Modal parameters estimation using ant colony optimisation algorithm

Metaheuristic‐based approach for state and process parameter prediction using hybrid grey wolf optimization

“…The most optimum solution among the three algorithms is highlighted in bold in Table 4. In case of F 6 , F 16 , and F 17 , the existing GWO is inferior to that of PSO algorithm, under prescribed settings. The quantitative statistical analysis is performed for both parametric and nonparametric categories.…”

“…In generic case, a hypothesis is placed to evaluate the value of the R, which becomes the significant in determining the parameter uncertainty and reliability over the estimated quantitates. The R is represented by Equation (16).…”

“…The horizon around the global optimum for all the unimodal functions (F 1 -F 7 ) is 1 × 10 −8 and multimodal functions F 8 is −1 × 10 −4 and F 9 and F 10 are 1 × 10 −8 . The fixed dimension multimodal functions are 1 × 10 −3 , 1 × 10 −4 , and 1 × 10 −8 for F 16 , F 17 , and F 18 , respectively. If any of the implemented algorithms could not reach either of the above solution space, then the algorithm is terminated.…”

“…For example, particle swarm optimization (PSO) algorithm is used to identify the model parameters in biomedical 13 and environmental applications. 14,15 Another commonly used algorithm is the ant colony optimization, which is used in estimating the model parameter 16,17 for mechanical systems. Bat algorithm, a swarm-based algorithm is also used for parameter estimation.…”

Parameter identification of nonlinear dynamic systems using an improved particle swarm optimization

“…It has been demonstrated that the applications of intelligent algorithms can bring about better performance or improved designs. There are several researches on applications of intelligent algorithms to parameters identification and control system design, such as [2][3][4][5][6].…”