathematics and Statistics, Hazara University, Mansehra, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zulqurnain","family":"Sabir","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, Hazara University, Mansehra, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muhammad Asif","family":"Zahoor Raja","sequence":"additional","affiliation":[{"name":"Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"K. 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