СИСТЕМА ПІДТРИМКИ ПРИЙНЯТТЯ РІШЕНЬ ДЛЯ АНАЛІЗУ І ПРОГНОЗУВАННЯ СТАНУ ПІДПРИЄМСТВАЗапропоновано процедуру побудови системи підтримки прийняття рішень на основі мережі Байєса, яка надає можливість оцінювати та прогнозувати стан підприємства в умовах впливу збурень довільних типів та різної природи.Ключові слова: система підтримки прийняття рішень, байєсівські мережі, аналіз стану підприємства, стратегічне планування, статистичні дані.
The basic purpose of the work is a study of existing approaches to reinsurance directed towards modeling of distribution and minimization of risk for an insurance portfolio, and forming a strategy for its optimal reinsurance using developed decision support system. A method for a search of optimal reinsurance strategy is proposed. For this purpose statistical models were selected that correspond to the structure and volume of portfolio losses as well as the number of these losses. The simulation model for the total insurance losses is developed. While finding an optimal reinsurance strategy it was taken into consideration the dependence of the load coefficient on a specific form of reinsurance. A numerical study of the dependence between optimal reinsurance strategy and the varying load coefficient has been performed. It was established that taking into consideration of the variable load coefficient for specific risk capital values for an insurance company the stop-loss strategy provides worse results than other forms considered. An architecture and the functional layout for decision support system are proposed, and appropriate software was developed in C#. The decision support system functioning has been illustrated on simulated example. The system will provide a useful instrument for a business analytic to support decision making while selecting a strategy for insurance portfolio in specific conditions.
Context. Because assessing security risks is a complex and complete uncertainty process, and uncertainties are a major factor influencing valuation performance, it is advisable to use fuzzy methods and models that are adaptive to noncomputed data. The formation of vague assessments of risk factors is subjective, and risk assessment depends on the practical results obtained in the process of processing the risks of threats that have already arisen during the functioning of the organization and experience of security professionals. Therefore, it will be advisable to use models that can ade-quately assess fuzzy factors and have the ability to adjust their impact on risk assessment. The greatest performance indicators for solving such problems are neuro-fuzzy models that combine methods of fuzzy logic and artificial neural networks and systems, i.e. “human-like” style of considerations of fuzzy systems with training and simulation of mental phenomena of neural networks. To build a model for calculating the risk assessment of security, it is proposed to use a fuzzy product model. Fuzzy product models (Rule-Based Fuzzy Models/Systems) this is a common type of fuzzy models used to describe, analyze and simulate complex systems and processes that are poorly formalized. Objective. Development of a fuzzy model of quality of security risk assessment and protection of ERP systems through the use of fuzzy neural models. Method. To build a model for calculating the risk assessment of security, it is proposed to use a fuzzy product model. Fuzzy product models are a common kind of fuzzy models used to describe, analyze and model complex systems and processes that are poorly formalized. Results. Identified factors influencing risk assessment suggest the use of linguistic variables to describe them and use fuzzy variables to assess their qualities, as well as a system of qualitative assessments. The choice of parameters was substantiated and a fuzzy product model of risk assessment and a database of rules of fuzzy logical conclusion using the MATLAB application package and the Fuzzy Logic Toolbox extension package was implemented, as well as improved by introducing the adaptability of the model to experimental data by introducing neuro-fuzzy components into the model. The use of fuzzy models to solve the problems of security risk assessment, as well as the concept and construction of ERP systems and the analyzed problems of their security and vulnerabilities are considered. Conclusions. A fuzzy model has been developed risk assessment of the ERP system. Selected a list of factors affecting the risk of security. Methods of risk assessment of information resources and ERP-systems in general, assessment of financial losses from the implementation of threats, determination of the type of risk according to its assessment for the formation of recommendations on their processing in order to maintain the level of protection of the ERP-system are proposed. The list of linguistic variables of the model is defined. The structure of the database of fuzzy product rules – MISO-structure is chosen. The structure of the fuzzy model was built. Fuzzy variable models have been identified.
The problem of correct analysis and mathematical description of financial risks is considered; some uncertainties relevant to the risks analysis are highlighted, and an example is given for the financial process model construction in the form of prognostic distribution. The data used characterize the payment flow within a five year period for a chosen insurance company
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