Method for Clustering and Identification of Elements of Real Engineering Sites on The Basis of Dynamic Logic
LEONID I. PERLOVSKY · Biomedical Journal of Scientific & Technical Research · 2020
Currently there is a contradiction between availability of various new equipment, which provides a stream of digital video data, in particular in the form of point clouds from mobile laser scanning, and the lack of adequate efficient methods of information extraction and analysis.This project is aimed at resolving this contradiction on the basis of neural modeling field theory and dynamic logic (DL) proposed by L. I. Perlovsky.The main result of the project will be a method of extracting information from digital video data in the form of hybrid clouds of mobile laser scanning data points for their analysis based on neural modeling field theory and DL.The success of this project depends on the successful integration of approaches from various fields of science and technology (interdisciplinarity): artificial intelligence, pattern and object recognition, logic, algorithm theory.The significance of the development of the proposed method is to create a fundamental theoretical basis for new application algorithms and software in the field of autonomous driving, "smart city" projects, ensuring safety for sites of various purposes, etc.The scientific novelty of the proposed method is that it will solve, by a fairly new method, the relevant problem of extracting and analyzing information from a not particularly traditional type of digital video data represented by a hybrid cloud of laser scanning points.This will allow to significantly expand the existing boundaries of knowledge in the field of extraction and analysis of information from various digital video data.The main hypothesis of the research is that the new method based on L. I. Perlovsky's neural modeling field theory and DL will improve the performance of relevant calculations and close the existing gaps in the use of various digital video data.