建筑材料价格数据用于建筑中的预测性成本估计
Oluwambo Tolulope Olowe1, Ayodele Adebiyi1, Ibidun Christiana Obagbuwa2
1Department of Computer Science, Landmark University, Omu Aran, Nigeria.
Data in brief
|October 23, 2025
概括
一个新的建筑材料数据集提供了对尼日利亚建筑材料价格波动的见解. 该资源帮助行业专业人士和政策制定者进行成本估计,采购规划和财务预测.
科学领域:
- 建设管理建设管理.
- 数据科学数据科学数据科学
- 经济学 经济学 经济学
背景情况:
- 尼日利亚的建筑材料价格表现出显著的历史和实时波动.
- 缺乏结构化,全面的数据阻碍了尼日利亚建筑业的有效成本估计,采购规划和财务预测.
研究的目的:
- 介绍建筑材料数据集,这是分析尼日利亚建筑材料价格动态的新型资源.
- 为建筑行业的成本估计,采购和财务管理提供数据驱动决策的基础.
主要方法:
- 通过结构化调查和二次来源 (在线市场,行业报告) 收集数据.
- 数据预处理包括清理,Min-Max规范化和功能工程.
- 集成到BuildCES系统,用于使用长短期存储器 (LSTM) 模型进行价格预测和成本估计.
主要成果:
- 建筑材料数据集提供了一个时间序列,材料类型的表格格式,定价变化和影响经济因素.
- 在BuildCES系统中应用的LSTM模型展示了价格预测和成本估计的能力.
- 该数据集有助于数据驱动的采购优化和合同管理.
结论:
- 建筑材料数据集解决了关键的数据缺口,支持尼日利亚的研究,行业基准分析和政策制定.
- 该数据集通过数据驱动的方法促进建筑行业的经济稳定,透明度和可持续性.
- 未来的改进旨在整合区块链,API驱动的实时定价和地理空间分析以评估区域价格差异.
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