CorrectMyText Users
English language
The text to correct from user juliana-zh
In our articles we've considered the tasks of forecasting reliability of modifiable complex information systems. Such systems are subject to modifications during development, testing, and regular functioning.
It is necessary to develop the methods and algorithms of estimating and forecasting various reliability characteristics.
One approach to determine the system reliability is to compute the probability that a signal fed to the input of a system will be processed correctly by the system.
In this article we've considered the exponential recurrent growth model of reliability. In such model the probability is represented as a linear combination of the “effectiveness” and “defectiveness” parameters.
“Effectiveness” is the weight parameter responsible for increasing in the system reliability.
“Defectiveness” is the weight parameter responsible for decreasing in the system reliability.
These parameters are random variables.
It is assumed that the researcher does not have exact information about the system. He is only familiar with the characteristics of the class from which this system is taken.
----------------------------------------------
We've done the patents on the software system of the Institute of Informatics Problems of the Academy of Sciences.
It is the software system of modeling and analysis Bayesian recurrent reliability growth model for "effectiveness" and defectiveness" parameters.
This software system is the special module designed to calculate the average marginal probability of the reliability of the complex modified information systems for the different distributions of the “defectiveness” and “defectiveness” parameters.
Average marginal system reliability has been calculated. Numerical results for model examples have been obtained.
Language: English
Language Skills: Native speaker, Proficiency
It is necessary to develop the methods and algorithms of estimating and forecasting various reliability characteristics.
One approach to determine the system reliability is to compute the probability that a signal fed to the input of a system will be processed correctly by the system.
In this article we've considered the exponential recurrent growth model of reliability. In such model the probability is represented as a linear combination of the “effectiveness” and “defectiveness” parameters.
“Effectiveness” is the weight parameter responsible for increasing in the system reliability.
“Defectiveness” is the weight parameter responsible for decreasing in the system reliability.
These parameters are random variables.
It is assumed that the researcher does not have exact information about the system. He is only familiar with the characteristics of the class from which this system is taken.
----------------------------------------------
We've done the patents on the software system of the Institute of Informatics Problems of the Academy of Sciences.
It is the software system of modeling and analysis Bayesian recurrent reliability growth model for "effectiveness" and defectiveness" parameters.
This software system is the special module designed to calculate the average marginal probability of the reliability of the complex modified information systems for the different distributions of the “defectiveness” and “defectiveness” parameters.
Average marginal system reliability has been calculated. Numerical results for model examples have been obtained.
Login or register to correct this text!
You can correct this text if you set follow language skills of English in settings: Native speaker, Proficiency
You can correct this text if you set follow language skills of English in settings: Native speaker, Proficiency
Please correct texts in English:
Please help with translation:
Arabic Armenian Azerbaijan Basque Belorussian Bosnian Bulgarian Catalan Chinese Croatian Czech Danish Dutch English Esperanto Estonian Finnish French Georgian German Greek Gujarati Hebrew Hindi Hungarian Icelandic Indonesian Italian Japanese Javanese Kazakh Korean Kyrgyz Latin Latvian Macedonian Malay Mongolian Norwegian (bokmal) Norwegian (Nynorsk) Persian Polish Portuguese Romanian Russian Sanskrit Serbo-Croatian Slovak Spanish Swedish Tatar Thai Turkish Ukrainian Uzbek Vietnamese Welsh