On interval estimates for optimal value of stochastic programs

2007 ◽  
pp. 556-563
Author(s):  
Jitka Dupačová
Keyword(s):  
Interval Estimates ◽  
Stochastic Programs ◽  
Optimal Value

Dual Bounds for Periodical Stochastic Programs

2022 ◽  
Author(s):  
Alexander Shapiro ◽  
Yi Cheng
Keyword(s):  
Upper Bound ◽  
Numerical Experiments ◽  
Dual Problem ◽  
Infinite Horizon ◽  
Stochastic Program ◽  
Discount Factor ◽  
Stochastic Programs ◽  
Multistage Stochastic Program ◽  
Optimal Value ◽  
Dual Bounds

A construction of the dual of a periodical formulation of infinite-horizon linear stochastic programs with a discount factor is discussed. The dual problem is used for computing a deterministic upper bound for the optimal value of the considered multistage stochastic program. Numerical experiments demonstrate behavior of that upper bound, especially when the discount factor is close to one.

Quantitative Stability of Two-Stage Linear Second-Order Conic Stochastic Programs with Full Random Recourse

2018 ◽  
Vol 35 (05) ◽  
pp. 1850031
Author(s):  
Qingsong Duan ◽  
Mengwei Xu ◽  
Shaoyan Guo ◽  
Liwei Zhang
Keyword(s):  
Lipschitz Continuity ◽  
Optimal Solution ◽  
Second Order ◽  
Two Stage ◽  
Quantitative Stability ◽  
Stochastic Programs ◽  
Perturbation Problem ◽  
Optimal Value ◽  
Primal And Dual Problems ◽  
Primal And Dual

In this paper, we consider quantitative stability for full random two-stage linear stochastic program with second-order conic constraints when the underlying probability distribution is subjected to perturbation. We first investigate locally Lipschitz continuity of feasible set mappings of the primal and dual problems in the sense of Hausdorff distance which derives the Lipschitz continuity of the objective function, and then establish the quantitative stability results of the optimal value function and the optimal solution mapping for the perturbation problem. Finally, the obtained results are applied to the convergence analysis of optimal values and solution sets for empirical approximations of the stochastic problems.

How to Correct for Chance Agreement in the Estimation of Sensitivity and Specificity of Diagnostic Tests

1994 ◽  
Vol 33 (02) ◽  
pp. 180-186 ◽  
Author(s):  
H. Brenner ◽  
O. Gefeller
Keyword(s):  
Sensitivity And Specificity ◽  
Disease Status ◽  
Disease Prevalence ◽  
Small Sample ◽  
Small Samples ◽  
Interval Estimate ◽  
Traditional Concept ◽  
Interval Estimates ◽  
Major Disadvantage ◽  
Test Result

Abstract:The traditional concept of describing the validity of a diagnostic test neglects the presence of chance agreement between test result and true (disease) status. Sensitivity and specificity, as the fundamental measures of validity, can thus only be considered in conjunction with each other to provide an appropriate basis for the evaluation of the capacity of the test to discriminate truly diseased from truly undiseased subjects. In this paper, chance-corrected analogues of sensitivity and specificity are presented as supplemental measures of validity, which pay attention to the problem of chance agreement and offer the opportunity to be interpreted separately. While recent proposals of chance-correction techniques, suggested by several authors in this context, lead to measures which are dependent on disease prevalence, our method does not share this major disadvantage. We discuss the extension of the conventional ROC-curve approach to chance-corrected measures of sensitivity and specificity. Furthermore, point and asymptotic interval estimates of the parameters of interest are derived under different sampling frameworks for validation studies. The small sample behavior of the estimates is investigated in a simulation study, leading to a logarithmic modification of the interval estimate in order to hold the nominal confidence level for small samples.

Optimization of K Value in KNN Algorithm for Spam and Ham Email Classification

2020 ◽  
Vol 4 (2) ◽  
pp. 377-383
Author(s):  
Eko Laksono ◽  
Achmad Basuki ◽  
Fitra Bachtiar
Keyword(s):  
Frequency Distribution ◽  
Confusion Matrix ◽  
High Accuracy ◽  
K Value ◽  
A Value ◽  
Optimal Value ◽  
Classification Evaluation ◽  
Email Spam ◽  
Email Classification

There are many cases of email abuse that have the potential to harm others. This email abuse is commonly known as spam, which contains advertisements, phishing scams, and even malware. This study purpose to know the classification of email spam with ham using the KNN method as an effort to reduce the amount of spam. KNN can classify spam or ham in an email by checking it using a different K value approach. The results of the classification evaluation using confusion matrix resulted in the KNN method with a value of K = 1 having the highest accuracy value of 91.4%. From the results of the study, it is known that the optimization of the K value in KNN using frequency distribution clustering can produce high accuracy of 100%, while k-means clustering produces an accuracy of 99%. So based on the results of the existing accuracy values, the frequency distribution clustering and k-means clustering can be used to optimize the K-optimal value of the KNN in the classification of existing spam emails.

Optimization of Cutting Parameters in Milling Process Using Genetic Algorithm and ANOVA (March 2020)

2020 ◽  
Vol 38 (10A) ◽  
pp. 1489-1503
Author(s):  
Marwa Q. Ibraheem
Keyword(s):  
Genetic Algorithm ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Optimal Value ◽  
Optimization Of Cutting Parameters

In this present work use a genetic algorithm for the selection of cutting conditions in milling operation such as cutting speed, feed and depth of cut to investigate the optimal value and the effects of it on the material removal rate and tool wear. The material selected for this work was Ti-6Al-4V Alloy using H13A carbide as a cutting tool. Two objective functions have been adopted gives minimum tool wear and maximum material removal rate that is simultaneously optimized. Finally, it does conclude from the results that the optimal value of cutting speed is (1992.601m/min), depth of cut is (1.55mm) and feed is (148.203mm/rev) for the present work.

FORMULATION AND SOLUTION OF OPTIMIZATION PROBLEM REDUNDANCY SYSTEM COMPRISING SITUATION CENTER

2019 ◽  
pp. 44-50
Author(s):  
A.V. Alekseev
Keyword(s):  
Analytical Model ◽  
Quality Indicators ◽  
Significant Influence ◽  
Optimization Problem ◽  
Sampling Theorem ◽  
Sampling Frequency ◽  
Generalized Sampling ◽  
Optimal Value ◽  
Situation Center ◽  
Situation Centers

The analysis of the concept, properties and features of heterogeneous redundancy in modern complex ergatic systems, including those included in the situation centers (SC). On the basis of the qualimetric paradigm, the generalized analytical model of quality and optimization of quality by private, group, summary and aggregated quality indicators is justified. Practical ways of realization of the model and methods of optimization of the objects which are a part of SC and them as a whole at the expense of reduction of structural, functional and other types of redundancy under the obligatory condition of non-reduction of the required value of quality are given. On the example of the generalized sampling theorem when choosing the optimal value of the sampling frequency of the real bandpass signal, the criticality and significant influence on the redundancy of data in their further processing in the SC is shown.

Neutrophil/lymphocyte Ratio after Flow Citometry Periferic Blood Cell Detection - Predictive Marker of Anastomotic Fistula in Colorectal Cancer Surgery

2020 ◽  
Vol 71 (6) ◽  
pp. 295-306
Author(s):  
Dumitru Radulescu ◽  
Vlad Dumitru Baleanu ◽  
Andrei Nicolaescu ◽  
Marius Lazar ◽  
Marius Bica ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Patients ◽  
Rectal Surgery ◽  
Predictive Marker ◽  
Fistula Formation ◽  
Cell Detection ◽  
Colon And Rectal Surgery ◽  
Optimal Value ◽  
Anastomotic Fistula ◽  
Colorectal Cancer Patients

Anastomotic fistula is a dreadful complication of colon and rectal surgery that can put life into danger, being common after colorectal surgery. The preoperative lymphocyte neutrophil ratio (NLR) is known as a prognostic marker for colorectal cancer patients. The existence of a predictive marker of anastomotic fistula in colorectal cancer patients is not fully undestood, so we proposed to investigate the utility of preoperative NLR as a predictor of anastomotic fistula formation. This study the Neutrophils and lymphocytes were detected from periferic blood using flow citometry. We retrospectively evaluated 161 patients with colorectal cancer, who were treated curatively, in which at least one anastomosis was performed, comparing NLR values between patients who had fistula and those with normal healing, then comparing the group with low NLR, with the group with increased NLR, after finding the optimal value of NLR using the ROC curve.The optimal value of the NLR after establishing the cutoff value was 3.07. Between the low NLR group (n=134) and the high NLR group (n=27), were observed statistically significant differences in fistula (p [0.001) and death (p=0.001). The odds ratio for failure in the group with increased NLR was 10.37, which means that patients with NLR]3.54 have a chance of developing anastomotic fistula greater than 10.37 comparable to patients with lower NLR. We suggest the preoperative use of NLR can be used as a predictive marker of anastomotic fistula than can increase the quality of preoperative preparation and therefore the establishment of the optimal surgical technique that can lead to anastomotic fistula risk decrease.

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