检索结果-内蒙古大学图书馆

Research on CART Model of Mass Concrete Temperature Prediction Based on big data processing technology

IEEE ACCESS 2022年 10卷 32845-32854页

作者： Li Baoyu Li Guoxing Wang Guiyu Zhang Guofeng Yang Man Henan Vocat Coll Water Conservancy & Environm Zhengzhou 450008 Peoples R China Henan 2 Hydraul Engn Bur Zhengzhou 450016 Peoples R China Zhengzhou Univ Sch Hydraul Sci & Engn Zhengzhou 450001 Peoples R China

Due to the influence of temperature changes or temperature gradients in the construction process of mass concrete, temperature cracks will occur in the concrete. In order to achieve a reasonable prediction of the temperature change of the mass concrete during the construction process and accurately obtain the temperature change trend, this paper attempts to construct a CART prediction model based on the big data processing technology based on the characteristics of the temperature change of the mass concrete. This paper introduces in detail how to use data processing methods such as outlier identification, missing value filling and random error elimination to improve data quality, as well as the method for constructing the CART prediction model, and combines engineering examples to demonstrate the feasibility of the model method. The results show that the model and method can better predict the temperature change of mass concrete. It has high prediction accuracy and can provide necessary guidance for practical engineering.

关键词： Mass concrete temperature big data processing technology CART prediction model

来源：评论

学校读者我要写书评

暂无评论

Climatic and Environmental Characteristics of Beijing Based on Rapid processing technology of Urban Meteorological big data

引用

Journal of Landscape Research 2021年第1期13卷 67-72页

作者： PENG Li CHEN Heming XU Zhenghou North China University of Technology Beijing 100144China

The meteorological big data in Beijing area are typical multi-dimensional big data containing spatiotemporal characteristics,which have important research value for researches related to urban human settlement *** the help of computer programming and software processing,big data crawling,integration,extraction and multi-dimensional information fusion can be realized quickly and effectively,so as to obtain the data set needed for research and realize the target of *** big data analysis of wind environment,thermal environment and total atmospheric suspended particulate pollutants in Beijing area,it was found that the average wind speed in Beijing area decreased signifi cantly in recent 40 years,while the surface temperature increased signifi cantly;urban heat island effect was signifi cant,and the phenomenon of atmospheric suspended particulate pollution was relatively *** spatial distribution of the three climatic and environmental data was not balanced and had signifi cant regularity and *** urban ventilation corridors and improving urban ventilation capacity is a feasible way to improve urban heat island effect and reduce urban climate issues such as atmospheric particulate pollution.

关键词： Beijing big data processing technology Wind environment Thermal environment Atmospheric suspended particulate

来源：评论

学校读者我要写书评

暂无评论

Design of Accounting Information big data Analysis Platform Based on Cloud Computing 11th

Design of Accounting Information Big Data Analysis Platform ...

引用

11th International Conference on Applications and Techniques in Cyber Intelligence, ATCI 2023

作者： Duan, Yu Intelligent Finance and Economics Industry School Shandong Institute of Commerce and Technology Shandong Jinan250103 China

The advent of the era of big data provides unprecedented opportunities for the transformation and innovation of corporate accounting, but also poses severe challenges to its development. Taking Company M as an example, this paper analyzes the accounting transformation under the current big data environment, and raises many new issues, such as the security of accounting information and the authenticity of information, and the transformation of accounting information data processing mode. At the same time, enterprises are also facing many opportunities, such as: the impact on accounting confirmation, enterprise financial forecasting, decision-making and cost control, and the management of enterprise accounting electronic documents in the cloud computing environment and big data environment. This paper intends to study the accounting information system under the environment of cloud computing and big data, aiming to improve the security and reliability of enterprise accounting information. This article constructed an accounting information big data analysis platform. Through experimental testing, it was found that before using the platform, the cost of hardware investment and system maintenance in 2019 was 19,803 yuan, while the cost after using the platform was 13,256 yuan. Studies have shown that using big data processing technology to extract useful information from huge financial and accounting databases can help enhance the core competitiveness of enterprises. © 2024 The Authors. Published by Elsevier B.V.

关键词： Accounting Information big data Analysis Platform big data processing technology Cloud Computing Construction of Accounting Informatization Enterprise Financial Cost Control

来源：评论

学校读者我要写书评

暂无评论

Design of Accounting Information big data Analysis Platform Based on Cloud Computing

引用

Procedia Computer Science 2024年 247卷 1128-1136页

作者： Yu Duan Intelligent Finance and Economics Industry School Shandong Institute of Commerce and Technology Jinan 250103 Shandong China

关键词： big data processing technology Construction of Accounting Informatization Accounting Information big data Analysis Platform Cloud Computing Enterprise Financial Cost Control

来源：评论

学校读者我要写书评

暂无评论

Research and construction of student management platform for special needs students with decision tree model and big data technology

Systems and Soft Computing

引用

Systems and Soft Computing 2025年 7卷

作者： Jingkun Jin Institutes of Chifeng Chifeng 024000 China

This study focuses on enhancing the intelligence and operational efficiency of student management platforms. Given the critical role of data-driven decision-making in promoting educational quality improvement, the research deeply integrates decision tree models with big data processing technologies such as Hadoop and Spark to optimize student management strategies. Through improvements to the decision tree model, the accuracy of student behavior prediction has significantly increased from the original 78 % to 92 %, greatly enhancing predictive accuracy. Additionally, leveraging big data technology allows for real-time data updates and analysis, significantly shortening data processing time, ensuring that the effective insights needed for management decisions can be provided promptly. Furthermore, the platform innovatively constructs an intelligent early warning system that can keenly capture potential learning issues among students and intervene in a timely manner; the personalized learning recommendation system tailors course plans based on student behavior patterns and preferences, effectively improving learning efficiency. The results of this research fully demonstrate the significant value of incorporating advanced data processing technologies into student management platforms, laying a solid foundation for building intelligent education systems. It illustrates how data-driven decision-making aids in achieving personalized and equitable education, showcasing the tremendous transformative potential of educational informationization.

关键词： Decision tree model big data processing technology Student management platform

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：