Abstract
The article considers the tasks of intellectual support for decision support in relation to a complex technological object. The relevance is determined by a high level of responsibility, together with a variety of possible situations at a complex technological facility. The authors consider case-based reasoning (CBR) as a method for decision support. For a complex technological object, the problem defined is the uniqueness of the situations, which is determined by a variety of elements and the possible environmental influence. This problem complicates the implementation of CBR, especially the stages of comparing situations and a further selection of the most similar situation from the database. As a solution to this problem, the authors consider the use of neural networks. The work examines two neural network architectures. The first part of the research presents a neural network model that builds upon the multilayer perceptron. The second part considers the “Comparator-Adder” architecture. Experiments have shown that the proposed neural network architecture “Comparator-Adder” showed higher accuracy than the multilayer perceptron for the considered tasks of comparing situations. The results have a high level of generalization and can be used for decision support in various subject areas and systems where complex technological objects arise.
Highlights
The results have a high level of generalization and can be used for decision support in various subject areas and systems where complex technological objects arise
The purpose of this work is to develop and research neural network architecture to evaluate the similarity of situations on a complex technological object of urban infrastructure
In the course of the experiments, the concatenation of two vectors (x, y) with a total length of 224 positions was fed to the input of the neural network
Summary
Modern systems of urban infrastructure (power supply systems, gas, water, and heat supply systems) are complex technological objects (CTO). Their safety and stability processes are important for to enable city systems, and for the protection of the ecology, people’s lives, and health. The emergency situation has dangerous and fatal consequences The prevention of such situations and their removal represent a relevant task in managing complex technological objects. The dangerous situation prevention relates to monitoring and recognition and to retrieving solutions for neutralizing an incident The implementation of both tasks in one software–hardware complex leads to the modern concept of intelligence monitoring and decision-making systems (IMDS) [1]. The decision-making process to neutralize (prevent) an arising dangerous situation is aimed at finding an action program (for personnel of operating, service organizations, operational dispatch service, and support services), which should convert the current emergency situation into a target, standard situation
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