87978797威尼斯老品牌

成果推介‖李洪敏等:《Knowledge-Based Systems》,Air quality deterministic and probabilistic forecasting system based on hesitant fuzzy sets and nonlinear robust outlier correction

来源:    发布人:   发布时间:2023-12-29   浏览次数:

【按语】威尼斯官网以绿色为底绘就绿色发展,践行“绿水青山就是金山银山”发展理念,奋力打造“两山”理论的理论研究桥头堡,产生了一批高水平且具有社会影响力的研究成果。学院官网建立“成果推介”栏目,以展示威尼斯官网师生的优秀成果,传播威尼斯官网师生在生态文明建设和绿色可持续发展等方面的学术观点,为“筑牢生态屏障、推动绿色发展”提供有益借鉴。


作者:李洪敏,王建州,杨胡方,王颖

题名:Air quality deterministic and probabilistic forecasting system based on hesitant fuzzy sets and nonlinear robust outlier correction

期刊:Knowledge-Based SystemsSCIJCR1TOP期刊、影响因子8.8

摘要:Performing scientific and accurate forecasting and realizing the quantitative description of uncertainties in air quality remain challenging prospects. Because of the strong volatility and uncertainty of air pollutant concentrations, this problem increases in difficulty when multiple requirements are considered. In this study, a novel air quality deterministic and probabilistic forecasting system based on hesitant fuzzy sets and nonlinear robust outlier correction was proposed to realize air quality early warning. The proposed system solves the non-stochastic non-deterministic problem in air quality forecasting considering a novel hesitant fuzzy time series forecasting model wherein the intervals are partitioned by different approaches with optimal weights determined by the multi-objective JAYA algorithm. The forecasting performance is further enhanced with the introduction of a new nonlinear error correction model based on an outlier robust extreme learning machine and multi-objective JAYA algorithm, and the quality of the solution obtained is verified by sensitivity analysis. However, point forecast information alone is not sufficient to facilitate the rational integration of pollution control measures. Therefore, this study conducts probabilistic forecasting and constructs proper prediction intervals based on the optimal distribution of the forecasting residuals. By comparing the results with typical counterparts and comparison models considering multiple metrics, the experimental results confirmed the improvement scheme proposed in this study on the traditional fuzzy time series forecasting method while the effectiveness of applying the proposed system to air quality early warning was confirmed as well.


作者简介:

李洪敏,东北林业业大学87978797威尼斯老品牌副教授,应用经济学科经济统计专业负责人,东北财经大学统计学博士。研究方向为统计预测与决策,机器学习及其应用,主要从事空气质量评估,空气污染预警,能源经济研究。在《Applied Mathematical Modelling》、《Knowledge-Based Systems》、《Expert Systems with Applications》、《Applied Soft Computing》等国际顶流期刊发表SCI/SSCI检索论文20余篇,其中4篇文章入选“ESI检索高被引论文。截止至202312月,个人谷歌学术引用次数800余次,H指数14。出版专著1部(科学出版社),软件著作权4项。主持纵向项目国家自然科学基金项目、黑龙江省自然科学基金优秀青年项目、黑龙江省哲学社会科学规划项目等多项。重要参与国家社会科学基金重大项目、国家自然科学基金项目、教育部人文社会科学项目、辽宁省教育厅高层次创新团队海外培训项目等10余项。



87978797威尼斯老品牌(中国)有限公司版权所有 中国 黑龙江省哈尔滨市香坊区和兴路26号 邮编:150040 技术支持:网络信息中心  备案号:黑ICP备19004777号