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Fuzzy Optimal Allocation Model for Task-Resource Assignment Problem in a Collaborative Logistics Network

IEEE transactions on fuzzy systems, 2019-05, Vol.27 (5), p.1112-1125

2019

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Carbon allowance auction design of China's emissions trading scheme: A multi-agent-based approach

Energy policy, 2017-03, Vol.102, p.30-40

2017

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A Novel CEEMD-Based EELM Ensemble Learning Paradigm for Crude Oil Price Forecasting

International journal of information technology & decision making, 2015-01, Vol.14 (1), p.141-169

2015

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A Data-Trait-Driven Rolling Decomposition-Ensemble Model for Gasoline Consumption Forecasting

Energies (Basel), 2021-08, Vol.14 (15), p.4604

2021

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Evolving Least Squares Support Vector Machines for Stock Market Trend Mining

IEEE transactions on evolutionary computation, 2009-02, Vol.13 (1), p.87-102

2009

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Why do EMD‐based methods improve prediction? A multiscale complexity perspective

Journal of forecasting, 2019-11, Vol.38 (7), p.714-731

2019

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Missing Data Preprocessing in Credit Classification: One-Hot Encoding or Imputation?

Emerging markets finance & trade, 2022, Vol.58 (2), p.472-482

2022

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A Hybrid Short-Term Load Forecasting Model Based on a Multi-Trait-Driven Methodology and Secondary Decomposition

Energies (Basel), 2022-08, Vol.15 (16), p.5875

2022

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Stock Selection with a Novel Sigmoid-Based Mixed Discrete-Continuous Differential Evolution Algorithm

IEEE transactions on knowledge and data engineering, 2016-07, Vol.28 (7), p.1891-1904

2016

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A compressed sensing based AI learning paradigm for crude oil price forecasting

Energy economics, 2014-11, Vol.46, p.236-245

2014

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A hybrid grid-GA-based LSSVR learning paradigm for crude oil price forecasting

Neural computing & applications, 2016-11, Vol.27 (8), p.2193-2215

2016

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Privacy Preservation in Distributed Subgradient Optimization Algorithms

IEEE transactions on cybernetics, 2018-07, Vol.48 (7), p.2154-2165

2018

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A high-dimensionality-trait-driven learning paradigm for high dimensional credit classification

Financial innovation (Heidelberg), 2021-04, Vol.7 (1), p.1-20, Article 32

2021

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Assessing Potentiality of Support Vector Machine Method in Crude Oil Price Forecasting

Eurasia journal of mathematics, science and technology education, 2017-12, Vol.13 (12)

2017

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Managing knowledge reuse: the duality of innovator personality

Journal of knowledge management, 2023-03, Vol.27 (3), p.785-819

2023

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A novel data-characteristic-driven modeling methodology for nuclear energy consumption forecasting

Applied energy, 2014-09, Vol.128, p.1-14

2014

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Volatility forecasting for the shipping market indexes: an AR-SVR-GARCH approach

Maritime policy and management, 2022-08, Vol.49 (6), p.864-881

2022

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Crude oil price analysis and forecasting using wavelet decomposed ensemble model

Energy (Oxford), 2012-10, Vol.46 (1), p.564-574

2012

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Skewness of Fuzzy Numbers and Its Applications in Portfolio Selection

IEEE transactions on fuzzy systems, 2015-12, Vol.23 (6), p.2135-2143

2015

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Analysis of the Determinants and Mechanism of Mutton Price in Xinjiang Region of China

Sustainability, 2022-10, Vol.14 (20), p.13482

2022

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Two-Stage Portfolio Optimization Integrating Optimal Sharp Ratio Measure and Ensemble Learning

IEEE access, 2023, Vol.11, p.1654-1670

2023

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Feature weighted confidence to incorporate prior knowledge into support vector machines for classification

Knowledge and information systems, 2019-02, Vol.58 (2), p.371-397

2019

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Bio-Inspired Credit Risk Analysis: Computational Intelligence with Support Vector Machines

1. Aufl., 2008

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Ensemble Forecasting for Complex Time Series Using Sparse Representation and Neural Networks

Journal of forecasting, 2017-03, Vol.36 (2), p.122-138

2017

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A novel seasonal decomposition based least squares support vector regression ensemble learning approach for hydropower consumption forecasting in China

Energy (Oxford), 2011-11, Vol.36 (11), p.6542-6554

2011

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Fuzzy Optimal Allocation Model for Task-Resource Assignment Problem in a Collaborative Logistics Network

Carbon allowance auction design of China's emissions trading scheme: A multi-agent-based approach

A Novel CEEMD-Based EELM Ensemble Learning Paradigm for Crude Oil Price Forecasting

A Data-Trait-Driven Rolling Decomposition-Ensemble Model for Gasoline Consumption Forecasting

Evolving Least Squares Support Vector Machines for Stock Market Trend Mining

Why do EMD‐based methods improve prediction? A multiscale complexity perspective

Missing Data Preprocessing in Credit Classification: One-Hot Encoding or Imputation?

A Hybrid Short-Term Load Forecasting Model Based on a Multi-Trait-Driven Methodology and Secondary Decomposition

Stock Selection with a Novel Sigmoid-Based Mixed Discrete-Continuous Differential Evolution Algorithm

A compressed sensing based AI learning paradigm for crude oil price forecasting

A hybrid grid-GA-based LSSVR learning paradigm for crude oil price forecasting

Privacy Preservation in Distributed Subgradient Optimization Algorithms

A high-dimensionality-trait-driven learning paradigm for high dimensional credit classification

Assessing Potentiality of Support Vector Machine Method in Crude Oil Price Forecasting

Managing knowledge reuse: the duality of innovator personality

A novel data-characteristic-driven modeling methodology for nuclear energy consumption forecasting

Volatility forecasting for the shipping market indexes: an AR-SVR-GARCH approach

Crude oil price analysis and forecasting using wavelet decomposed ensemble model

Skewness of Fuzzy Numbers and Its Applications in Portfolio Selection

Analysis of the Determinants and Mechanism of Mutton Price in Xinjiang Region of China

Two-Stage Portfolio Optimization Integrating Optimal Sharp Ratio Measure and Ensemble Learning

Feature weighted confidence to incorporate prior knowledge into support vector machines for classification

Bio-Inspired Credit Risk Analysis: Computational Intelligence with Support Vector Machines

Ensemble Forecasting for Complex Time Series Using Sparse Representation and Neural Networks

A novel seasonal decomposition based least squares support vector regression ensemble learning approach for hydropower consumption forecasting in China

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