Study on stealth characteristics of metamaterials based on simulated annealing algorithm

Liu, Feiliang; Wang, Yan; Bai, Yang; Yu, Jie

doi:10.1016/j.procs.2019.01.230

Cited by 8 publications

(2 citation statements)

References 6 publications

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“…Simulated annealing is an algorithm that simulates the solid annealing process. Such a process includes the coding of the solution, an annealing temperature, the energy function, generation and acceptance of a new solution, and the length of the Markov chain (Liu et al, 2019). Detailed descriptions are as follows.…”

Section: Solution Algorithmmentioning

confidence: 99%

Dynamic location models of mobile sensors for travel time estimation on a freeway

Sun¹,

Shen²,

Shao³

et al. 2021

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Travel time estimation for freeways has attracted much attention from researchers and traffic management departments. Because of various uncertain factors, travel time on a freeway is stochastic. To obtain travel time estimates for a freeway accurately, this paper proposes two traffic sensor location models that consider minimizing the error of travel time estimation and maximizing the collected traffic flow. First, a dynamic optimal location model of the mobile sensor is proposed under the assumption that there are no traffic sensors on a freeway. Next, a dynamic optimal combinatorial model of adding mobile sensors taking account of fixed sensors on a freeway is presented. It should be pointed out that the technology of data fusion will be adopted to tackle the collected data from multiple sensors in the second optimization model. Then, a simulated annealing algorithm is established to find the solutions of the proposed two optimization models. Numerical examples demonstrate that dynamic optimization of mobile sensor locations for the estimation of travel times on a freeway is more accurate than the conventional location model.

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Section: Solution Algorithmmentioning

confidence: 99%

Dynamic location models of mobile sensors for travel time estimation on a freeway

Sun¹,

Shen²,

Shao³

et al. 2021

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show abstract

“…r 1 () and r 2 () are random Numbers in the range of 0-1; v max d is the maximum speed; Δt is the time interval. The starting point of simulated annealing algorithm 22 for optimization problems is based on the similarity between the annealing process of solid substances in physics and general optimization problems. In Aslett et al, 23 the acceptance criterion allows the target function to go bad rather than according to probability, but directly presses ΔE < e, where ΔE is the change in the adaptive value caused by the two positions, and e is the range of the allowed target function to go bad.…”

Section: Introductionmentioning

confidence: 99%

Reliability evaluation of concrete‐filled steel tube arch bridge based on DBN‐PSOSA hybrid algorithm

Hong

et al. 2021

Structural Concrete

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When traditional response surface method is used to evaluate the reliability of concrete-filled steel tubular arch bridge, due to its complex structure and highly nonlinear implicit function, the response surface fitting accuracy is not high, and the reliability accuracy is difficult to meet the requirements of design specifications. In order to solve the above problems, this paper chooses dynamic Bayesian networks (DBN) which is suitable for solving the problem of multiple state unit or system uncertainty to build implicit function of the response surface function. And this paper combines DBN and particle swarm optimization algorithm based on simulated annealing algorithm (PSOSA) to improve efficiency of model parameter optimization. It can make the construction of implicit function simulate the real structure of the limit state function. Then this paper verifies the suitability for this kind of complex structure reliability assessment of DBN-PSOSA hybrid algorithm. A numerical example is given to demonstrate the effectiveness of the proposed method, and the reliability of a concrete filled steel tube arch bridge project is evaluated. The results show that this method improves the calculation accuracy and efficiency.

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Multi-strategy synergy-based backtracking search optimization algorithm

Wei

Yunpeng

et al. 2020

Soft Comput

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Study on stealth characteristics of metamaterials based on simulated annealing algorithm

Cited by 8 publications

References 6 publications

Dynamic location models of mobile sensors for travel time estimation on a freeway

Dynamic location models of mobile sensors for travel time estimation on a freeway

Reliability evaluation of concrete‐filled steel tube arch bridge based on DBN‐PSOSA hybrid algorithm

Multi-strategy synergy-based backtracking search optimization algorithm

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