D-Index & Metrics Best Publications
Economics and Finance
China
2023

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Economics and Finance D-index 79 Citations 21,646 600 World Ranking 187 National Ranking 4
Engineering and Technology D-index 79 Citations 22,540 596 World Ranking 231 National Ranking 27

Research.com Recognitions

Awards & Achievements

2023 - Research.com Economics and Finance in China Leader Award

2022 - Research.com Economics and Finance in China Leader Award

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Artificial intelligence
  • Machine learning

Shouyang Wang mostly deals with Artificial intelligence, Econometrics, Machine learning, Artificial neural network and Portfolio. His study ties his expertise on Data mining together with the subject of Artificial intelligence. The various areas that Shouyang Wang examines in his Econometrics study include Financial risk and Spillover effect.

His Machine learning study combines topics from a wide range of disciplines, such as Index and Generalization. His biological study spans a wide range of topics, including Stock market index and Exchange rate. His studies deal with areas such as Actuarial science and Dynamic programming, Mathematical optimization as well as Portfolio.

His most cited work include:

  • Forecasting stock market movement direction with support vector machine (665 citations)
  • Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm (448 citations)
  • Managing carbon footprints in inventory management (436 citations)

What are the main themes of his work throughout his whole career to date?

Shouyang Wang focuses on Econometrics, Artificial intelligence, Mathematical optimization, Artificial neural network and Supply chain. His Econometrics study incorporates themes from Empirical research and Stock market. His study connects Machine learning and Artificial intelligence.

His work deals with themes such as Portfolio optimization and Portfolio, which intersect with Mathematical optimization. He interconnects Ensemble forecasting and Data mining in the investigation of issues within Artificial neural network. Shouyang Wang has researched Supply chain in several fields, including Microeconomics and Industrial organization.

He most often published in these fields:

  • Econometrics (18.59%)
  • Artificial intelligence (12.48%)
  • Mathematical optimization (13.94%)

What were the highlights of his more recent work (between 2017-2021)?

  • Econometrics (18.59%)
  • Volatility (5.58%)
  • Industrial organization (5.98%)

In recent papers he was focusing on the following fields of study:

Shouyang Wang mainly focuses on Econometrics, Volatility, Industrial organization, Artificial intelligence and Natural resource economics. His Econometrics study combines topics in areas such as Oil price, Demand forecasting, Stock market and Time series. His Volatility research is multidisciplinary, relying on both Vector autoregression, Monetary economics and Financial crisis.

His research ties Supply chain and Industrial organization together. His study in Supply chain is interdisciplinary in nature, drawing from both Microeconomics, Profit and Remanufacturing. Much of his study explores Artificial intelligence relationship to Machine learning.

Between 2017 and 2021, his most popular works were:

  • Big data in tourism research: A literature review (220 citations)
  • Global supply-chain effects of COVID-19 control measures. (94 citations)
  • Carbon emissions of cities from a consumption-based perspective (84 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Artificial intelligence
  • Machine learning

Shouyang Wang spends much of his time researching Natural resource economics, Econometrics, Supply chain, Ensemble learning and Artificial neural network. His biological study spans a wide range of topics, including Oil market, Oil price and Mainland China. His Supply chain research is multidisciplinary, incorporating perspectives in Constraint, Microeconomics, Profit, Industrial organization and Remanufacturing.

The concepts of his Ensemble learning study are interwoven with issues in Algorithm, Decomposition, Cluster analysis and Hilbert–Huang transform. His work in Algorithm addresses subjects such as Support vector machine, which are connected to disciplines such as Field. Shouyang Wang combines subjects such as Nonlinear system, Data mining and Benchmark with his study of Artificial neural network.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Forecasting stock market movement direction with support vector machine

Wei Huang;Yoshiteru Nakamori;Shou-Yang Wang.
Computers & Operations Research (2005)

1260 Citations

Nonconvex Optimization and Its Applications

Panos Pardalos;Shashi Kant Mishra;Shou-Yang Wang;Kin Keung Lai.
(2008)

1173 Citations

Managing carbon footprints in inventory management

Guowei Hua;T.C.E. Cheng;T.C.E. Cheng;Shouyang Wang.
International Journal of Production Economics (2011)

763 Citations

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

Lean Yu;Shouyang Wang;Kin Keung Lai.
Energy Economics (2008)

700 Citations

Price and lead time decisions in dual-channel supply chains

Guowei Hua;Guowei Hua;Shouyang Wang;T.C.E. Cheng.
European Journal of Operational Research (2010)

518 Citations

A new fuzzy support vector machine to evaluate credit risk

Yongqiao Wang;Shouyang Wang;K.K. Lai.
IEEE Transactions on Fuzzy Systems (2005)

456 Citations

A new approach for crude oil price analysis based on Empirical Mode Decomposition

Xun Zhang;K.K. Lai;Shou-Yang Wang.
Energy Economics (2008)

455 Citations

Global supply-chain effects of COVID-19 control measures.

Dabo Guan;Daoping Wang;Stephane Hallegatte;Steven J. Davis.
Nature Human Behaviour (2020)

443 Citations

Credit risk assessment with a multistage neural network ensemble learning approach

Lean Yu;Shouyang Wang;Kin Keung Lai.
Expert Systems With Applications (2008)

383 Citations

Vague soft sets and their properties

Wei Xu;Jian Ma;Shouyang Wang;Gang Hao.
Computers & Mathematics With Applications (2010)

349 Citations

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