A novel linear assorted classification method based association rule mining with spatial data

Smart, Philip D.; Thanammal, K. K.; Sujatha, S.

doi:10.1007/s12046-020-01548-2

Cited by 4 publications

(1 citation statement)

References 16 publications

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“…Generally speaking, the association degree should be more than 50%, otherwise the mining value of association rules is not high, so the distance value of clustering center can be used as a reference value to meet the requirement of 50% association degree of rules, so as to improve the scientificity of parameter setting. Find the cluster group which is less than the distance parameter, and these cluster groups are the maximum frequent bit set, so we can use the idea of association rule algorithm to generate rules to generate sub rule set [13]. Through the generation of this rule, we can mine the association rules of rural governance resource endowment attribute data.…”

Section: Design Rural Governance Resource Endowment Clustering Algorithmmentioning

confidence: 99%

Analysis of Rural Governance and Resource Endowment Modeling Based on Association Rule Algorithm

Gan

Wang²

2023

SPEE

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At present, in the modeling and analysis of rural resource endowment, the internal relationship of elements is ignored, resulting in inaccurate judgment of governance level. Therefore, the modeling and analysis of rural governance and construction resource endowment is based on association rule algorithm. Identify the characteristics of rural governance resource elements as the information basis, design the clustering algorithm to determine the association rules and element attributes, and use the association rules algorithm to mine the internal relationship of resource endowment. Taking the information of rural governance resource endowment as the direction, the evaluation index is selected, and the rural resource endowment measurement model is constructed. The experimental results show that the modeling analysis results based on association rule algorithm are consistent with the actual governance development orientation, while the modeling analysis results based on evolution analysis algorithm and special group analysis algorithm are quite different from the actual governance development orientation. Therefore, the modeling analysis in this paper is more accurate, which is conducive to the accurate implementation of governance policies and rural planning.

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Section: Design Rural Governance Resource Endowment Clustering Algorithmmentioning

confidence: 99%

Analysis of Rural Governance and Resource Endowment Modeling Based on Association Rule Algorithm

Gan

Wang²

2023

SPEE

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Evaluation Method of Chemical Technology Safety Practical Operation Ability Based on Stochastic Model

Wang

2021

Wireless Communications and Mobile Computing

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The current evaluation method does not consider the coordination and overall situation of various practical skills, which affects the evaluation contact degree and leads to hidden dangers of production safety. Therefore, an evaluation method of chemical technology safety practical operation ability based on a stochastic model is proposed. Using association rules to design the feature mining algorithm of practical operation ability, combined with crosslayer coding strategy, the mapping relationship between safety accidents and practical operation ability is established. The chemical safety practical operation skills are simulated by a random model, and the practical operation skills are classified and coordinated according to the simulation predictive control results. According to the coordination results, the evaluation index system is constructed, the index weight is determined, and the evaluation model of chemical technology safety operation ability is constructed. The experimental results show that the maximum connection degree of the evaluation method designed in this paper is 88.06%, and the evaluation results are more accurate, which is helpful to improve the production safety of chemical enterprises.

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Modeling Spatial Riding Characteristics of Bike-Sharing Users Using Hotspot Areas-Based Association Rule Mining

Sun

Lü

2022

Journal of Advanced Transportation

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This study aims to investigate the spatial riding characteristics under different demand scenarios using association rule mining with hotspot detection, and to establish the subordinate rules between bike-sharing demand and land elements and between land elements. To reduce deviation from modifiable areal unit problem (MAUP) and improve objectivity and accuracy, we impose spatial constraints using the hotspot detection model instead of the square grid and traditional traffic zone. The bike-sharing trajectory-based kernel density algorithm is employed to explore the optimum analysis locations and the analysis areas with the relatively high demand. More importantly, the research featured here involves five demand scenarios for the differentiation of riding characteristics. The results show that the most significant influencers on bike-sharing demand include financial insurance facilities, dining facilities, and landscapes. As for characteristics of riding destination, the combinations between landscapes and financial insurance facilities, between landscapes and companies/enterprises, and between companies/enterprises and financial insurance facilities are more likely to be visited simultaneously. These findings make us understand urban spatial structure in response to traffic plan and provide evidence for bike-sharing dispatch optimization.

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A novel linear assorted classification method based association rule mining with spatial data

Cited by 4 publications

References 16 publications

Analysis of Rural Governance and Resource Endowment Modeling Based on Association Rule Algorithm

Analysis of Rural Governance and Resource Endowment Modeling Based on Association Rule Algorithm

Evaluation Method of Chemical Technology Safety Practical Operation Ability Based on Stochastic Model

Modeling Spatial Riding Characteristics of Bike-Sharing Users Using Hotspot Areas-Based Association Rule Mining

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