Development of the survivability indicators forecasting method of the special-purpose system executive element based on analytical and stochastic simulation of a conflict situation

The developed method for forecasting the survivability indicators of the executive element of a special-purpose system based on analytical-stochastic simulation of a conflict situation is presented. The purpose of the method was to solve the problem of preserving and rational use of the resource of the executive elements to achieve the desired effect of the functioning of special-purpose systems. The method is sensitive to the description of the patterns of changes in the survivability and efficiency indicators of the system. It is supposed to compare the predicted value of the survivability indicator with its criterion value and forecast the time when the system loses the ability to effectively perform tasks. The survivability indicator is the mathematical expectation of the number of executive elements of a special-purpose system, which retained their ability to perform tasks as intended during a conflict situation. Based on the results of the study, the values of the time characteristics of a conflict situation were obtained, in particular, the duration of the corresponding states of the executive element: preparation, waiting, implementation. Graph-analytical simulation provides a solution to the problem of forecasting the time when the loss of executive elements leads to the system’s inability to effectively perform tasks. Checking of the adequacy of the method showed that the confidence interval of the discrepancy between the calculation results of other methods with a confidence level of 0.9 does not exceed 0.095, and no contradictions between the methods were found. The proposed method provides an increase in the efficiency of determining the corresponding indicators within 8–11 % and reliability by 22 %. The possibility to determine the required reserve and the time for introducing executive elements into the system can provide a justification for how they are used to maintain the required level of efficiency of a special-purpose system.

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Spatial stochastic simulation to aid local extreme value analysis of cyclone-induced wave heights when numerical hydrodynamic simulations are scarce

10.5194/egusphere-egu21-2081 ◽

2021 ◽

Author(s):

Jeremy Rohmer ◽

Rodrigo Pedreros ◽

Yann Krien

Keyword(s):

Confidence Interval ◽

Stochastic Simulation ◽

Extreme Value ◽

Return Level ◽

Extreme Value Analysis ◽

Percentage Error ◽

Value Analysis ◽

Return Levels ◽

Wave Heights ◽

Local Extreme

<p>To estimate return levels of wave heights (Hs) induced by tropical cyclones at the coast, a commonly-used approach is to (1) randomly generate a large number of synthetic cyclone events (typically >1,000); (2) numerically simulate the corresponding Hs over the whole domain of interest; (3) extract the Hs values at the desired location at the coast and (4) perform the local extreme value analysis (EVA) to derive the corresponding return level. Step 2 is however very constraining because it often involves a numerical hydrodynamic simulator that can be prohibitive to run: this might limit the number of results to perform the local EVA (typically to several hundreds). In this communication, we propose a spatial stochastic simulation procedure to increase the database size of numerical results with synthetic maps of Hs that are stochastically generated. To do so, we propose to rely on a data-driven dimensionality-reduction method, either unsupervised (Principal Component Analysis) or supervised (Partial Least Squares Regression), that is trained with a limited number of pre-existing numerically simulated Hs maps. The procedure is applied to the Guadeloupe island and results are compared to the commonly-used approach applied to a large database of Hs values computed for nearly 2,000 synthetic cyclones (representative of 3,200 years &#8211; Krien et al., NHESS, 2015). When using only a hundred of cyclones, we show that the estimates of the 100-year return levels can be achieved with a mean absolute percentage error (derived from a bootstrap-based procedure) ranging between 5 and 15% around the coasts while keeping the width of the 95% confidence interval of the same order of magnitude than the one using the full database. Without synthetic Hs maps augmentation, the error and confidence interval width are both increased by nearly 100%. A careful attention is paid to the tuning of the approach by testing the sensitivity to the spatial domain size, the information loss due to data compression, and the number of cyclones. This study has been carried within the Carib-Coast INTERREG project (https://www.interreg-caraibes.fr/carib-coast).</p>

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Improving a method for determining the maneuvering intensity of the executive element of a special-purpose system

Eastern-European Journal of Enterprise Technologies ◽

10.15587/1729-4061.2021.242688 ◽

2021 ◽

Vol 5 (3 (113)) ◽

pp. 75-83

Author(s):

Spartak Hohoniants ◽

Iurii Repilo ◽

Oleksandr Tytarenko ◽

Andrii Kokoiko ◽

Oleg Golovchenko

Keyword(s):

At Risk ◽

Initial Data ◽

Stochastic Modeling ◽

Mutual Influence ◽

Improved Method ◽

Executive Element ◽

Favorable Conditions ◽

The Impact ◽

Executive Elements ◽

Significant Factors

The purpose of improving a method is to devise a tool for resolving contradictions in the practice of conflict events related to increasing the survivability and effectiveness of participation in a conflict event. A method for forecasting the survivability indicators of a special-purpose system based on the method of analytical-stochastic modeling of a conflict event was chosen as the basis for improvement. The improved method is intended to find a compromise between the need to increase the duration of participation in the conflict and minimize the time of being at risk of loss of ability to function. The use of the improved method, unlike the existing ones, provides an assessment of the impact of maneuver on the effectiveness of the implementation of tasks and the survivability of SPS. The method implies justifying the techniques for the executive elements to maneuver in order to create favorable conditions and effectively perform tasks in a conflict event. The method involves the procedure for the formation of initial data; determining the maneuvering intensity of executive elements; comparing the parameters for expedient (rational) and implemented maneuvering techniques; the generalization of the research results. The accepted indicators of the effectiveness and survivability of a special-purpose system in a conflict event are the mathematical expectations of the number of destructive influences and the number of preserved executive elements as a function of the intensity of maneuvering. The criteria defined for assessing the maneuvering techniques are the greatest values of the increase in efficiency and survivability with the change in the intensity of maneuvering and taking the favorable position by an executive element in a conflict event. The specified method has helped investigate the peculiarities of changing performance and survivability indicators dependent on the intensity of maneuvering and determine the criteria signs for selecting maneuvering techniques. Based on the signs of informativeness and the nature of the mutual influence of the relevant indicators, the advantage of the method is 30 % while the objectivity of taking into consideration significant factors increases by 15 %. Practice needs to predict the consequences of processes of conflicting nature on the grounds of the effectiveness and survivability of its participants

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A Wind Power Forecasting Method and Its Confidence Interval Estimation

Electrical Engineering in Japan ◽

10.1002/eej.22326 ◽

2013 ◽

Vol 186 (2) ◽

pp. 52-60 ◽

Cited By ~ 1

Author(s):

Tatsuya Iizaka ◽

Toru Jintsugawa ◽

Hideyuki Kondo ◽

Yosuke Nakanishi ◽

Yoshikazu Fukuyama ◽

...

Keyword(s):

Confidence Interval ◽

Wind Power ◽

Interval Estimation ◽

Wind Power Forecasting ◽

Forecasting Method ◽

Confidence Interval Estimation ◽

Power Forecasting

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A wind power forecasting method with confidence interval

2011 IEEE 54th International Midwest Symposium on Circuits and Systems (MWSCAS) ◽

10.1109/mwscas.2011.6026398 ◽

2011 ◽

Cited By ~ 2

Author(s):

Tatsuya Iizaka ◽

Toru Jintsugawa ◽

Hideyuki Kondo ◽

Yousuke Nakanishi ◽

Yoshikazu Fukuyama ◽

...

Keyword(s):

Confidence Interval ◽

Wind Power ◽

Wind Power Forecasting ◽

Forecasting Method ◽

Power Forecasting

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Confidence Interval For An Unknown Mathematical Expectation Based On Weakly Related Observations

The American Journal of Applied Sciences ◽

10.37547/tajas/volume03issue05-25 ◽

2021 ◽

Vol 03 (05) ◽

pp. 160-171

Author(s):

Yusupov Farrukh ◽

◽

Khasanova Zukhra ◽

Keyword(s):

Confidence Interval ◽

Confidence Intervals ◽

Mathematical Expectation ◽

Random Variables ◽

Weak Relationship

In this article, we construct confidence intervals for estimating the unknown mathematical expectation of weakly related random variables. To do this, we first define a weak relationship.

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Optimising Shovel-Truck Fuel Consumption using Stochastic Simulation

Ghana Mining Journal ◽

10.4314/gm.v17i2.6 ◽

2017 ◽

Vol 17 (2) ◽

pp. 39-49

Author(s):

N. K. Dumakor ◽

V. A. Temeng ◽

K. J. Bansah

Keyword(s):

Confidence Interval ◽

Fuel Consumption ◽

Stochastic Simulation ◽

Waiting Time ◽

Material Handling ◽

Simulation Modelling ◽

Fuel Savings ◽

Simulated Fuel

Stochastic simulation was conducted to analyse the fuel consumption of a shovel-truck system. An example shovel-truck system, comprising a single shovel and four trucks was considered. At 95% confidence interval, the monthly simulated fuel consumption by the shovel-truck system was found to be about 198 127 litres against the actual fuel consumption of 203 772 litres, registering a variance of -2.70%. About 22 000 litres of fuel was consumed per month due to truck waiting. Optimising the fuel consumption and truck waiting time can result in significant fuel savings. The paper demonstrates that stochastic simulation is an effective tool for optimising the utilisation of fossil-based fuels in mining and related industries. Keywords: Stochastic, Simulation Modelling, Mining, Optimisation, Shovel-Truck Material Handling

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Convergence characteristics at stochastic estimation of image inter-frame deformations

Information Technology and Nanotechnology ◽

10.18287/1613-0073-2019-2391-114-120 ◽

2019 ◽

pp. 114-120

Author(s):

A G Tashlinskii ◽

A V Zhukova ◽

D G Kraus

Keyword(s):

Mathematical Modeling ◽

Confidence Interval ◽

Convergence Rate ◽

Probability Density ◽

Mathematical Expectation ◽

Threshold Value ◽

Stochastic Gradient ◽

Stochastic Estimation ◽

Gradient Estimation ◽

Inter Frame

Several approaches to the numerical description of image inter-frame geometric deformations parameters estimates behavior at iterations of non-identification relay stochastic gradient estimation are considered. The probability density of the Euclidean mismatch distance of estimates vector is chosen as an argument of the characteristics forming the numerical values. It made it possible to ensure invariance of research to the set of parameters of the used inter-frame geometric deformations model. The mathematical expectation, the probability of exceeding a given threshold value of the convergence rate and the confidence interval of the Euclidean mismatch distance were investigated as characteristics. Probabilistic mathematical modeling is applied to calculate the probability density of the Euclidean mismatch distance.

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Assessment of Rescue Facilities and Personnel in the Ghanaian Underground Mines

Ghana Mining Journal ◽

10.4314/gm.v18i1.7 ◽

2018 ◽

Vol 18 (1) ◽

pp. 56-64

Author(s):

Sylvester Yenzanya ◽

Newton Amegbey

Keyword(s):

Confidence Interval ◽

Fuel Consumption ◽

Stochastic Simulation ◽

Waiting Time ◽

Material Handling ◽

Simulation Modelling ◽

Underground Mines ◽

Fuel Savings ◽

Simulated Fuel

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Estimation of the time of ship maintenance by the terminal in the transport hub system

Fisheries ◽

10.37663/0131-6184-2021-2-86-89 ◽

2021 ◽

Vol 2021 (2) ◽

pp. 86-89

Author(s):

Sergey Berezenko ◽

Ksenia Penkovskaya ◽

Vyacheslav Menshikov

Keyword(s):

Markov Process ◽

Confidence Interval ◽

Least Squares ◽

Mathematical Expectation ◽

Least Squares Method ◽

Point Estimate ◽

Time Interval ◽

Time Intervals ◽

Ship Maintenance ◽

Loading And Unloading

It is proposed to evaluate various options for the mooring of a vessel at the berth of a cargo terminal by integer time intervals, which, when using Erlang's formulas, generalized to the case of the Markov process, can be used to solve the problems of planning loading and unloading operations on the company's ships, and should be presented in the form of a vector, the size of which is determined by the number of possible states of the "ship – berth" system. A method for assessing the time of servicing a loading and unloading operation by the terminal has been compiled, when observing a number of particulars corresponding to the usual histogram, and each value of the time interval corresponds to a certain bit of the histogram, a variant of evaluating the mathematical expectation of the time the terminal serves one loading and unloading operation. It was found that using the least squares method, it is possible to identify the value of the variance of the time of the loading and unloading operation, which, in turn, can be used as a point estimate when compiling the confidence interval for the mathematical expectation of this interval.

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