<?xml version="1.1" encoding="utf-8"?>
<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">ERA</journal-id><journal-title-group><journal-title>Engineering Research and Application</journal-title></journal-title-group><issn>2995-3154</issn><eissn>2993-2742</eissn><publisher><publisher-name>Art and Technology</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.61369/ERA.7514</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>人工智能在二手车特征及价值评估中的应用研究</title><url>https://artdesignp.com/journal/ERA/2/9/10.61369/ERA.7514</url><author>黄乐</author><pub-date pub-type="publication-year"><year>2024</year></pub-date><volume>2</volume><issue>9</issue><history><date date-type="pub"><published-time>2024-09-20</published-time></date></history><abstract>随着人工智能的发展，二手车特征及价值评估通过人工智能涌现出速度快、并行处理量大、准确度高的通用能力，在二手车交易、金融、保险的商业场景中价值凸显。本文首先研究了个人在二手车价值评估中客观存在的传统计算方法，有限历史成交经验和记忆容量受限的痛点。随后，探讨了人工智能的单体原理及应用前景，提出了基于人工智能的二手车特征及价值评估的科学应用，包括数据挖掘、特征预处理、数据编码、模型计算等，同时分析了机器学习方法包含线性、深度学习、决策树、神经网络等回归、分类算法及引用案例；最后，展望了人工智能在二手车特征及价值评估中赋能及解决个人痛点的价值。</abstract><keywords>人工智能,二手车特征,二手车价值评估,机器学习</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>[1]A.Dutulescu,M.Iamandei,L.M.Neagu,S.Ruseti,V.Ghita,M.Dascalu,What is the Price of Your Used Car? Automated Predictions using XGBoost and Neural Networks，IEEEaccess,24th International Conference on Control Systems and Computer Science (CSCS),2023，pp.418-425.[2]A.K. MANDAL, M.NADIM , H SAHA, T SULTANA, M. D HOSSAIN, AND E. H,&amp;ldquo;Feature Subset Selection for High-Dimensional, Low Sampling Size Data ClassificationUsing Ensemble Feature Selection With a Wrapper-Based Search&amp;rdquo;，IEEE access, vol.12,May 2024,pp.62341-62357.[3]A.SHRESTHA, A MAHMOOD,Review of Deep Learning Algorithms and Architectures，IEEE access,VOL. 7, 2019,pp.53040-53065.[4]K.Noor,S.Jan,Vehicle Price Prediction System using Machine Learning Techniques，International Journal of Computer Applications (0975 &amp;ndash; 8887) Volume 167 &amp;ndash; No.9,June 2017,pp.27-31.[5]J. Sharma, S. K. Mitra,Developing a used car pricing model applying Multivariate Adaptive regression Splines approach，Expert Systems With Applications,0957-4174/&amp;copy;2023 Elsevier Ltd.September 2023.[6]A. SHRESTHA, A. MAHMOOD,Review of Deep Learning Algorithms and Architectures，IEEE access,VOL.7, May,2019, PP.53040-53065.[7] 陈潇．人工智能在广播电视节目推荐系统中的应用［J］．电视技术，2023,47(7):163-165,182. DOI:10.16280/j.videoe.2023.07.043.[8] 赖小馨．基于人工智能的个性化推荐系统在电子商务中的应用［J］．知识经济，2024,670(6):37-39.[9] 田丽．人工智能在推荐系统中的应用与分析［J］．文渊（高中版）,2023(9):232-234. DOI:10.12252/j.issn.2096-6288.2023.09.078.[10] 曾新士．基于人工智能的智慧在线服务信息推荐方法及云计算系统：CN202110682159.6［P］．2021-09-03.[11] 深圳宏途教育网络科技有限公司．一种基于人工智能的在线教育资源管理系统及其推荐方法：CN202010328707.0［P］．2020-07-24.</p><pub-id pub-id-type="doi"/></element-citation></ref></ref-list></back></article>
