Modeling and Predicting Monkeypox Spread Using Fuzzy Logic and Machine Learning Regression Techniques H. A. Bhavithra, S. Sindhuja, T. Harikrishnan, S. Sindu Devi, P. Sathya, A. Sudha Rani 2025 International Conference on Computing Technologies and Data Communication Icctdc 2025, 2025 Understanding the dynamics of infectious disease such as Monkeypox is critical for effective public health intervention. This study integrates fuzzy logic based mathematical modeling and machine learning techniques to capture the complexities and uncertainties inherent in real world disease dynamics. A fuzzy logic approach was employed to assign weighted values to key parameters, enabling a more flexible representation of disease spread. Simulations revealed a significant shift in the disease-free equilibrium, with the number of susceptible individuals declining from 1000 to 185 as parameter weights varied. To complement the modeling, three machine learning regression models - Linear Regression Polynomial Regression and Decision Tree Regression were evaluated for predicting univariate time series data. Results showed that polynomial Regression outperformed the others across all standard metrics (RMSE, MAE, MAPE, MSE), effectively capturing the underlying nonlinear patterns in data. These findings emphasize the importance of incorporating both uncertainty aware modeling and appropriate machine learning techniques for accurate prediction and strategic planning on disease control. Further work may explore advanced nonlinear models such as Support Vector Regression and LSTM networks for enhanced long-term forecasting.
Dihedral Group Divisor Cordial Labeling For Path, Cycle Graph, Star Graph, Jelly Fish And Wheel Graphs Iaeng International Journal of Applied Mathematics, 2024
Dihedral Group Contra Mean Cordial Labeling for Path, Cycle, Ladder and Dumbbell Graphs Iaeng International Journal of Applied Mathematics, 2024
A Method for Solving Balanced and Unbalanced Trapezoidal Intuitionistic Fuzzy Assignment Quandary M Joseph Robinson, C Veeramani, A Sudha Rani Journal of Physics Conference Series, 2019 In this paper, we discuss Trapezoidal intuitionistic fuzzy assignment quandary(TrIFAP). In classical assignment quandary, Cost always remains same. But, here we develop an method to solve Trapezoidal intuitionistic fuzzy assignment quandary where cost is not deterministic numbers but infelicitous ones. Here, the costs(profits) matrix have all the elements they are TrIFN and others have been immensely colossal demonstration against the classical method. Then its trapezoidal membership and non-membership functions are defined. In general compare the findings from different methods attested the same picture. Numerical examples show that an intuitionistic fuzzy ranking method is very efficacious and utilizable method for handling a TrIFAP.
A Method for Solving Balanced and Unbalanced Trapezoidal Intuitionistic Fuzzy Assignment Quandary SRA Joseph Robinson.M, Veeramani.C Journal of Physics: Conference Seriesthis link is disabled, 2019 1377 (012021) , 2019 2019
A Novel Approach for Solving Triangular and Trapezoidal Intuitionistic Fuzzy Games Using Dominance Property and Oddment Method M Joseph Robinson, S Sheela, A Sudha Rani Computational Intelligence, Cyber Security and Computational Models … , 2015 2015
MOST CITED SCHOLAR PUBLICATIONS
A Method for Solving Balanced and Unbalanced Trapezoidal Intuitionistic Fuzzy Assignment Quandary SRA Joseph Robinson.M, Veeramani.C Journal of Physics: Conference Seriesthis link is disabled, 2019 1377 (012021) , 2019 2019
A Novel Approach for Solving Triangular and Trapezoidal Intuitionistic Fuzzy Games Using Dominance Property and Oddment Method M Joseph Robinson, S Sheela, A Sudha Rani Computational Intelligence, Cyber Security and Computational Models … , 2015 2015
