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

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...

Intelligent support for managing the processing of ore raw materials based on case management and ontological models

The article discusses the possibility of applying a precedent approach to improve the efficiency of control of thermophysical and chemical-energy-technological processes of processing ore raw materials. As an example, one of the variants of such processes is considered – heat treatment of pelletized phosphate raw materials. To form the knowledge base of an intelligent system, it is proposed to jointly use a compositional ontological model, which includes two ontologies, each of which is focused on describing one of the subject areas under consideration: thermophysical and chemical-energy-technological processes of heat treatment of pelletized phosphate ore processing plants. The use of this model makes it possible to take into account both the specific properties and characteristics of the processes under consideration, as well as unique tasks and management indicators, avoiding the need to form a generalized holistic ontology that would reflect these subject areas in a simplified form. The use of a compositional ontological model also makes it possible to store information not only in quantitative but also in qualitative form. To form solutions to provide support for the processes of managing the processing of ore raw materials, it is proposed to use a new modified case-based approach, which consists in the possibility of working with the proposed compositional ontological model in determining the closest solution to the current situation, as well as the formation of quantitative values of these decisions based on the information presented in linguistic form. It is possible to take into account the degree of significance of each of the ontologies when developing solutions for each individual current situation that arises when managing the processing of ore raw materials. Read more...

Fuzzy dynamic ontological model for decision support of energy-intensive systems management based on precedents

The article discusses the features of applying the precedent approach when managing complex energy-intensive systems in the context of the need to take into account various energy, technical, environmental and operational indicators, as well as the uncertainty of many internal and external factors influence. This leads to the presence of a large amount of semi-structured information that can be presented using various scales, which determines the prospects of using the precedent approach. The proposed fuzzy ontological model for supporting decision support based on precedents is described, characterized by the use of dynamic concepts, as well as concepts in the form of different scale numerical and linguistic variables. An algorithm for assessing the proximity of precedents based on an ontological model is proposed, which differs by taking into account the dynamic aspects of changes in the state of controlled systems. The developed algorithms for fuzzy inference for decision support based on precedents are presented, which allow the use of both linguistic and numerical variables as input characteristics of the fuzzy production model, as well as using various logical connections between the rules pre-requisites. The software that implements the developed model and algorithms is described. Particular attention is paid to the modified fuzzy inference component, implemented using Python 3.8.7 language tools. To implement the user interface of the specified component, the cross-platform graphic library Tkinter was used. The results of computational experiments using real data obtained during the operation of an energy-intensive system for processing fine ore raw materials, including a conveyor-type roasting machine, are presented. Minimization of specific total costs for thermal and electrical energy was considered as a criterion for the effectiveness of management decisions. The outcome obtained showed that the proposed model and software make it possible to obtain a result comparable to the one of using complex analytical dependencies, while ensuring a reduction in time and financial costs. Read more...