Inverse Analysis of Rock Creep Model Parameters Based on Improved Simulated Annealing Differential Evolution Algorithm

2018 ◽  
Vol 37 (2) ◽  
pp. 639-649 ◽  
Author(s):  
Liu Yang ◽  
Zhi-da Li
Keyword(s):  
Simulated Annealing ◽  
Differential Evolution ◽  
Inverse Analysis ◽  
Differential Evolution Algorithm ◽  
Creep Model ◽  
Model Parameters ◽  
Rock Creep ◽  
Evolution Algorithm

scholarly journals Solving Multiobjective Game in Multiconflict Situation Based on Adaptive Differential Evolution Algorithm with Simulated Annealing

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Huimin Li ◽  
Shuwen Xiang ◽  
Wensheng Jia ◽  
Yanlong Yang ◽  
Shiguo Huang
Keyword(s):  
Simulated Annealing ◽  
Differential Evolution ◽  
Differential Evolution Algorithm ◽  
Payoff Function ◽  
Game Model ◽  
Entropy Weight ◽  
Strategy Space ◽  
De Algorithm ◽  
Adaptive Differential Evolution ◽  
Evolution Algorithm

In this paper, we study the multiobjective game in a multiconflict situation. First, the feasible strategy set and synthetic strategy space are constructed in the multiconflict situation. Meanwhile, the value of payoff function under multiobjective is determined, and an integrated multiobjective game model is established in a multiconflict situation. Second, the multiobjective game model is transformed into the single-objective game model by the Entropy Weight Method. Then, in order to solve this multiobjective game, an adaptive differential evolution algorithm based on simulated annealing (ADESA) is proposed to solve this game, which is to improve the mutation factor and crossover operator of the differential evolution (DE) algorithm adaptively, and the Metropolis rule with probability mutation ability of the simulated annealing (SA) algorithm is used. Finally, the practicability and effectiveness of the algorithm are illustrated by a military example.

scholarly journals Estimating Traffic Accidents in Turkey Using Differential Evolution Algorithm

2017 ◽  
Vol 12 (1) ◽  
pp. 75-84
Author(s):  
Ali Payıdar Akgüngör ◽  
Ersin Korkmaz
Keyword(s):  
Differential Evolution ◽  
Road Safety ◽  
Traffic Accidents ◽  
Model Development ◽  
Differential Evolution Algorithm ◽  
Vital Role ◽  
Performance Criteria ◽  
Model Parameters ◽  
Evolution Algorithm ◽  
Mean Square Errors

Abstract Estimating traffic accidents play a vital role to apply road safety procedures. This study proposes Differential Evolution Algorithm (DEA) models to estimate the number of accidents in Turkey. In the model development, population (P) and the number of vehicles (N) are selected as model parameters. Three model forms, linear, exponential and semi-quadratic models, are developed using DEA with the data covering from 2000 to 2014. Developed models are statistically compared to select the best fit model. The results of the DE models show that the linear model form is suitable to estimate the number of accidents. The statistics of this form is better than other forms in terms of performance criteria which are the Mean Absolute Percentage Errors (MAPE) and the Root Mean Square Errors (RMSE). To investigate the performance of linear DE model for future estimations, a ten-year period from 2015 to 2024 is considered. The results obtained from future estimations reveal the suitability of DE method for road safety applications.

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