Yi‐Chung Hu
Biographic Data
| ID | 6587601 |
|---|---|
| NAME | Yi‐Chung Hu |
| GIVEN NAMES | Yi‐Chung |
| FAMILY NAME | Hu |
| SIGNATURE | HU Y C |
| AFFILIATIONS | Chung Yuan Christian University |
| ORCID | 0000-0003-3090-1515 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 8 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Generation of ensemble forecasts using functional-link net for decomposition ensemble learning to forecast tourist arrivals
Tourism combination forecasting using a dynamic weighting strategy with change-point analysis
Combination forecasting is an important in the literature on tourism. This study considers three important issues to develop a more accurate combination forecasting method for tourism forecasting. We address the unrealistic requirement related to the statistical properties of the collected data for model fitting, assign changing rather than fixed weights to single models, and incorporate nonlinear relationships among single-model forecasts into f…
Tourism Demand Forecasting Using Nonadditive Forecast Combinations
Accurately forecasting the demand for tourism can help governments formulate industrial policies and guide the business sector in investment planning. Combining forecasts can improve the accuracy of forecasting the demand for tourism, but limited work has been devoted to developing such combinations. This article addresses two significant issues in this context. First, the linear combination is the commonly used method of combining tourism foreca…
A new multivariate grey prediction model for forecasting China’s regional energy consumption
Developing grey prediction with Fourier series using genetic algorithms for tourism demand forecasting
An Optimized Fractional Grey Prediction Model for Carbon Dioxide Emissions Forecasting
Because grey prediction does not demand that the collected data have to be in line with any statistical distribution, it is pertinent to set up grey prediction models for real-world problems. GM(1,1) has been a widely used grey prediction model, but relevant parameters, including the control variable and developing coefficient, rely on background values that are not easily determined. Furthermore, one-order accumulation is usually incorporated in…
Forecasting China’s CO2 emissions by considering interaction of bilateral FDI using the improved grey multivariable Verhulst model
Because of the harmful influence of CO 2 emissions on the environment and humans, issues related to CO 2 emissions have received considerable attention in recent years. Based on the pollution haven hypothesis and pollution halo effect, the uncertain effect of bilateral foreign direct investment (FDI) on CO 2 emissions has recently been in focus. Moreover, because of the opposing capital flow of bilateral FDI, the interaction between inward FDI (I…
Forecasting the demand for tourism using combinations of forecasts by neural network-based interval grey prediction models
In contrast to point forecasting, interval forecasting provides the degree of variation associated with forecasts. Accurate forecasting can help governments formulate policies for tourism, but little attention has been paid to interval forecasting of tourism demand. This study contributes to apply neural networks to develop interval models for tourism demand forecasting. Since combined forecasts are likely to improve the accuracy of point forecas…
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Developing grey prediction with Fourier series using genetic algorithms for tourism demand forecasting
An Optimized Fractional Grey Prediction Model for Carbon Dioxide Emissions Forecasting
Because grey prediction does not demand that the collected data have to be in line with any statistical distribution, it is pertinent to set up grey prediction models for real-world problems. GM(1,1) has been a widely used grey prediction model, but relevant parameters, including the control variable and developing coefficient, rely on background values that are not easily determined. Furthermore, one-order accumulation is usually incorporated in…
Forecasting China’s CO2 emissions by considering interaction of bilateral FDI using the improved grey multivariable Verhulst model
Because of the harmful influence of CO 2 emissions on the environment and humans, issues related to CO 2 emissions have received considerable attention in recent years. Based on the pollution haven hypothesis and pollution halo effect, the uncertain effect of bilateral foreign direct investment (FDI) on CO 2 emissions has recently been in focus. Moreover, because of the opposing capital flow of bilateral FDI, the interaction between inward FDI (I…
Forecasting the demand for tourism using combinations of forecasts by neural network-based interval grey prediction models
In contrast to point forecasting, interval forecasting provides the degree of variation associated with forecasts. Accurate forecasting can help governments formulate policies for tourism, but little attention has been paid to interval forecasting of tourism demand. This study contributes to apply neural networks to develop interval models for tourism demand forecasting. Since combined forecasts are likely to improve the accuracy of point forecas…
Tourism combination forecasting using a dynamic weighting strategy with change-point analysis
Combination forecasting is an important in the literature on tourism. This study considers three important issues to develop a more accurate combination forecasting method for tourism forecasting. We address the unrealistic requirement related to the statistical properties of the collected data for model fitting, assign changing rather than fixed weights to single models, and incorporate nonlinear relationships among single-model forecasts into f…
Tourism Demand Forecasting Using Nonadditive Forecast Combinations
Accurately forecasting the demand for tourism can help governments formulate industrial policies and guide the business sector in investment planning. Combining forecasts can improve the accuracy of forecasting the demand for tourism, but limited work has been devoted to developing such combinations. This article addresses two significant issues in this context. First, the linear combination is the commonly used method of combining tourism foreca…
A new multivariate grey prediction model for forecasting China’s regional energy consumption
Generation of ensemble forecasts using functional-link net for decomposition ensemble learning to forecast tourist arrivals
Mathematics (8 works) · Econometrics (7 works) · Grey System Theory Applications (7 works) · Computer Science (6 works) · Energy Load and Power Forecasting (6 works) · Data mining (4 works) · Economics (4 works) · Geography (4 works) · Tourism (4 works) · Artificial Intelligence (3 works)