Forecasting of energy-related carbon dioxide emission using ANN combined with hybrid metaheuristic optimization algorithms

IF 5.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Engineering Applications of Computational Fluid Mechanics Pub Date : 2024-02-29 DOI:10.1080/19942060.2024.2322509

Hossein Moayedi, Azfarizal Mukhtar, Nidhal Ben Khedher, Isam Elbadawi, Mouldi Ben Amara, Quynh TT, Nima Khalilpoor

引用次数: 0

Abstract

Energy-related CO2 emissions are one of the biggest concerns facing urban design today, increasing rapidly as cities grow. This study uses as inputs the GDP of the G8 nations (from 1990 to 2016) de...

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使用ANN结合混合元启发式优化算法预测与能源相关的二氧化碳排放量

与能源相关的二氧化碳排放是当今城市设计面临的最大问题之一，并随着城市的发展而迅速增加。本研究以 G8 国家（1990-2016 年）的 GDP 为输入数据，对城市设计中与能源相关的二氧化碳排放量进行了分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Engineering Applications of Computational Fluid Mechanics ENGINEERING, MULTIDISCIPLINARY-ENGINEERING, MECHANICAL

CiteScore

10.60

自引率

14.80%

发文量

109

审稿时长

3.4 months

期刊介绍： The aim of Engineering Applications of Computational Fluid Mechanics is a continuous and timely dissemination of innovative, practical and industrial applications of computational techniques to solve the whole range of hitherto intractable fluid mechanics problems. The journal is a truly interdisciplinary forum and publishes original contributions on the latest advances in numerical methods in fluid mechanics and their applications to various engineering fields including aeronautic, civil, environmental, hydraulic and mechanical. The journal has a distinctive and balanced international contribution, with emphasis on papers addressing practical problem-solving by means of robust numerical techniques to generate precise flow prediction and optimum design, and those fostering the thorough understanding of the physics of fluid motion. It is an open access journal.