About reasonable number of rankings in preference profile when measuring quality / S. V. Muravyov (Murav’ev)

Основной Автор-лицо: Muravyov (Murav’ev), S. V., specialist in the field of control and measurement equipment, Professor of Tomsk Polytechnic University,Doctor of technical sciences, 1954-, Sergey VasilyevichКоллективный автор (вторичный): Национальный исследовательский Томский политехнический университет (ТПУ), Институт кибернетики (ИК), Кафедра компьютерных измерительных систем и метрологии (КИСМ)Язык: английский.Резюме или реферат: To plan the quality measuring in the form of consensus relation determination for the given m weak order relations (rankings) it is necessary to know a reasonable number of the rankings. If a ranking is produced by an expert then the number of rankings is equal to number of experts. It is proposed to estimate the expert number using simple probabilistic Bernoulli model, where m experts reveal defects (demerits) of an object. The model assumes that the more the number of an expert group participants, the less the probability of a new defect revealing. Based on this assumption, the probability decrease have been evaluated and graphically presented. The investigations allow to suppose that the number of rankings in preference profile can be from 4 to 10 for typical applications..Тематика: электронный ресурс | труды учёных ТПУ | quality measurement | ordinal scale measurement | number of weak orders | number of experts Ресурсы он-лайн:Щелкните здесь для доступа в онлайн
Тэги из этой библиотеки: Нет тэгов из этой библиотеки для этого заглавия. Авторизуйтесь, чтобы добавить теги.
Оценка
    Средний рейтинг: 0.0 (0 голосов)
Нет реальных экземпляров для этой записи

Title screen

To plan the quality measuring in the form of consensus relation determination for the given m weak order relations (rankings) it is necessary to know a reasonable number of the rankings. If a ranking is produced by an expert then the number of rankings is equal to number of experts. It is proposed to estimate the expert number using simple probabilistic Bernoulli model, where m experts reveal defects (demerits) of an object. The model assumes that the more the number of an expert group participants, the less the probability of a new defect revealing. Based on this assumption, the probability decrease have been evaluated and graphically presented. The investigations allow to suppose that the number of rankings in preference profile can be from 4 to 10 for typical applications.

Для данного заглавия нет комментариев.

оставить комментарий.