A NOVEL DESIGN OF MEYER WAVELET NEURAL NETWORKS TO STUDY THE EPIDEMIOLOGICAL SMOKING MODEL

Muhammad Shoaib, Ghania Zubair (), Kottakkaran Sooppy Nisar, Muhammad Asif Zahoor Raja, Mohammed S. Alqahtani, Mohamed Abbas and H. M. Almohiy ()
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Muhammad Shoaib: Department of Mathematics, COMSATS University Islamabad, Attock Campus, Punjab, Pakistan†Yuan Ze University, AI Center, Taoyuan 320, Taiwan
Ghania Zubair: Department of Mathematics, COMSATS University Islamabad, Attock Campus, Punjab, Pakistan
Kottakkaran Sooppy Nisar: Department of Mathematics, College of Sciences and Humanities, Prince Sattam bin Abdulaziz University, Al Kharj 16278, Saudi Arabia2School of Technology, Woxsen University, Hyderabad 502345, Telangana, India
Muhammad Asif Zahoor Raja: Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliu, Yunlin 64002, Taiwan
Mohammed S. Alqahtani: Radiological Sciences Department, College of Applied Medical Sciences, King Khalid University, Abha 61421, Saudi Arabia5BioImaging Unit, Space Research Centre, Michael Atiyah Building, University of Leicester, Leicester LE1 7RH, UK
Mohamed Abbas: Electrical Engineering Department, College of Engineering, King Khalid University, Abha 61421, Saudi Arabia7Electronics and Communications Department, College of Engineering, Delta University for Science and Technology, Gamasa 35712, Egypt
H. M. Almohiy: Radiological Sciences Department, College of Applied Medical, Sciences King Khalid University, Abha 61421, Saudi Arabia

FRACTALS (fractals), 2023, vol. 31, issue 02, 1-20

Abstract: In this paper, a new Meyer neuro-evolutionary computational algorithm is introduced for mathematical modeling of the epidemiological smoking model by employing hybrid heuristics of Meyer wavelet neural network with global optimized search efficiency of genetic algorithm and sequential quadratic programming. According to the World Health Organization, tobacco consumption kills 10% of all adults worldwide. The smoking epidemic is often regarded as the greatest health threat that humanity has ever confronted. So it’s an important issue to address by employing hybrid suggested techniques. The Meyer wavelet modeling approach is exploited to describe the system model epidemiological smoking in a mean squared error-based function, and the systems are optimized using the proposed approach’s combined optimizing capability. Root mean square error, Theil’s inequality factor, and mean absolute deviation-based measurements are used to better verify the effectiveness of the suggested methodology. The combined approach for smoking model is verified, validated, and perfected through comparison investigations of reference results on stability, precision, convergence, and reliability criteria, which shows the novelty of this study. Furthermore, the results of the quantitative study support the value of the suggested approach-based stochastic algorithm. The values of absolute error lie between 10−2 and 102, 10−6 and 10−3, 10−6 and 10−4, 10−6 and 10−3, 10−5 and 10−4, and 10−6 and 10−5. The convergence measurement values for Theil’s inequality coefficient lie between 10−5 and 100, 10−10 and 10−5, 10−10 and 10−5, 10−10 and 10−5, 10−10 and 10−5, and 10−10 and 10−5.

Keywords: Epidemiological Smoking Model; Meyer Neuro-Evolutionary Computation Algorithm; Meyer Wavelet; Genetic Algorithm; Sequential Quadratic Programming (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S0218348X23400340

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