A computational framework to solve the nonlinear dengue fever SIR system. Issue 16 (10th December 2022)

• Record Type: Journal Article
• Authors: Umar, Muhammad; Kusen, ; Raja, Muhammad Asif Zahoor; Sabir, Zulqurnain; Al-Mdallal, Qasem
• Is Part Of: Computer methods in biomechanics and biomedical engineering. Volume 25:Issue 16(2022)
• Page Start: 1821
• Page End: 1834
• Publication Date: 2022-12-10
• Subjects: Nonlinear dengue fever -- SIR system -- Levenberg-Marquardt backpropagation -- reference dataset -- numerical measures; Biomechanics -- Data processing -- Periodicals; Biomedical engineering -- Periodicals; Biomechanics -- Periodicals; Biomedical Engineering -- methods -- Periodicals; Computing Methodologies -- Periodicals; 612.7
• DOI: 10.1080/10255842.2022.2039640
• Languages: English
• ISSNs: 1025-5842

Abstract

Abstract: This study is relevant to present the numerical form of the nonlinear dengue fever SIR system are presented using the artificial neural networks along with the Levenberg-Marquardt backpropagation technique, i.e. ANNs-LMB. The procedures of ANNs-LMB are applied with three different sample data scales based on testing, training and authentication. The statistics to solve three cases of the nonlinear dengue fever based on susceptible, infected and recovered system are selected with 75%, 15% and 10% for training, validation and testing, respectively. To find the numerical results of the nonlinear dengue fever system, the reference dataset is designed on the basis of Adams scheme for the numerical solution. The numerical results based on the nonlinear dengue fever system are obtained through the ANNs-LMB to reduce the mean square error. In order to check the exactness, reliability, effectiveness and competence of the proposed ANNs-LMB, the numerical outcomes are proficient to the proportional measures using the topographies of the fitness attained in mean squared error sense, correlation, error histograms and regression.