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Chernovalova M.

Postgraduate student, National Research University MPEI

Algorithmic and information support of innovative project management in conditions of uncertainty

The article presents the features of innovative projects of industrial enterprises that complicate the process of their management. The main groups of mathematical methods used to manage innovative projects are identified. The possible directions of further developing mathematical methods in the field of managing the complex innovative projects at industrial enterprises are determined. Algorithms of accounting the influence of uncertainty factors on the duration and costs that associate with implementing the innovation project works are presented. A distinctive feature of these algorithms is the usage of fuzzy production rules. These rules formulate recommendations for managing these projects based on the distribution of resources available in the organization depending on the results of each stage. It allows minimizing the execution time, both individual stages, and the entire innovation project as a whole. The variant of information support formation is offered that is presented in the form of a physical model of the database. This model allows storing all the information available in the industrial organization that necessary to manage these projects. A distinctive feature of this database is the ability to store information on the impact of uncertainties on the implementation effectiveness in a formalized form. This information is necessary for the implementing the developed algorithms.

Fuzzy cognitive modeling of heterogeneous electromechanical systems

The article presents a method of fuzzy cognitive modeling for heterogeneous electromechanical systems (HEMSs) in the management of innovative design solutions. During the operation of the HEMSs, as a result of their operational aging, the properties of the windings parametric matrices and the HEMSs vector space properties change. Periodic testing of the HEMSs vector space allows obtaining reliable information about the current technical condition of the HEMSs, about its changes during operation and about the risks of operating capability loss. At the same time (I) the presence of proportional changes in signals during sequential testing indicates the homogeneous operational aging of the HEMSs and its rate; (II) a disproportionate change in one of the signals indicates the damage or the development of a heterogeneous aging process; (III) a change in signals with a change in the angular position of the rotor indicates worn bearings or damage of the HEMSs rotor. The article presents the HEMSs model, describes the method for the topological research of the vector space and the method for forming the diagnostic matrices. The deviations of their elements are fuzzy due to the uncertainty of the load, influencing environmental factors and unstable supply voltages. Therefore, for predictive estimation of the HEMSs state, it is proposed to use fuzzy relational cognitive models that allow implementing a completely fuzzy approach to modeling problem situations in these systems. The presented data confirm the growth of the HEMSs heterogeneity under conditions of uncertainty of external influences. The proposed method for predictive estimation of the HEMSs state, based on fuzzy relational cognitive models, provides resistance to an increase in the uncertainty of the estimation results for various models of system dynamics due to a reasonable set of fuzzy vector-matrix operations. Read more...

Fuzzy case models for project management using a multi-ontology approach

The article identifies the features of innovative projects that should be taken into account when building models of information processes in decision support systems (DSS) for project management. It is shown that, in terms of taking into account these features, methods for forming knowledge in the form of ontologies and the use of information analysis procedures based on precedent methods seem to be promising. The limitations of existing precedent methods, including those involving the formation of a knowledge base in the form of ontologies for their use in project management, are revealed. Development trends in methods for representing knowledge in the form of ontologies and their use within the framework of precedent approaches are substantiated. The trends are as follows: providing the ability to use several independent ontologies for different subject areas; taking into account the differences of the analyzed projects and creating conditions for the adaptation of ontologies when the indicators of the external and internal environments of the project change. A DSS structure for project management is proposed, which provides the use of several subject and functional ontologies and a developed fuzzy logic algorithm for adapting earlier rational decisions to the current situation. Software tools implementing the proposed models and procedures are described, as well as the results of their application to decision support in managing a project to develop an innovative asynchronous electric motor. It is shown that the proposed approach allows the description of the current situation in a linguistic form. At the same time, in contrast to the known variants of precedent methods based on the use of ontological models, the described algorithm for deriving solutions allows taking into account the characteristics of the analyzed situations related to various subject and functional areas. This allows you to develop recommendations for the allocation of resources for the implementation of design work based on the analysis of positive experience in the implementation of projects of various sizes. Read more...

Algorithms and soft for adapting the knowledge base of project management information systems

The effectiveness of design solutions largely depends on the promptness of processing a large amount of data from various sources, which determines the feasibility of using information decision support systems (IDSS) in the field of project management. The peculiarities of information processes in project management greatly complicate or even make it impossible to implement in practice methods for constructing analytical, as well as probabilistic and statistical dependencies between the characteristics of the modeled project management system and the indicators of its internal and external environment. In this regard, as an algorithmic support for IDSS for project management, it is promising to use precedent methods for analyzing information based on knowledge about similar situations previously observed in the practice of project management, and representing knowledge in the form of ontologies. Analysis of practical situations in the field of project management makes it possible to substantiate the expediency of organizing a monitoring procedure for the IDSS knowledge base, based on the results of which decisions on its adaptation are made. The article proposes the main ways of this adaptation: changing the structure and basic elements (first of all, concepts) of ontologies; clarification of the structure of the description of current situations and, therefore, precedents. The developed algorithm for monitoring the IDSS knowledge base on project management for the analysis and identification of typical situations of the feasibility of changing it is described. The algorithm is distinguished by the possibility of developing recommendations on the modification of ontologies based on a fuzzy classification of search results and using precedents relevant to current situations. A procedure is proposed for changing the structure of the description of precedents, taking into account the results of assessing the indices of the fuzzy correspondence of the characteristics of the existing precedents to the characteristics of the project being implemented. A description of a computer program that implements the proposed algorithm and its components, as well as the results of its application are given. Read more...