Asghar, M., Mehmood, K., Yasin, S., & Khan, Z. M. (2021). Used cars price prediction using machine learning with optimal features. Pakistan Journal of Engineering and Technology, 4(2), 113–119.
Deng, S., Zhu, Y., Huang, X., Duan, S., & Fu, Z. (2022). High-frequency direction forecasting of the futures market using a machine-learning-based method. Future Internet, 14(6), 180.
Istudor, N., Dumitru, I., Filip, A., Stancu, A., Roșca, M. I., & Cânda, A. (2023). Integration of circular economy principles in consumer behaviour for electrical and electronic equipment. Amfiteatru Economic, 25(62), 48–62.
M’hamdi, O., Takács, S., Palotás, G., Ilahy, R., Helyes, L., & Pék, Z. (2024). A comparative analysis of XGBoost and neural network models for predicting some tomato fruit quality traits from environmental and meteorological data. Plants, 13(5), 746.
Orji, U., & Ukwandu, E. (2024). Machine learning for an explainable cost prediction of medical insurance. Machine Learning with Applications, 15, 100516.
Xing, X., Tang, F. F., & Yang, Z. (2004). Pricing dynamics in the online consumer electronics market. Journal of Product & Brand Management, 13(6), 429–441.
Safonov, K. (2024). Neural network approach to demand estimation and dynamic pricing in retail. Hasnain, M., Sajid, A., & Awan, M. A. (2024). Predicting the price of used electronic devices using machine learning techniques.