Manhua Chen

Welcome!
I am Manhua Chen (Maho Chan / 陈漫桦) and this page is mainly about a brief personal introduction. Prof. Hailin Li, a renowned scholar in the field of data science (The World's Top 2% Scientists by Stanford University), was my academic advisor when I was an undergraduate at HuaQiao University. I used to study time-series data mining, and now I am inclined to solve financial problems using machine learning and data mining approaches.

Email / ORCID / GitHub / Scholat / Gitee / CSDN / Cnblogs /

Educations

(2018-2019), Studying, Human Resources Management , College of Business Administration, HuaQiao University, Quanzhou, China.

(06/2019), I changed my major from Human Resource Management to Information Management and Information Systems.

(2019-2022), Undergraduate, Infosrmation Management and Information System, College of Business Administration, HuaQiao University, Quanzhou, China.

News

(Last updated on 2023-11-05)

(09/2023), Applied Soft Computing, the International Journal of Computer Science and Artificial Intelligence, has accepted our paper.

(03/2021), Our proposal for PM2.5 forecasting research won an excellent prize in the Innovation Competition on Shared Services of Science and Technology Resources for University Students organized by the National Population and Health Science Data Center.

Publications

Time series clustering based on normal cloud model and complex network
Hailin Li *, Manhua Chen
Abstract
When data mining research is conducted, it is difficult to obtain precise domain knowledge to set a similarity threshold. Furthermore, noise and missing values are inevitable. Missing values and noise without pre-processing are challenges for many algorithms. A time-series clustering method is proposed based on the normal cloud model and complex networks. Matrix profile similarity measurement, normal cloud model generation and filtering, cloud model expectation curve weighting, degree centrality reweighting, and community discovery in complex networks are the five stages of the proposed clustering algorithm. Local features are considered, and the effects of missing values are reduced when performing similarity measurements. The normal cloud model can be used to set thresholds adaptively. The Louvain algorithm accomplishes the clustering task in complex networks without specifying the clusters. Experiments are conducted on 94 datasets and are compared with 8 clustering methods in the UCR time-series clustering benchmark study. Experimental results indicate that the proposed method can perform well on many datasets.
Graphic Abstract
Paper Link
基于决策分析的PM2.5污染特征及指数预测研究
(The Pollution Characteristics of PM2.5 and Indices Prediction Research Based on the Decision Analysis)
Fang Zong, Manhua Chen, Gongqiang Chen
Website Link

Awards

(12/2021), The Third-Prize College Scholarship (College Individual Scholarship)

(03/2021), Excellent Prize of the Innovation Competition on Shared Services of Science and Technology Resources for University Students organized by the National Population Health Science Data Center

(10/2019), The Third-Prize College Scholarship (College Individual Scholarship)

(06/2019), Outstanding Member of the Communist Youth League of China

Visitors'map

Thanks for Dr.Wang and Ziyang Chen. The design of this website originates from Dr.Wang and the idea comes from Ziyang Chen.