Proceedings of the First International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’16)
This volume of Advances in Intelligent Systems and Computing contains papers presented in the main track of IITI 2016, the First International Conference on Intelligent Information Technologies for Industry held in May 16-21 in Sochi, Russia. The conference was jointly co-organized by Rostov State Transport University (Russia) and VŠB – Technical University of Ostrava (Czech Republic) with the participation of Russian Association for Artificial Intelligence (RAAI) and Russian Association for Fuzzy Systems and Soft Computing (RAFSSC). The volume is devoted to practical models and industrial applications related to intelligent information systems. The conference has been a meeting point for researchers and practitioners to enable the implementation of advanced information technologies into various industries. Nevertheless, some theoretical talks concerning the-state-of-the-art in intelligent systems and soft computing are included in the proceedings as well.
There are many applications where the comparison of histograms (discrete random variables, fuzzy set on discrete universal set) is required with the help of relationship of type ”more-less”. There are many approaches to solving this problem. The relations between some popular stochastic and fuzzy orderings are investigated in the article. The simple formulas for calculating the number of comparisons obtained, as well as established relationships between the various comparisons. The new approach for comparison of histogram is proposed in this paper too. This approach is based on the calculation of minimum directional transform of one histogram in another histogram.
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