Accuracy of reliability calculated by the Monte Carlo simulation method

Ostojić, Dušan; Pokorni, Slavko; Rakonjac, Predrag I.; Brkić, Dragoljub M.

doi:10.5937/vojtehg1204047o

“…Because of the complexity of the IoT, we suggest using simulation to asses the reliability of the IoT. We used simulation for some examples of complex systems and showed that simulations can give useful results (Pokorni & Janković, 2011), (Pokorni et al, 2011), (Ostojić et al, 2012).…”

Section: Reliabilityof the Iot Systemmentioning

confidence: 99%

Reliability and availability of the Internet of things

Pokorni¹

2019

Vojnotehnički glasnik

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The problem of reliability and availability of the Internet of Things (IoT) from the point of view of the classical approach of reliability assessment using MIL-HDBK 217 is discussed in this paper. With the classical approach of reliability assessment using MIL-HDBK 217, only hardware reliability can be assessed, and the situation with the IoT is more complicated: billions of different things (devices), software programs, and human users are involved (networked). The reliability and availability of the IoT is not only a matter of a failure rate of elements (things), but also protocols, standardization, logistics support and other influences. The relation for the reliability calcuation of an IoT system is proposed.

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“…al. [11] analyzed the accuracy of the point reliability assessment obtained using Monte Carlo simulation method depending on the sample size and number of iterations. James Charalambous et.…”

Section: Introductionmentioning

confidence: 99%

Parameter Optimization, Uncertainty Estimation and Sensitivity Analysis in Hydrological Modeling

Kherde

¹

,

Sawant²

2018

EJENG

0

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This paper describes the application of Monte-Carlo simulations for parameter optimization, uncertainty estimation and sensitivity analysis using hydrological model developed by author [8] for Wardha River basin, Maharashtra, India. The Monte Carlo simulations revealed that the average values of parameters for the local optima of the calibration period seem to give good fit to the data and performance measure (NSE) does not differ significantly from the local optima of the respective calibration years. It is interesting to notice that, if the Monte Carlo simulations are carried out all over again, it generate yet another set of random numbers as realizations of model parameters. However the model objective function (NSE) differs mere by 0.1% by running the new set of realizations and the local optimum parameter values are close to the earlier local optima. It seems that the model structure is in agreement with the ‘‘equifinality’’ or ‘‘non-uniqueness’’ concept as many different parameter sets give good fit to the data. However particular area of the parameter space is observed to be dominant in fitting the available observations, this is in contradiction to Beven’s theory behind rejecting the idea of optimum parameter set.

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Parameter Optimization, Uncertainty Estimation and Sensitivity Analysis in Hydrological Modeling

Kherde¹,

Sawant²

2018

EJERS

1

0

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This paper describes the application of Monte-Carlo simulations for parameter optimization, uncertainty estimation and sensitivity analysis using hydrological model developed by author [8] for Wardha River basin, Maharashtra, India. The Monte Carlo simulations revealed that the average values of parameters for the local optima of the calibration period seem to give good fit to the data and performance measure (NSE) does not differ significantly from the local optima of the respective calibration years. It is interesting to notice that, if the Monte Carlo simulations are carried out all over again, it generate yet another set of random numbers as realizations of model parameters. However the model objective function (NSE) differs mere by 0.1% by running the new set of realizations and the local optimum parameter values are close to the earlier local optima. It seems that the model structure is in agreement with the ‘‘equifinality’’ or ‘‘non-uniqueness’’ concept as many different parameter sets give good fit to the data. However particular area of the parameter space is observed to be dominant in fitting the available observations, this is in contradiction to Beven’s theory behind rejecting the idea of optimum parameter set.

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Accuracy of reliability calculated by the Monte Carlo simulation method

Abstract: Reliability is the main indicator of the quality of special

Cited by 3 publications

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Reliability and availability of the Internet of things

Reliability and availability of the Internet of things

Parameter Optimization, Uncertainty Estimation and Sensitivity Analysis in Hydrological Modeling

Parameter Optimization, Uncertainty Estimation and Sensitivity Analysis in Hydrological Modeling

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