Time Series Analysis: Forecasting and Control
Time Series Analysis: Forecasting and Control
Journal of Global Optimization
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Chaotic Time Series Prediction Using a Neuro-Fuzzy System with Time-Delay Coordinates
IEEE Transactions on Knowledge and Data Engineering
Differential evolution algorithm with strategy adaptation for global numerical optimization
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Adaptive particle swarm optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Prospective Infectious Disease Outbreak Detection Using Markov Switching Models
IEEE Transactions on Knowledge and Data Engineering
A novel set-based particle swarm optimization method for discrete optimization problems
IEEE Transactions on Evolutionary Computation
Clustering-Based Adaptive Crossover and Mutation Probabilities for Genetic Algorithms
IEEE Transactions on Evolutionary Computation
Differential Evolution: A Survey of the State-of-the-Art
IEEE Transactions on Evolutionary Computation
System for Infectious Disease Information Sharing and Analysis: Design and Evaluation
IEEE Transactions on Information Technology in Biomedicine
| Hi-index | 0.00 |
Prospective infectious disease outbreak detection has long been a major concern in public health. Using time series analysis method for the outbreak detection, a nonlinear Markov switching model is more excellent than linear models in modelling time series, due to its ability to describe the switching process of time series variables in different states. However the estimation difficulty of Markov switching model hinders the model's extensive application in practice. The paper proposes using Differential Evolution (termed DE) algorithm to obtain maximum likelihood estimator of Markov switching model in consideration of DE's good global optimization ability. In addition, to effectively reduce negative impact of label switching problem on disease outbreak detection validity of the estimated model by maximum likelihood estimation (termed MLE) method, the paper introduces identifiability constraint on estimation parameters constructed with the heuristic information about difference between durations of different states in MLE using DE. Encouraging experimental study has demonstrated the effectiveness and efficiency of DE in maximizing likelihood function of the studied Markov switching model as well as the effectiveness of the proposed identifiability constraint on improving disease outbreak detection validity of the estimated Markov switching model by MLE.