Kaijian He
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View article: Computational and Mathematical Methods in Information Science and Engineering, 2nd Edition
Computational and Mathematical Methods in Information Science and Engineering, 2nd Edition Open
This Special Issue compiles eleven excellent papers, selected from a highly competitive pool of submissions, to collectively highlight the dynamic and interdisciplinary nature of the crucial field of computational and mathematical methods …
View article: Prediction of Crude Oil Price using LLM: An Empirical Analysis
Prediction of Crude Oil Price using LLM: An Empirical Analysis Open
View article: Crude oil risk forecasting using time series foundation model
Crude oil risk forecasting using time series foundation model Open
View article: Measuring Multi-Dimensional Mobile Behavior Effect on Inclusive Finance: Evidence from China
Measuring Multi-Dimensional Mobile Behavior Effect on Inclusive Finance: Evidence from China Open
Credit Invisible is one key area that many countries put much effort to solve in decades. According to the 2020 World Bank statistics, for example, there are over 500 million Chinese and 45 million American, classified as credit invisible …
View article: Dragon’s Ascent: The Significance of Stock Exchanges in the Chinese Financial Revolution
Dragon’s Ascent: The Significance of Stock Exchanges in the Chinese Financial Revolution Open
View article: Risk estimation of crude oil future price using temporal fusion transformer model
Risk estimation of crude oil future price using temporal fusion transformer model Open
To estimate the price risk of the crude oil market more accurately, this paper applies a temporal fusion transformer (TFT) model based on the quantile loss function. The TFT model first obtains the autocorrelation in the return of crude oi…
View article: Crude oil future price forecasting using pretrained transformer model
Crude oil future price forecasting using pretrained transformer model Open
View article: Preface to the Special Issue on “Computational and Mathematical Methods in Information Science and Engineering”
Preface to the Special Issue on “Computational and Mathematical Methods in Information Science and Engineering” Open
With the emergence of big data and the resulting information explosion, computational and mathematical methods provide effective tools to handle the vast amounts of data and information used in big data analytics, knowledge discovery and d…
View article: Quantum Optimized Cost Based Feature Selection and Credit Scoring for Mobile Micro-financing
Quantum Optimized Cost Based Feature Selection and Credit Scoring for Mobile Micro-financing Open
View article: Financial Time Series Forecasting with the Deep Learning Ensemble Model
Financial Time Series Forecasting with the Deep Learning Ensemble Model Open
With the continuous development of financial markets worldwide to tackle rapid changes such as climate change and global warming, there has been increasing recognition of the importance of financial time series forecasting in financial mar…
View article: Forecasting crude oil futures prices using Extreme Gradient Boosting
Forecasting crude oil futures prices using Extreme Gradient Boosting Open
Multi-source data is widely used in the field of energy future prices forecasting, the improvement of forecast ability and data screening are becoming the focus of current research. In this paper, two tree-based models (namely, Random Fore…
View article: Crude oil price prediction using temporal fusion transformer model
Crude oil price prediction using temporal fusion transformer model Open
In this paper, we applied the temporal fusion transformer model to the crude oil price movement modeling and forecasting. The temporal fusion transformer model has been adopted in the crude oil price forecasting model using the attention m…
View article: Tourist Arrival Forecasting Using Multiscale Mode Learning Model
Tourist Arrival Forecasting Using Multiscale Mode Learning Model Open
The forecasting of tourist arrival depends on the accurate modeling of prevalent data patterns found in tourist arrival, especially for daily tourist arrival, where tourist arrival changes are more complex and highly nonlinear. In this pap…
View article: Forecasting Crude Oil Risk Using a Multivariate Multiscale Convolutional Neural Network Model
Forecasting Crude Oil Risk Using a Multivariate Multiscale Convolutional Neural Network Model Open
In light of the increasing level of correlation and dependence between the crude oil markets and the external influencing factors in the related financial markets, we propose a new multivariate empirical decomposition convolutional neural …
View article: Crude oil risk forecasting using mode decomposition based model
Crude oil risk forecasting using mode decomposition based model Open
The crude oil markets have been transformed into more risky market environment with the increasing level of complexity and volatility in recent years. More accurate and reliable risk estimates increasingly depends on the better understandi…
View article: China's Crude oil futures forecasting with search engine data
China's Crude oil futures forecasting with search engine data Open
In this paper, we used the Baidu feed index to quantify the valuable information from the search engine, and proposed a China's crude oil futures price forecasting model with feed index. The empirical analysis confirms that the feed index,…
View article: Crude Oil Price Prediction using Embedding Convolutional Neural Network Model
Crude Oil Price Prediction using Embedding Convolutional Neural Network Model Open
In this paper, a new crude oil price forecasting model using data embedding and Convolutional Neural Network has been proposed to predict more accurate crude oil price movement. It uses the time delayed embedding technique to transform the…
View article: Factor analysis of financial time series using EEMD-ICA based approach
Factor analysis of financial time series using EEMD-ICA based approach Open
View article: Measuring the maturity of carbon market in China: An entropy-based TOPSIS approach
Measuring the maturity of carbon market in China: An entropy-based TOPSIS approach Open
In this study, we construct an evaluation index system in terms of three dimensions including internal, external and interface factors. We propose an entropy-based TOPSIS model to measure the maturity of carbon market. The proposed model u…
View article: Carbon futures price forecasting based with ARIMA-CNN-LSTM model
Carbon futures price forecasting based with ARIMA-CNN-LSTM model Open
In this paper, we introduced an ARIMA-CNN-LSTM model to forecast the carbon futures price. The ARIMA-CNN-LSTM model employs the ARIMA model and the deep neural network structure that combines the CNN and LSTM layers to capture linear and n…
View article: Crude oil risk forecasting: New evidence from multiscale analysis approach
Crude oil risk forecasting: New evidence from multiscale analysis approach Open
View article: A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting
A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting Open
View article: Forecasting Exchange Rate Value at Risk using Deep Belief Network Ensemble based Approach
Forecasting Exchange Rate Value at Risk using Deep Belief Network Ensemble based Approach Open
In this paper, we propose a new Value at Risk estimate based on the Deep Belief Network ensemble model with Empirical Mode Decomposition (EMD) technique. It attempts to capture the multi-scale data features with the EMD-DBN ensemble model …
View article: Integrated Dynamic 3D Imaging of Microbial Processes and Communities in Rhizosphere Environments: The Argonne Small Worlds Project
Integrated Dynamic 3D Imaging of Microbial Processes and Communities in Rhizosphere Environments: The Argonne Small Worlds Project Open
Journal Article Integrated Dynamic 3D Imaging of Microbial Processes and Communities in Rhizosphere Environments: The Argonne Small Worlds Project Get access K M Kemner, K M Kemner Argonne National Laboratory, Argonne, United States Search…
View article: Forecasting Crude Oil Prices: a Deep Learning based Model
Forecasting Crude Oil Prices: a Deep Learning based Model Open
With the popularity of the deep learning model in the engineering fields, it has attracted significant research interests in the economic and finance fields. In this paper, we use the deep learning model to capture the unknown complex nonl…
View article: Forecasting Electricity Market Risk Using Empirical Mode Decomposition (EMD)—Based Multiscale Methodology
Forecasting Electricity Market Risk Using Empirical Mode Decomposition (EMD)—Based Multiscale Methodology Open
The electricity market has experienced an increasing level of deregulation and reform over the years. There is an increasing level of electricity price fluctuation, uncertainty, and risk exposure in the marketplace. Traditional risk measur…
View article: Forecasting Energy Value at Risk Using Multiscale Dependence Based Methodology
Forecasting Energy Value at Risk Using Multiscale Dependence Based Methodology Open
In this paper, we propose a multiscale dependence-based methodology to analyze the dependence structure and to estimate the downside portfolio risk measures in the energy markets. More specifically, under this methodology, we formulate a n…
View article: Multivariate EMD-Based Modeling and Forecasting of Crude Oil Price
Multivariate EMD-Based Modeling and Forecasting of Crude Oil Price Open
Recent empirical studies reveal evidence of the co-existence of heterogeneous data characteristics distinguishable by time scale in the movement crude oil prices. In this paper we propose a new multivariate Empirical Mode Decomposition (EM…
View article: The Information Content of OVX for Crude Oil Returns Analysis and Risk Measurement: Evidence from the Kalman Filter Model
The Information Content of OVX for Crude Oil Returns Analysis and Risk Measurement: Evidence from the Kalman Filter Model Open
View article: Wavelet Entropy Based Analysis and Forecasting of Crude Oil Price Dynamics
Wavelet Entropy Based Analysis and Forecasting of Crude Oil Price Dynamics Open
For the modeling of complex and nonlinear crude oil price dynamics and movement, wavelet analysis can decompose the time series and produce multiple economically meaningful decomposition structures based on different assumptions of wavelet…