With the intelligent development of road traffic control and management,higher requirements for the accuracy and effectiveness of traffic data have been put forward.The issue of how to collect and integrate data for t...With the intelligent development of road traffic control and management,higher requirements for the accuracy and effectiveness of traffic data have been put forward.The issue of how to collect and integrate data for traffic scenes has sought importance in this field as various treatment technologies have emerged.A lot of research work have been carried out from the theoretical aspect to engineering application.展开更多
在智慧城市发展进程中,交通系统的精细化管理和智能化服务面临海量异构数据处理的挑战。传统交通信息查询系统存在数据源异构性强、自然语言交互能力不足、长尾查询场景覆盖有限等问题。文章基于ChatGLM3大语言模型,创新性地构建了融合N...在智慧城市发展进程中,交通系统的精细化管理和智能化服务面临海量异构数据处理的挑战。传统交通信息查询系统存在数据源异构性强、自然语言交互能力不足、长尾查询场景覆盖有限等问题。文章基于ChatGLM3大语言模型,创新性地构建了融合NL2SQL(Natural Language to Structured Query Language)技术的智能问数系统,通过动态Schema对齐、LoRA微调优化及多维度提示工程技术,实现了交通领域复杂自然语言查询到精准SQL指令的智能转换。实验结果表明,经过微调的模型在交通信息查询任务中准确率达到78.9%,较基线模型提升15.8个百分点。本研究为交通管理智能化转型提供了创新技术路径,并对大模型在垂直领域的深度适配进行了系统性探索。展开更多
文摘With the intelligent development of road traffic control and management,higher requirements for the accuracy and effectiveness of traffic data have been put forward.The issue of how to collect and integrate data for traffic scenes has sought importance in this field as various treatment technologies have emerged.A lot of research work have been carried out from the theoretical aspect to engineering application.
文摘在智慧城市发展进程中,交通系统的精细化管理和智能化服务面临海量异构数据处理的挑战。传统交通信息查询系统存在数据源异构性强、自然语言交互能力不足、长尾查询场景覆盖有限等问题。文章基于ChatGLM3大语言模型,创新性地构建了融合NL2SQL(Natural Language to Structured Query Language)技术的智能问数系统,通过动态Schema对齐、LoRA微调优化及多维度提示工程技术,实现了交通领域复杂自然语言查询到精准SQL指令的智能转换。实验结果表明,经过微调的模型在交通信息查询任务中准确率达到78.9%,较基线模型提升15.8个百分点。本研究为交通管理智能化转型提供了创新技术路径,并对大模型在垂直领域的深度适配进行了系统性探索。
