津贴(工程)
计量经济学
欧洲联盟
投资(军事)
模糊逻辑
价值(数学)
生产(经济)
排放交易
集合(抽象数据类型)
经济
期限(时间)
碳价格
特征(语言学)
计算机科学
微观经济学
数学
温室气体
统计
运营管理
人工智能
国际经济学
哲学
物理
政治
生物
程序设计语言
法学
量子力学
语言学
生态学
政治学
作者
Katarzyna Rudnik,Anna Hnydiuk-Stefan,Zhixiong Li,Zhixiong Li
标识
DOI:10.1016/j.jclepro.2023.137970
摘要
Accurate price forecasts on the European Union Emissions Trading System (EU ETS) market are of interest to many production and investment entities. The article presents a new approach, which models the most significant determinants by the use of a rule-based model containing facts written in the form of ordered fuzzy numbers, as the description of trends of imprecise values of prices. This approach allows for a qualitative analysis of potential values and directions of EU allowance (EUA) price changes and their trends along with the probability of their occurrence in the future. Article presents a wide set of factors used for the analysis of EUA price conditions and the comparison of the results of various feature selection methods (Hellwig's method, F-test, Neighborhood Component Feature Selection method, RreliefF method). Another scientific value added to the presented research results is a new approach to modeling an influence of the significant determinants for a day-ahead prediction CO2 price in the form of fuzzy rules which contain additional information about the tendencies of value changes. Thanks to a comprehensive approach, improvements to existing methods, and proprietary models, additional information was obtained about the tendencies of EUA price level changes.
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