The Threshold Optimization of Track Image Under Strong Sunlight

2020 ◽  
Author(s):  
Wentao Hu ◽  
Yongjian Zhao
Keyword(s):  
Threshold Optimization

A Q-learning based energy threshold optimization algorithm in LAA networks

2021 ◽  
pp. 1-1
Author(s):  
Errong Pei ◽  
Lineng Zhou ◽  
Bingguang Deng ◽  
Xun Lu ◽  
Zhizhong Zhang ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
Energy Threshold ◽  
Q Learning ◽  
Threshold Optimization

A weak derivative approach to optimization of threshold parameters in a multicomponent maintenance system

2001 ◽  
Vol 38 (02) ◽  
pp. 386-406 ◽  
Author(s):  
Bernd Heidergott
Keyword(s):  
Optimization Problems ◽  
Estimation Algorithm ◽  
Replacement Policy ◽  
Cost Performance ◽  
Weak Derivative ◽  
Preventive Replacement ◽  
Maintenance System ◽  
Threshold Optimization ◽  
Age Replacement ◽  
The Cost

We consider a multicomponent maintenance system controlled by an age replacement policy: when one of the components fails, it is immediately replaced; all components older than a threshold age θ are preventively replaced. Costs are associated with each maintenance action, such as replacement after failure or preventive replacement. We derive a weak derivative estimator for the derivative of the cost performance with respect to θ. The technique is quite general and can be applied to many other threshold optimization problems in maintenance. The estimator is easy to implement and considerably increases the efficiency of a Robbins-Monro type of stochastic approximation algorithm. The paper is self-contained in the sense that it includes a proof of the correctness of the weak derivative estimation algorithm.

Optimal triage for COVID-19 patients under limited healthcare resources: Development of a parsimonious machine learning prediction model and threshold optimization using discrete-event simulation (Preprint)

2021 ◽  
Author(s):  
Jeong Min Kim ◽  
Hwa Kyung Lim ◽  
Jae-Hyeon Ahn ◽  
Kyoung Hwa Lee ◽  
Kwang Suk Lee ◽  
...  
Keyword(s):  
Prediction Model ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Mortality Rates ◽  
Clinical Severity ◽  
Ordinal Scale ◽  
Event Simulation ◽  
Hypothetical Patient ◽  
Optimal Thresholds ◽  
Threshold Optimization

BACKGROUND The coronavirus disease 2019 (COVID-19) pandemic has caused an unprecedented burden on healthcare systems. OBJECTIVE To effectively triage COVID-19 patients within situations of limited data availability and to explore optimal thresholds to minimize mortality rates while maintaining the healthcare system capacity. METHODS A nationwide sample of 5601 patients confirmed for COVID-19 up until April 2020 was retrospectively reviewed. XGBoost and logistic regression analysis were used to develop prediction models for the patients’ maximum clinical severity during hospitalization, classified according to the WHO Ordinal Scale for Clinical Improvement (OSCI). The recursive feature elimination technique was used to evaluate the extent of the model performance’s maintenance when clinical and laboratory variables are eliminated. Using populations based on hypothetical patient influx scenarios, discrete-event simulation was performed to find the optimal threshold within limited resource environments that minimizes mortality rates. RESULTS The cross-validated area under the receiver operating characteristics (AUROC) of the baseline XGBoost model that utilized all 37 variables was 0.965 for OSCI ≥ 6. Compared to the baseline model’s performance, the AUROC of the feature-eliminated model that utilized 17 variables was maintained at 0.963 with statistical insignificance. Our prediction model was provided online for clinical implementation. Optimal thresholds were found to minimize mortality rates in a hypothetical patient influx scenario. The benefit of utilizing an optimal triage threshold was clear, reducing mortality up to 18.1% compared to the conventional Youden Index. CONCLUSIONS Our adaptive triage model and its threshold optimization capability reveal that COVID-19 management can be integrated using both medical and healthcare management sectors to guarantee maximum treatment efficacy.

Sign in / Sign up

Export Citation Format

Share Document