World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
61
Citations
12700
World Ranking
3116
National Ranking
418

Overview

Lean Yu is affiliated with the Academy of Mathematics and Systems Science in China and has contributed extensively to research in computer science and engineering. Their work covers a broad range of topics with a significant focus on management science, operations research, and artificial intelligence.

Their research portfolio includes studies in imbalanced data classification techniques, financial distress and bankruptcy prediction, energy load and power forecasting, market dynamics and volatility, stock market forecasting methods, grey system theory applications, and forecasting techniques and applications.

Lean Yu has published extensively in leading venues, with frequent contributions to Expert Systems with Applications, Information Sciences, INFORMS Journal on Computing, Applied Soft Computing, and Procedia Computer Science.

Their recent papers include:

  • "Missing Data Preprocessing in Credit Classification: One-Hot Encoding or Imputation?" (2020) in Emerging Markets Finance and Trade
  • "Trajectory prediction for heterogeneous traffic-agents using knowledge correction data-driven model" (2022) in Information Sciences
  • "Blockchain-driven supply chain finance solution for small and medium enterprises" (2020) in Frontiers of Engineering Management
  • "An effective rolling decomposition-ensemble model for gasoline consumption forecasting" (2021) in Energy
  • "Decarbonizing China's power sector by 2030 with consideration of technological progress and cross-regional power transmission" (2021) in Energy Policy

Frequent co-authors collaborating with Lean Yu include Xiaoming Zhang, Hang Yin, Yixiang Ma, Guoxing Zhang, and Xi Xi.

The main fields of study addressed by Lean Yu encompass:

  • Computer Science
  • Engineering

Within these fields, notable subfields of study are:

  • Management Science and Operations Research
  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Economics and Econometrics
  • Accounting

Best Publications

  • Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm

    Lean Yu;Shouyang Wang;Kin Keung Lai

  • Credit risk assessment with a multistage neural network ensemble learning approach

    Lean Yu;Shouyang Wang;Kin Keung Lai

  • A deep learning ensemble approach for crude oil price forecasting

    Yang Zhao;Jianping Li;Lean Yu

  • A novel nonlinear ensemble forecasting model incorporating GLAR and ANN for foreign exchange rates

    Lean Yu;Shouyang Wang;K.K. Lai

  • A distance-based group decision-making methodology for multi-person multi-criteria emergency decision support

    Lean Yu;Kin Keung Lai

  • A new method for crude oil price forecasting based on support vector machines

    Wen Xie;Lean Yu;Shanying Xu;Shouyang Wang

  • Estimating the impact of extreme events on crude oil price: An EMD-based event analysis method

    Xun Zhang;Lean Yu;Shouyang Wang;Kin Keung Lai

  • An intelligent-agent-based fuzzy group decision making model for financial multicriteria decision support: The case of credit scoring

    Lean Yu;Lean Yu;Shouyang Wang;Kin Keung Lai

  • Evolving Least Squares Support Vector Machines for Stock Market Trend Mining

    Lean Yu;Huanhuan Chen;Shouyang Wang;Kin Keung Lai

  • Online big data-driven oil consumption forecasting with Google trends

    Lean Yu;Yaqing Zhao;Ling Tang;Zebin Yang

  • A novel decomposition ensemble model with extended extreme learning machine for crude oil price forecasting

    Lean Yu;Wei Dai;Ling Tang

  • A decomposition–ensemble model with data-characteristic-driven reconstruction for crude oil price forecasting

    Lean Yu;Zishu Wang;Ling Tang

  • Multistage RBF neural network ensemble learning for exchange rates forecasting

    Lean Yu;Kin Keung Lai;Shouyang Wang

  • Support vector machine based multiagent ensemble learning for credit risk evaluation

    Lean Yu;Wuyi Yue;Shouyang Wang;K. K. Lai

  • Least squares support vector machines ensemble models for credit scoring

    Ligang Zhou;Kin Keung Lai;Lean Yu

  • An integrated data preparation scheme for neural network data analysis

    Lean Yu;Shouyang Wang;K.K. Lai

  • A neural-network-based nonlinear metamodeling approach to financial time series forecasting

    Lean Yu;Shouyang Wang;Kin Keung Lai

  • A non-iterative decomposition-ensemble learning paradigm using RVFL network for crude oil price forecasting

    Ling Tang;Ling Tang;Yao Wu;Lean Yu

  • A novel hybrid ensemble learning paradigm for nuclear energy consumption forecasting

    Ling Tang;Lean Yu;Lean Yu;Shuai Wang;Jianping Li

  • NEURAL NETWORKS IN FINANCE AND ECONOMICS FORECASTING

    Wei Huang;Wei Huang;Kin Keung Lai;Kin Keung Lai;Yoshiteru Nakamori;Shouyang Wang;Shouyang Wang

  • Neural network-based mean-variance-skewness model for portfolio selection

    Lean Yu;Shouyang Wang;Kin Keung Lai

Frequent Co-Authors

Shouyang Wang
Shouyang Wang Chinese Academy of Sciences
Kin Keung Lai
Kin Keung Lai Shaanxi Normal University
Wai-Ki Ching
Wai-Ki Ching University of Hong Kong
Gang Kou
Gang Kou Southwestern University of Finance and Economics
Aoying Zhou
Aoying Zhou East China Normal University
Yong Shi
Yong Shi Chinese Academy of Sciences
Yukun Bao
Yukun Bao Huazhong University of Science and Technology
Enrique Herrera-Viedma
Enrique Herrera-Viedma University of Granada
Yi Peng
Yi Peng University of Electronic Science and Technology of China
Masao Fukushima
Masao Fukushima Kyoto University

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