An overall analysis method of urban road parking lots based on data mining

We used the principle of hyperlink analysis method to mine the website data according to the indicators of the hyperlink analysis. We selected Taobao.com as an object of study. The evaluation indicators of network marketing effect were page views, sales quantity, sales, the number of adding store to bookmark . According to our research, we find Taobao.com stores can use data mining tool to obtain the very good marketing effect.

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Application of data mining technology and wireless network sensing technology in sports training index analysis

10.21203/rs.3.rs-17559/v1 ◽

2020 ◽

Author(s):

Liqiu Qian ◽

Jiatong Liu

Keyword(s):

Data Mining ◽

Test Accuracy ◽

Analysis Method ◽

Sports Training ◽

Analysis Model ◽

Data Types ◽

Mining Technology ◽

Accuracy Test ◽

Index Analysis ◽

Sensing Technology

Abstract The conventional analysis method can provide a general analysis of sports training index, but its ability is relatively low when analyzing niche data. To solve this problem, this paper proposes data mining technology. First, the indicator parameter classification is determined, then the data mining technology is imported, the sports training analysis mechanism is established through this technology, and the construction of the index analysis model is completed. The model is used to analyze the process of niche data mining, and effective data of training indicators are obtained. Deep learning is a method of machine learning based on representation of data.Through the coverage test, accuracy test and immunity test, the variable parameters of the comprehensive analysis capability are determined. Further calculation of this parameter shows that the comprehensive ability of the data mining application analysis method is improved by 37.14% compared with the conventional method, which is suitable for analysis of niche sports training indicators of different data types.

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Exploring Drivers’ Route Choice Behaviors in Urban Road Network by Data Mining

CICTP 2015 ◽

10.1061/9780784479292.240 ◽

2015 ◽

Author(s):

Ya Chen ◽

Jun Li

Keyword(s):

Data Mining ◽

Road Network ◽

Route Choice ◽

Urban Road Network ◽

Urban Road

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A Novel Urban Road Management System Based On Data Mining

International Journal of Industrial and Systems Engineering ◽

10.1504/ijise.2020.10033539 ◽

2020 ◽

Vol 1 (1) ◽

pp. 1

Author(s):

Min Jiang ◽

Min Li ◽

Jiapeng Shen ◽

Guanlin Chen

Keyword(s):

Data Mining ◽

Management System ◽

Urban Road ◽

Road Management

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The Application of Data Mining in the Civil Aviation Accident Analysis

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.241-244.3000 ◽

2012 ◽

Vol 241-244 ◽

pp. 3000-3004

Author(s):

Dai Wu Zhu ◽

Yin Ni

Keyword(s):

Data Mining ◽

Set Theory ◽

Rough Set ◽

Rough Set Theory ◽

Attribute Reduction ◽

Passive State ◽

Civil Aviation ◽

Accident Analysis ◽

Analysis Method ◽

Accident Prediction

At present, our analysis of the aviation accident mainly limited to the methods of mathematical statistics, the analysis method means of a single, and in a passive state, so the accident prediction is poor. This paper, basis on the rough set theory in data mining and preferential information ,we improve the rough set attribute reduction algorithm, and applied to civil aviation accident analysis to indentify the potential law of accident.

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Data Mining Based Analysis Method for Chinese Elders' Survival Self-Evaluation in Universal Design

2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics ◽

10.1109/ihmsc.2014.57 ◽

2014 ◽

Cited By ~ 1

Author(s):

Fangyan Zhang ◽

Hao Liang

Keyword(s):

Data Mining ◽

Universal Design ◽

Analysis Method ◽

Self Evaluation ◽

Chinese Elders

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Analysis of energy consumption structure based on K-means clustering algorithm

E3S Web of Conferences ◽

10.1051/e3sconf/202126701054 ◽

2021 ◽

Vol 267 ◽

pp. 01054

Author(s):

Weizheng Kong ◽

Yaohua Wang ◽

Hongcai Dai ◽

Liujun Zhao ◽

Chunming Wang

Keyword(s):

Data Mining ◽

Energy Consumption ◽

Structure Analysis ◽

Clustering Algorithm ◽

Analysis Method ◽

Environmental Characteristics ◽

Qinghai Province ◽

Consumption Structure ◽

Coefficient Method

In order to solve the problem of huge and messy data in the process of analyzing energy consumption structure in different regions, an energy consumption structure analysis method based on K-means clustering algorithm is proposed, and the elbow method and contour coefficient method are used to analyze the data in Qinghai Province. The consumption structure was analyzed and the algorithm was verified. The results show that the algorithm can efficiently and quickly perform data mining and clustering based on local economic and environmental characteristics, which greatly improve the convenience of energy consumption structure analysis.

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