Application of Information Technologies and Programming Methods of Embedded Systems for Complex Intellectual Analysis

An information model is outlined, which represents an intelligent system of metallographic analysis in the form of a set of subsystems, the interaction of which ensures the performance of metallographic analysis functions. The structure of the information storage subsystem for metallographic analysis is presented. The deployment model of an intelligent metallographic analysis system is proposed and described. The paper outlines the approach to the presentation of an expert subsystem for metallographic quality control of metals based on a neural network. The process of finding a close precedent in metallographic analysis with reference to a multilayer neural network is described. An intelligent metallographic analysis system is described, which based on proposed information model. A specialized software of an intelligent metallographic analysis system is presented. The functioning results of the developed system for processing images of steel microstructures to determine the steel quantitative parameters is presented.

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A neural network as a quality control monitor of an intelligent system

Proceedings of the 1995 ACM symposium on Applied computing - SAC '95 ◽

10.1145/315891.315977 ◽

1995 ◽

Cited By ~ 1

Author(s):

Ray R. Hashemi ◽

John R. Talburt ◽

Meena Velusamy

Keyword(s):

Neural Network ◽

Quality Control ◽

Intelligent System

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Improving the Safety of Power Plants by Developing a Digital Twin and an Expert System for Adaptive-Predictive Analysis of the Operability of Gas Turbine Units

Volume 6: Education; Electric Power ◽

10.1115/gt2020-14217 ◽

2020 ◽

Author(s):

Roman Polyakov ◽

Eugenii Paholkin ◽

Igor Kudryavcev ◽

Nikolay Krupenin

Keyword(s):

Neural Network ◽

Power Plants ◽

Intelligent System ◽

General Concept ◽

Predictive Analysis ◽

Complex Object ◽

Basic Principles ◽

Digital Twin ◽

Analysis System ◽

Generating Equipment

Abstract The article describes general approaches to creating an intelligent system for monitoring and diagnosing the operability of energy supply facilities. The general concept of the adaptive-predictive analysis system and the construction of an artificial neural network for its use in the predictive module for predicting the type and time of failure occurrence is given. The basic principles of training a neural network for recognizing various types of failures are also given. Critical remarks of the concept of creating a digital twin of such a complex object for modeling as energy-generating equipment are given.

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Research on visual recognition intelligent system of city brand image based on fuzzy theory and regional culture

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189833 ◽

2021 ◽

pp. 1-9

Author(s):

Lin Han ◽

Lu Han

Keyword(s):

Neural Network ◽

Visual Recognition ◽

Intelligent System ◽

Brand Image ◽

Fuzzy Theory ◽

Recognition System ◽

Market Competitiveness ◽

Visual Identity ◽

Fuzzy Neural ◽

Intelligent Recognition

With the rapid development of China’s market economy, brand image is becoming more and more important for an enterprise to enhance its market competitiveness and occupy a favorable market share. However, the brand image of many established companies gradually loses with the development of society and the improvement of people’s aesthetic pursuit. This has forced it to change its corporate brand image and regain the favor of the market. Based on this, this article combines the related knowledge and concepts of fuzzy theory, from the perspective of visual identity design, explores the development of corporate brand image visual identity intelligent system, and aims to design a set of visual identity system that is different from competitors in order to shape the enterprise. Distinctive brand image and improve its market competitiveness. This article first collected a large amount of information through the literature investigation method, and made a systematic and comprehensive introduction to fuzzy theory, visual recognition technology and related theoretical concepts of brand image, which laid a sufficient theoretical foundation for the later discussion of the application of fuzzy theory in the design of brand image visual recognition intelligent system; then the fuzzy theory algorithm is described in detail, a fuzzy neural network is proposed and applied to the design of the brand image visual recognition intelligent system, and the design experiment of the intelligent recognition system is carried out; finally, through the use of the specific case of KFC brand logo, the designed intelligent recognition system was tested, and it was found that the visual recognition intelligent system had an overall accuracy rate of 96.08% for the KFC brand logo. Among them, the accuracy rate of color recognition was the highest, 96.62%; comparing the changes in the output value of the training sample and the test sample, the output convergence effect of the color network is the best; through the comparison test of the BP neural network, the recognition effect of the fuzzy neural network is better.

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