DOI

An approach to the sensitivity analysis of local a posterior inference equations in algebraic Bayesian networks is proposed in the paper. Performed a sensitivity analysis of first a posterior inference task for stochastic and deterministic evidences propagated into the knowledge pattern with scalar estimates. For each of the considered cases the necessary metrics are chosen and transformations are carried out, that result into a linear programming problem. In addition, for each type of evidence theorems that postulate upper sensitivity estimates are formulated and proofs are provided. Theoretical results are implemented in CSharp using the module of probabilistic-logical inference software complex. A series of computational experiments is conducted. The results of experiments are visualized using tables and charts. The proposed visualization demonstrates the high sensitivity of the considered models, that confirms the correctness of their use.

Язык оригиналаанглийский
Название основной публикацииProceedings of the 2nd International Scientific Conference on Intelligent Information Technologies for Industry, IITI 2017
РедакторыSergey Kovalev, Andrey Sukhanov, Margreta Vasileva, Valery Tarassov, Vaclav Snasel, Ajith Abraham
ИздательSpringer Nature
Страницы34-42
Число страниц9
ISBN (печатное издание)9783319683201
DOI
СостояниеОпубликовано - 1 янв 2018
Событие2nd International Conference on Intelligent Information Technologies for Industry, IITI 2017 - Varna, Болгария
Продолжительность: 14 сен 201716 сен 2017

Серия публикаций

НазваниеAdvances in Intelligent Systems and Computing
Том679
ISSN (печатное издание)2194-5357

конференция

конференция2nd International Conference on Intelligent Information Technologies for Industry, IITI 2017
Страна/TерриторияБолгария
ГородVarna
Период14/09/1716/09/17

    Предметные области Scopus

  • Системотехника
  • Компьютерные науки (все)

ID: 36984823