Muhammad Shoaib Arif^1,2,*, Kamaleldin Abodayeh¹, Yasir Nawaz²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3417-3434, 2024, DOI:10.32604/cmes.2024.046944 - 11 March 2024

Abstract This study focuses on the urgent requirement for improved accuracy in disease modeling by introducing a new computational framework called the Hybrid SIR-Fuzzy Model. By integrating the traditional Susceptible-Infectious-Recovered (SIR) model with fuzzy logic, our method effectively addresses the complex nature of epidemic dynamics by accurately accounting for uncertainties and imprecisions in both data and model parameters. The main aim of this research is to provide a model for disease transmission using fuzzy theory, which can successfully address uncertainty in mathematical modeling. Our main emphasis is on the imprecise transmission rate parameter, utilizing a three-part… More >

Ibtehal Alazman¹, Kholoud Saad Albalawi¹, Pranay Goswami^2,*, Kuldeep Malik²

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2409-2425, 2023, DOI:10.32604/cmes.2023.028674 - 03 August 2023

Abstract This paper presents a restricted SIR mathematical model to analyze the evolution of a contagious infectious disease outbreak (COVID-19) using available data. The new model focuses on two main concepts: first, it can present multiple waves of the disease, and second, it analyzes how far an infection can be eradicated with the help of vaccination. The stability analysis of the equilibrium points for the suggested model is initially investigated by identifying the matching equilibrium points and examining their stability. The basic reproduction number is calculated, and the positivity of the solutions is established. Numerical simulations More >

F. M. Allehiany¹, Fazal Dayan^2,3,*, F. F. Al-Harbi⁴, Nesreen Althobaiti⁵, Nauman Ahmed², Muhammad Rafiq⁶, Ali Raza⁷, Mawahib Elamin⁸

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3213-3229, 2022, DOI:10.32604/cmc.2022.025811 - 29 March 2022

Abstract Fuzziness or uncertainties arise due to insufficient knowledge, experimental errors, operating conditions and parameters that provide inaccurate information. The concepts of susceptible, infectious and recovered are uncertain due to the different degrees in susceptibility, infectivity and recovery among the individuals of the population. The differences can arise, when the population groups under the consideration having distinct habits, customs and different age groups have different degrees of resistance, etc. More realistic models are needed which consider these different degrees of susceptibility infectivity and recovery of the individuals. In this paper, a Susceptible, Infected and Recovered (SIR) More >

Khaled A. Gepreel^1,2, Mohamed S. Mohamed^1,3, Hammad Alotaibi¹, Amr M. S. Mahdy^1,2,*

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 675-686, 2021, DOI:10.32604/cmc.2021.012200 - 12 January 2021

Abstract The development of mathematical modeling of infectious diseases is a key research area in various fields including ecology and epidemiology. One aim of these models is to understand the dynamics of behavior in infectious diseases. For the new strain of coronavirus (COVID-19), there is no vaccine to protect people and to prevent its spread so far. Instead, control strategies associated with health care, such as social distancing, quarantine, travel restrictions, can be adopted to control the pandemic of COVID-19. This article sheds light on the dynamical behaviors of nonlinear COVID-19 models based on two methods: More >

Hefei Ling¹, Yang Fang¹, Lei Wu¹, Ping Li^1,*, Jiazhong Chen¹, Fuhao Zou¹, Jialie Shen²

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 85-100, 2019, DOI:10.32604/cmc.2019.05588

Abstract Recently, Convolutional Neural Network (CNN) based hashing method has achieved its promising performance for image retrieval task. However, tackling the discrepancy between quantization error minimization and discriminability maximization of network outputs simultaneously still remains unsolved. Motivated by the concern, we propose a novel Balanced Deep Supervised Hashing (BDSH) based on variant posterior probability to learn compact discriminability-preserving binary code for large scale image data. Distinguished from the previous works, BDSH can search an equilibrium point within the discrepancy. Towards the goal, a delicate objective function is utilized to maximize the discriminability of the output space More >

X.G. Yuan^1,2, R.J. Zhang³, H.W. Zhang¹

CMC-Computers, Materials & Continua, Vol.7, No.3, pp. 155-166, 2008, DOI:10.3970/cmc.2008.007.155

Abstract In this paper, the dynamic inflation problems are examined for infinitely long cylindrical tubes composed of a class of transversely isotropic incompressible Ogden material models. The inner surface of the tube is subjected to a class of periodic step radial pressures relating to time. The influences of various parameters, namely, the material parameters, the structure parameters and the applied pressures, on dynamic behaviors of the tube are discussed in detail. Significantly, for some given material parameters, it is proved that the motion of the tube would present a class of nonlinear periodic oscillations for any… More >