What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Machine learning
His primary areas of investigation include Artificial neural network, Artificial intelligence, Operations research, Machine learning and Econometrics. Kin Keung Lai combines subjects such as Data processing, Expert system, Stock market index, Nonlinear system and Exchange rate with his study of Artificial neural network. In Artificial intelligence, Kin Keung Lai works on issues like West Texas Intermediate, which are connected to Feedforward neural network, Spot contract, Brent Crude and Pattern recognition.
His Operations research research is multidisciplinary, incorporating perspectives in Production, Production planning, Stochastic programming, Decision support system and Port. His Machine learning study combines topics in areas such as Generalization, Data mining and Financial crisis. His work deals with themes such as Hilbert–Huang transform, Actuarial science and Portfolio optimization, Portfolio, which intersect with Econometrics.
His most cited work include:
- Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm (448 citations)
- A new fuzzy support vector machine to evaluate credit risk (292 citations)
- A new approach for crude oil price analysis based on Empirical Mode Decomposition (269 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Econometrics, Artificial intelligence, Mathematical optimization, Artificial neural network and Data mining. The study incorporates disciplines such as Value at risk, Empirical research, Wavelet and Portfolio in addition to Econometrics. His research in Portfolio is mostly focused on Portfolio optimization.
As part of his studies on Artificial intelligence, Kin Keung Lai often connects relevant subjects like Machine learning. His studies in Genetic algorithm and Duality are all subfields of Mathematical optimization research. His research links Credit risk with Support vector machine.
He most often published in these fields:
- Econometrics (20.21%)
- Artificial intelligence (15.57%)
- Mathematical optimization (16.77%)
What were the highlights of his more recent work (between 2017-2021)?
- Supply chain (14.07%)
- Industrial organization (8.53%)
- Operations research (13.32%)
In recent papers he was focusing on the following fields of study:
Kin Keung Lai mainly focuses on Supply chain, Industrial organization, Operations research, Econometrics and Mathematical optimization. His Supply chain study integrates concerns from other disciplines, such as Incentive, Microeconomics, Profit, Stackelberg competition and Remanufacturing. Kin Keung Lai has researched Stackelberg competition in several fields, including Consignment and Newsvendor model.
His research in Industrial organization tackles topics such as Revenue sharing which are related to areas like Product and Pareto principle. His studies in Operations research integrate themes in fields like Calibration and Vendor Selection. His Econometrics study combines topics from a wide range of disciplines, such as Market liquidity, Currency crisis, Renminbi and Focus.
Between 2017 and 2021, his most popular works were:
- The future natural gas consumption in China: Based on the LMDI-STIRPAT-PLSR framework and scenario analysis (39 citations)
- The future natural gas consumption in China: Based on the LMDI-STIRPAT-PLSR framework and scenario analysis (39 citations)
- Channel competition and coordination of a dual-channel supply chain with demand and cost disruptions (17 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Machine learning
The scientist’s investigation covers issues in Supply chain, Industrial organization, Supply and demand, Data mining and Remanufacturing. His work on Supply chain management as part of general Supply chain study is frequently connected to Subsidy, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. Kin Keung Lai works mostly in the field of Supply chain management, limiting it down to concerns involving Subject and, occasionally, Operations research.
His Industrial organization research includes themes of Revenue sharing, Pareto principle and Product. The various areas that Kin Keung Lai examines in his Data mining study include Ranking and Benchmark. The Benchmark study combines topics in areas such as Artificial neural network, Cluster analysis, Ensemble learning, Decomposition and Exchange rate.
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