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ISSN

3082-8201(Oline)

3082-821X(Print)

Article Processing Charges (APCs)

SGD$600

Publication Frequency

Bi-Monthly

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Published

2025-10-30

Issue

Vol 2 No 4 (2025): Published

Section

Articles

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面向电商领域的 AI 驱动 RPA:汽车价格预测与销售预测

徐 如意

广州城建职业学院

袁 冠聪

广州南方学院

谢 金荣

广州城建职业学院

张 秀婉

广州城建职业学院

尚 玥

广州城建职业学院

陈 兰兰

广州城建职业学院


DOI: https://doi.org/10.59429/zhkj.v2i4.11720


Keywords: 人工智能;机器人处理;自动化、汽车价格预测;电子商务;机器学习;回归分析


Abstract

电子商务行业的迅猛发展已显著影响汽车市场,促使企业亟需精准的价格预测模型,以优化供应商的定价策 略。本研究创新性地融合了人工智能(AI)与机器人流程自动化(RPA),旨在提升汽车价格预测的准确性和效率。 其中,RPA 被用于自动从线上平台抓取车辆价格及销售数据,有效克服了反爬虫机制带来的挑战;与此同时,基于 AI 的回归模型则深入分析历史数据及发动机排量、整备质量、马力和车辆尺寸等关键特征,从而精准预测未来价格 走势。通过对比决策树、支持向量机以及深度学习模型等多种机器学习算法,本研究重点突出了回归方法在兼顾预 测精度与模型可解释性方面的独特优势。研究结果表明,AI 与 RPA 的协同应用不仅能够简化数据获取流程、提高预 测准确性,还能为供应商提供基于数据驱动的定价建议。这一研究成果有助于推动汽车电商领域的智能化转型,为 希望在动态市场中优化定 价策略的企业提供了可扩展的解决方案。


References

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[2] M. Asghar, K. Mehmood, S. Yasin, and Z. M. Khan, "Used cars priceprediction using machine learning with optimal features," Pakistan Journalof Engineering and Technology, vol. 4, no. 2, pp. 113–119, 2021.

[3] L. Bukvić, J. Pašagić Škrinjar, T. Fratrović, and B. Abramović, "Priceprediction and classification of used-vehicles using supervised machinelearning," Sustainability, vol. 14, no. 24, p. 17034, 2022.

[4] C. Longani, S. Prasad Potharaju, and S. Deore, "Price prediction for pre-owned cars using ensemble machine learning techniques," in Recent Trendsin Intensive Computing, IOS Press, pp. 178–187, 2021.

[5] F. Al-Turjman, A. A. Hussain, S. Alturjman, and C. Altrjman, "Vehicleprice classification and prediction using machine learning in the IoT smartmanufacturing era," Sustainability, vol. 14, no. 15, p. 9147, 2022.



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