The relevance of developing knowledge-based systems used to support innovative processes for creating products and services is related to the objective need to reduce the life cycle of products under the influence of modern digital technologies in developing network enterprises. Well-known research results in the field of model-oriented design of products, processes, systems and enterprises do not fully provide semantic interoperability in the interaction of stakeholders in the innovation process. The aim of this work is to build a knowledge-based system architecture that implements semantic interoperability of network enterprise participants at various stages of the product lifecycle. The work is based on the use of a model-oriented approach to building a digital thread at all stages of the product lifecycle, an ontological approach to semantic modeling of a distributed knowledge base and a multiagent approach to organizing interaction between interested participants in the innovation process. The paper proposes a functional architecture of a knowledge-based system that includes modules for planning the innovation process, forming product value characteristics and functional requirements, construction and value chain design. A multi-level system of ontologies of the innovation process is also developed and its application in the work of functional modules that provide access to associated knowledge bases is described. The development of knowledge-based systems based on the results obtained will allow us to find the best design solutions for the configuration of products and corresponding value chains due to the possible iteration of the innovation process and increasing the semantic interoperability of network enterprise stakeholders.

The subject of the study  is the formation of the structure of a network enterprise, considered as a set of interacting enterprises in a networked Internet environment that implements a value chain. To build the structure of the network enterprise, it is proposed to use and support the ontology of the network enterprise, which conceptually reflects the models of products and related production and business processes throughout the life cycle. At the same time, the focus is on the implementation of flexible processes for creating innovative products using intelligent model-oriented technologies.The purpose of the study  is to build an algorithm for forming the structure of a network enterprise that would ensure the best implementation of the value chain with minimal risks of mismatch of designs and production processes with qualitative value characteristics and requirements for an innovative product. The construction of an algorithm for forming the structure of a network enterprise involves solving the problems of modeling the structure of an innovative product based on an analysis of qualitative value characteristics and requirements for product components, its creation processes, distribution of roles of enterprise participants and analysis of their capabilities.Methods. As the main research method is the method of constructing a model of “digital thread” of creating an innovative product. The most complete application of this method is carried out as part of the reference model of enterprise architecture for Industrie 4.0 (RAMI). The resulting conceptual model of an innovative product and related production and business processes is implemented using an ontological approach. It is proposed to use a combination of QFD (Quality Function Deployment) methods for deploying the structure of a network enterprise and analyzing the types and consequences of potential FMEA (Failure Mode and Effects Analysis) inconsistencies.The main results of the study are ontology and the algorithm for forming the structure of the network enterprise. A distinctive feature of the proposed ontology of the network enterprise is a clear separation of the valuable qualitative characteristics of the product and the requirements for its creation, as well as the allocation of the abilities of participants in enterprises to implement the necessary processes. The novelty of the presented algorithm for the formation of the structure of a network enterprise lies in the combined application of the QFD and FMEA methods, as well as in the iteration of modeling the structure of an innovative product from the position of the best implementation of quality value characteristics and functional requirements.Conclusions, prospects. The proposed algorithm for creating the structure of a network enterprise allows you to get the best decisions on the criterion for assessing the highest rating for the implementation of quality characteristics and requirements for the components of the value chain and its participants, provided that minimal risk assessments of the mismatch between the designs and processes of creating innovative products are obtained. The developed ontology and the algorithm for forming the structure of the network enterprise is of practical importance for creating an intelligent system for supporting the adoption of innovative decisions for the dynamic construction of network enterprises in the Internet environment.

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The aim of the study is electronic learning systems. They refer to organizational and technical systems and use different approaches and technologies to solve learning problems. In modern conditions, education is becoming one of the main factors for the successful development of countries with the developed economies. Knowledge is beginning to occupy key positions in the life of these countries. Specialists, who have received professional education and want to improve their level of knowledge, are the key resource of the economy. Lifelong education has become a necessary and increasingly dominant element of modern educational systems. Modern distance learning systems are used to solve these problems. The paper deals with electronic distance learning systems and explores the possibility of using cognitive mechanisms for the development of educational technologies.Materials and methods. Ongoing education requires new approaches and technologies that fit well into distance learning systems. These systems use the following approaches and technologies: service-oriented architectures, cloud technologies and virtualization, intelligent dynamic systems, multi-agent systems, ontologies, evolving knowledge. The authors use machine learning technologies and agent-oriented approach to apply cognitive mechanisms. Integrated methods of knowledge representation are used to describe the reality. Using these approaches and methods, the authors consider the development and construction of modules of intelligent learning systems with the integration of computer paradigm and cognitive mechanisms.Results.The article presents an example of the development and use of educational resources for learning a foreign language in a technical University. The electronic course is created in the distance learning system Moodle. The result of testing students after studying the definite topic is shown. The article considers the structure of hardware and software modules for the formation of concepts from the sensual images of objects and phenomena of reality. Hardware-software modules are presented, which are necessary for the formation of concepts-representations from a variety of sensory mappings of control actions. A demo example of the formation of the concept scenarios and a fragment of the knowledge base containing the generated concept scenario are given.Conclusion.The use of distance learning system Moodle allows students to work out the current material of the course. This material can be worked out by students independently and repeatedly, till their full understanding and achievements of skill. Testing after each studied topic allows assessing the level of knowledge and the success of the current training of the definite course units. The considered approaches for the formation of concepts-representations and concepts-scenarios open up opportunities for the use of cognitive mechanisms. These approaches make it possible to use generalized knowledge in intelligent systems for the formation of new solutions for targeted behavior. Such approaches can be used both in training systems for the assimilation of new knowledge and in simulators of advanced systems for the formation of skills. Cognitive technologies can be used in social communities of agents.

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