Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
The safe development of chemical industries requires adequate control of the environmental sustainability of the areas where enterprises are located. The purpose of the article is to develop and test a methodology for solving the multicriteria problem of choosing industrial zones for the development of chemical industries using the method of an additive global criterion. The novelty of the methodology lies in the multi-criteria and complexity of the tool and the presence of a statistical base, which allows it to be used for various socio-economic purposes at all levels of government. As the main research tools, the methods of multi-criteria selection of objects, one-dimensional data scaling, additive convolution of criteria, and methods of multivariate statistical analysis for verifying the results obtained and making a decision were used. The article describes the mathematical apparatus of the technique for solving the multicriteria problem of selecting objects by the method of an additive global criterion. The solution algorithm provides for a three-level integration of particular indicators using the methods of mathematical processing of an array of different-dimensional values. The procedure for selecting the vectors of the criterion space makes it possible to select industrial zones and obtain a global criterion using the additive convolution method. In order to test the methodology, the problem of choosing industrial zones for the potential development of chemical industries in the Russian region was solved. For the development of chemical production, industrial zones have been selected that are included in the above-average environmental sustainability group: Bavlinskaya, Nurlatskaya, Bugulminskaya, and Leninogorskaya. Tendencies of decrease in ecological stability of the zones, which have relatively safe industries on their territory but are adjacent to the zones of location of environmentally unfavorable industries, are revealed. The materials of the article can be used in the development of intelligent systems for monitoring and controlling the development of chemical industries, which allow monitoring the level of environmental safety of industrial zones, identifying sources of negative environmental impact with pursuing decision-making on the organization and planning of production systems in the territorial space.
The safe development of chemical industries requires adequate control of the environmental sustainability of the areas where enterprises are located. The purpose of the article is to develop and test a methodology for solving the multicriteria problem of choosing industrial zones for the development of chemical industries using the method of an additive global criterion. The novelty of the methodology lies in the multi-criteria and complexity of the tool and the presence of a statistical base, which allows it to be used for various socio-economic purposes at all levels of government. As the main research tools, the methods of multi-criteria selection of objects, one-dimensional data scaling, additive convolution of criteria, and methods of multivariate statistical analysis for verifying the results obtained and making a decision were used. The article describes the mathematical apparatus of the technique for solving the multicriteria problem of selecting objects by the method of an additive global criterion. The solution algorithm provides for a three-level integration of particular indicators using the methods of mathematical processing of an array of different-dimensional values. The procedure for selecting the vectors of the criterion space makes it possible to select industrial zones and obtain a global criterion using the additive convolution method. In order to test the methodology, the problem of choosing industrial zones for the potential development of chemical industries in the Russian region was solved. For the development of chemical production, industrial zones have been selected that are included in the above-average environmental sustainability group: Bavlinskaya, Nurlatskaya, Bugulminskaya, and Leninogorskaya. Tendencies of decrease in ecological stability of the zones, which have relatively safe industries on their territory but are adjacent to the zones of location of environmentally unfavorable industries, are revealed. The materials of the article can be used in the development of intelligent systems for monitoring and controlling the development of chemical industries, which allow monitoring the level of environmental safety of industrial zones, identifying sources of negative environmental impact with pursuing decision-making on the organization and planning of production systems in the territorial space.
Nowadays, there are too many large-scale speech recognition resources, which makes it difficult to ensure the scheduling speed and accuracy. In order to improve the effect of large-scale speech recognition resource scheduling, a large-scale speech recognition resource scheduling system based on grid computing is designed in this paper. In the hardware part, microprocessor, Ethernet control chip, controller and acquisition card are designed. In the software part of the system, it mainly carries out the retrieval and exchange of information resources, so as to realize the information scheduling of the same type of large-scale speech recognition resources. The experimental results show that the information scheduling time of the designed system is short, up to 2.4min, and the scheduling accuracy is high, up to 90%, in order to provide some help to effectively improve the speed and accuracy of information scheduling.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.