Özet:

The object of the study is decision support systems. A methodology for evaluating information and analytical support in decision support systems was developed. The method consists of the main stages: assessment of the type of uncertainty about the state of the analysis object, calculation of criteria and determination of development options, determination of system reaction time, formation of the initial scenario. The next steps are establishing the target state of the object, analyzing options for influencing the analysis object, obtaining intermediate target states of the analysis object, and determining options for the development of the analysis object. The method was developed because of the need to process more information and has a moderate computational complexity. It was found that the proposed method has a computational complexity of 10–15 % lower compared to the methods for evaluating the effectiveness of management decisions. This method will allow assessing the state of information and analytical support and determining effective measures to increase efficiency. The method will allow analyzing possible options for the development of the assessment object in each development phase and the moments in time when it is necessary to carry out structural changes that ensure the transition to the next phase. In this case, subjective factors of choice are taken into account while searching for solutions, which are formalized in the form of weights for the components of the integral efficiency criterion. The maximization of the criteria, calculated taking into account the preferences, makes it possible to determine the best option for the development of the assessment object. The method allows increasing the speed of assessment of the state of information and analytical support, reducing the use of computing resources of decision support systems, developing measures aimed at increasing the efficiency of information and analytical support Author Biographies Qasim Abbood Mahdi, Al-Taff University College PhD, Head of Department Department of Computer Technologies Engineering

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