Monte Carlo simulation analysis of ceftobiprole, dalbavancin, daptomycin, tigecycline, linezolid and vancomycin pharmacodynamics against intensive care unit-isolated methicillin-resistantStaphylococcus aureus

2014 ◽  
Vol 41 (6) ◽  
pp. 437-443 ◽  
Author(s):  
Ahmed Hamed Salem ◽  
George G Zhanel ◽  
Safaa A Ibrahim ◽  
Ayman M Noreddin
Keyword(s):  
Intensive Care Unit ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Intensive Care ◽  
Simulation Analysis

scholarly journals Monte Carlo Simulation of Doripenem in Patients Admitted to Intensive Care Unit

2017 ◽  
Vol 39 (8) ◽  
pp. e60-e61
Author(s):  
R. Tanaka ◽  
Y. Sato ◽  
Y. Suzuki ◽  
K. Goto ◽  
N. Yasuda ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Intensive Care

Simulation Analysis of the Capture Strategy Impact of Seeker Capture Probability

2013 ◽  
Vol 753-755 ◽  
pp. 1984-1987
Author(s):  
Guo Dong Zhang ◽  
Jing Xin An ◽  
Zhong Liu
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Statistical Methods ◽  
Simulation Analysis ◽  
Target Group ◽  
Capture Probability ◽  
Probability Models ◽  
Target Capture

Whether can seeker capture the ship target in target group is one of the important factors affect the anti-ship missile efficiency. By establishing the target capture probability models under various capture strategies and giving the Monte-Carlo simulation flow, this paper obtained the capture probability under various capture strategies by statistical methods. The result shows that because of the lack of comprehensive consideration of battlefield situation, the existing target capture strategies are difficult to finish the capture ship targets task efficiently; the result also indicates the target capture strategies direction.

The Use of Quantitative Methods in Investment Decisions

2019 ◽  
pp. 256-275 ◽  
Author(s):  
Serkan Eti
Keyword(s):  
Neural Networks ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Artificial Neural Networks ◽  
Decision Tree ◽  
Quantitative Methods ◽  
Simulation Analysis ◽  
Investment Decision ◽  
Tree Algorithms ◽  
Artificial Neural

Quantitative methods are mainly preferred in the literature. The main purpose of this chapter is to evaluate the usage of quantitative methods in the subject of the investment decision. Within this framework, the studies related to the investment decision in which quantitative methods are taken into consideration. As for the quantitative methods, probit, logit, decision tree algorithms, artificial neural networks methods, Monte Carlo simulation, and MARS approaches are taken into consideration. The findings show that MARS methodology provides a more accurate results in comparison with other techniques. In addition to this situation, it is also concluded that probit and logit methodologies were less preferred in comparison with decision tree algorithms, artificial neural networks methods, and Monte Carlo simulation analysis, especially in the last studies. Therefore, it is recommended that a new evaluation for investment analysis can be performed with MARS method because it is understood that this approach provides better results.

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