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Bayesian Belief Networks in Risky Behavior Modelling
P. 95–102.
Suvorova A., Tulupyeva T.
The area of risky behavior modelling has unsolved issues in current practice: there is a need for numerical estimates of risky behavior rate. We propose the approach for risky behavior modelling in terms of Bayesian Belief Networks on the base of the data about behavior episodes. The paper includes the description of the model, results of model testing on automatically generated dataset and discussion of possible further development
In book
Vol. 450. Issue 1. , Springer, 2016.
Хломов К. Д., Bochaver A. A., Психология и право 2021 Т. 11 № 3 С. 15–32
Risky sexual behavior is the most complicated form of antisocial risky teenage behavior, both in its manifestations and in terms of availability for study and interventions. Sexual behavior and romantic relationships of teenagers are viewed, on the one hand, as important developmental stages, encouraging one's positive psychosocial adaptation, on the other hand, as an element ...
Added: September 30, 2021
Suvorova A., , in: CEUR Workshop ProceedingsVol. 2258: Proceedings of the II International Scientific and Practical Conference “Fuzzy Technologies in the Industry – FTI 2018”.: Ulyanovsk: CEUR Workshop Proceedings, 2018. P. 63–70.
Decision making in many areas is based on data about individual behavior often measured using different surveys. The study investigates the proposed approach for behavior modelling on the base of Bayesian belief networks that allows predicting behavior characteristics using small and incomplete data from surveys about behavior episodes. We explored the characteristics of the models ...
Added: February 10, 2020
Suvorova A., Тулупьев А. Л., В кн.: Нечеткие системы и мягкие вычисления. Промышленные применения. Fuzzy Technologies in the Industry (FTI-2017): Первая Всероссийская научно-практическая конференция.: Ульяновск: УлГТУ, 2017. С. 170–177.
The paper presents an approach for dealing with imprecise data in risky behavior modelling based on Bayesian belief network. We conducted computational experiments to compare behavior rate predictions according to both initial and corrected data. The data randomization presented better prediction quality compared to initial method. ...
Added: February 10, 2020
Suvorova A., Tulupyev A., , in: Atlantis Studies in Uncertainty Modelling, Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (EUSFLAT 2019)Vol. 1.: Atlantis Press, 2019. P. 648–652.
Added: October 22, 2019
Suvorova A., Тулупьев А. Л., , in: Advances in Intelligent Systems and Computing. 3rd International Scientific Conference on Intelligent Information Technologies for Industry, IITI 2018Vol. 2.: Springer, 2019. P. 58–67.
Bayesian Belief Networks (BBN) provide a comprehensible framework for representing complex systems that allows including expert knowledge and statistical data simultaneously. We explored BBN models for estimating risky behavior rate and compared several network structures, both expert-based and data-based. To learn and evaluate models we used generated behavior data with 9393 observations. We applied both ...
Added: January 28, 2019
Suvorova A., , in: XX IEEE International Conference on Soft Computing and Measurements (SCM).: IEEE, 2017. P. 87–89.
The paper described the structure comparison of Bayesian Belief Network models for individual behavior rate estimate based on data about the last episodes of that behavior. We compared two types of network structures: expert-based and data-based. For model learning and evaluation we used data from social network VKontakte about episodes of publishing posts. The sample ...
Added: October 2, 2018
Suvorova A., Tulupyev A., , in: Proceedings of the XIX International Conference on Soft Computing and Measurements SCM`2016.: St. Petersburg: IEEE, 2016. P. 18–20.
The paper described the Bayesian belief network model for individual behavior rate estimate based on data about the last episodes of that behavior. For model evaluation we used data from social network VKontakte about episodes of publishing posts. The sample size is 1123 users with 160555 posts in total for the half-year period. Rate values ...
Added: September 26, 2016
Toropova A. V., Suvorova A., , in: Proceedings of the XIX International Conference on Soft Computing and Measurements SCM`2016.: St. Petersburg: IEEE, 2016. P. 14–17.
The purpose of the paper is to offer an instrument for data coherence diagnosis in socially significant behavior model. Problem of initial data coherence is considered. Data coherence diagnosis method is proposed. For more convenient use a software is developed. Examples of its using are shown. Obtained results can be used in different research fields, ...
Added: September 26, 2016
Tulupyev A., Suvorova A., Sousa J. et al., Statistics in Medicine 2013 Vol. 32 No. 23 P. 4044–4056
Our aim is to model the frequency of certain behavioral acts, especially those that are likely to transmit communicable diseases between persons. We develop a generalized linear model based on the beta prime distribution to model the responses to a survey question of the form, “When was the last time that you engaged in this ...
Added: March 26, 2015