Earticle

초록

영어

This study examines whether solar radiation and citywide particulate-matter measures add explanatory and predictive information to daily demand models for Seoul's Ttareungi public bicycle system. Using 550 daily observations, the primary explanatory regression includes mean-centered solar radiation and its squared term with established weather, mobility, and calendar controls. The fitted conditional association is inverse U-shaped, reaching a turning point at 19.50 MJ/m² rather than remaining positive across the observed range. Both solar terms remain statistically significant under lag-5 Newey–West HAC inference and remain supported in seasonal, temporal-trend, and missing-value sensitivity checks. PM10 and PM2.5 are not statistically significant explanatory additions under either OLS or HAC inference. Forecasting specifications are selected only within the first 440 observations using five expanding-window validation folds; the final 110 observations are retained as an untouched holdout. The RMSE-first, MAE-second rule selects Random Forest with solar radiation and PM10, with validation RMSE 15,519.70 and MAE 11,735.86. After refitting on all development data, final-holdout RMSE is 16,367.95 and MAE is 13,511.56. PM10 therefore offers small and somewhat unstable incremental predictive value, distinct from explanatory significance.

목차

Abstract
I. INTRODUCTION
2. LITERATURE REVIEW
2.1. Environmental and Temporal Predictors of Bicycle Demand
2.2. Air Quality and Bicycle Use
2.3. Explanatory Modeling and Forecast Validation
3. DATA AND METHODS
3.1. Data Sources, Study Period, and Variables
3.2. Data Preparation and Missing Values
3.3. Explanatory Regression and HAC Inference
3.4. Forecasting Design and Model Selection
3.5. Forecasting Metrics
4. RESULTS
4.1. Exploratory Relationships
4.2. Primary Quadratic Solar-Radiation Model
4.3. Seasonal, Temporal, and Missing-Value Robustness
4.4. PM10, PM2.5, and Multicollinearity
4.5. Development-Sample Validation and Final Holdout
4.6. Solar-Squared Forecasting Comparison
5. DISCUSSION
5.1. Interpretation of the Solar-Radiation Relationship
5.2. Air-Quality Inference versus Predictive Contribution
5.3. Forecasting Design and Operational Meaning
5.4. Limitations
6. CONCLUSION
REFERENCES

키워드

저자

• Yongjoo Kwon [ Statistics and Data Science Discipline, Division of Science and Mathematics, University of Minnesota Morris, Morris, MN 56267, USA ]
• Jong-Min Kim [ Statistics and Data Science Discipline, Division of Science and Mathematics, University of Minnesota Morris, Morris, MN 56267, USA/ EGADE Business School, Tecnologico de Monterrey, Ave. Rufino Tamayo, Garza Garcia, NL, CP 66269, Mexico ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Intelligent Technologies and Innovative Practices

• 간기

  계간

• eISSN

  3092-412X

• 수록기간

  2026~2026

• 십진분류

  KDC 323 DDC 338