{"title":"复杂烃类混合物化学组成的快速分子重建","authors":"N. A. Glazov, A. N. Zagoruiko","doi":"10.1134/S0040579525601104","DOIUrl":null,"url":null,"abstract":"<p>A new heuristic approach is proposed for significantly faster performance of stochastic molecular reconstruction. Its basis is a two-stage method that combines stochastic reconstruction and entropy maximization reconstruction. In the proposed method, the search for optimal distribution parameters is carried out by solving several relatively simple optimization problems. The proposed method makes it possible to reconstruct the composition of a vacuum gas oil sample at least 100 times faster than the classical approach with genetic algorithms.</p>","PeriodicalId":798,"journal":{"name":"Theoretical Foundations of Chemical Engineering","volume":"58 6","pages":"2053 - 2060"},"PeriodicalIF":0.7000,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fast Molecular Reconstruction of the Chemical Composition of Complex Hydrocarbon Mixtures\",\"authors\":\"N. A. Glazov, A. N. Zagoruiko\",\"doi\":\"10.1134/S0040579525601104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>A new heuristic approach is proposed for significantly faster performance of stochastic molecular reconstruction. Its basis is a two-stage method that combines stochastic reconstruction and entropy maximization reconstruction. In the proposed method, the search for optimal distribution parameters is carried out by solving several relatively simple optimization problems. The proposed method makes it possible to reconstruct the composition of a vacuum gas oil sample at least 100 times faster than the classical approach with genetic algorithms.</p>\",\"PeriodicalId\":798,\"journal\":{\"name\":\"Theoretical Foundations of Chemical Engineering\",\"volume\":\"58 6\",\"pages\":\"2053 - 2060\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2025-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Theoretical Foundations of Chemical Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://link.springer.com/article/10.1134/S0040579525601104\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, CHEMICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theoretical Foundations of Chemical Engineering","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1134/S0040579525601104","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
Fast Molecular Reconstruction of the Chemical Composition of Complex Hydrocarbon Mixtures
A new heuristic approach is proposed for significantly faster performance of stochastic molecular reconstruction. Its basis is a two-stage method that combines stochastic reconstruction and entropy maximization reconstruction. In the proposed method, the search for optimal distribution parameters is carried out by solving several relatively simple optimization problems. The proposed method makes it possible to reconstruct the composition of a vacuum gas oil sample at least 100 times faster than the classical approach with genetic algorithms.
期刊介绍:
Theoretical Foundations of Chemical Engineering is a comprehensive journal covering all aspects of theoretical and applied research in chemical engineering, including transport phenomena; surface phenomena; processes of mixture separation; theory and methods of chemical reactor design; combined processes and multifunctional reactors; hydromechanic, thermal, diffusion, and chemical processes and apparatus, membrane processes and reactors; biotechnology; dispersed systems; nanotechnologies; process intensification; information modeling and analysis; energy- and resource-saving processes; environmentally clean processes and technologies.