Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Qin-Ming Liu"'
Publikováno v:
Behavioral Sciences, Vol 12, Iss 9, p 332 (2022)
To prevent vehicle crashes, studies have proposed the use of flashing signals (brake lights or other light indicators) to improve the driver’s response time when the leading vehicle is braking. However, there are no consistent results on the ideal
Externí odkaz:
https://doaj.org/article/1659880300c24891af8a625b4d835747
Autor:
Qin Ming Liu, Wenyuan Lv
Publikováno v:
Industrial Management & Data Systems. 115:1412-1434
Purpose – The traditional maintenance scheduling strategies of multi-component systems may result in maintenance shortage or overage, while system degradation information is often ignored. The purpose of this paper is to propose a multi-phase model
Autor:
Ming Dong, Qin Ming Liu
Publikováno v:
Advanced Materials Research. :420-424
This paper explores the grey model based PSO (particle swarm optimization) algorithm for fatigue strength prognosis of concrete. First, depending on concrete’s testing status, fatigue life is studied. Then, one GM(1,1) based PSO algorithm is used i
Autor:
Ming Dong, Qin Ming Liu
Publikováno v:
Advanced Materials Research. :541-545
This paper explores the grey model based PSO (particle swarm optimization) algorithm for anti-cauterization reliability design of underground pipelines. First, depending on underground pipelines’ corrosion status, failure modes such as leakage and
Autor:
Wenyuan Lv, Qin Ming Liu
Publikováno v:
Computer and Information Science. 2
Diesel is a very complex system. Subsystems and components of diesel will be failure, between failure symptoms and causes have many uncertain factors. In view of this situation, fault diagnosis method based on PSO algorithm is presented. The effectiv
The forecasting residual life of underground pipeline based on particle swarm optimisation algorithm
Autor:
Wenyuan Lv, Qin Ming Liu
Publikováno v:
International Journal of Bio-Inspired Computation. 1:270
Grey theory explores the use of the PSO algorithm and this paper analysed the feasibility of using this algorithm to forecast the residual life of underground pipeline. It is allowed to offer fewer data while using this method to forecast its residua