Research on Performance Detection and Evaluation Platform Based on Data Analyzation

2014 ◽  
Vol 962-965 ◽  
pp. 2801-2808
Author(s):  
Dong Hui Li ◽  
Li Jing Shen ◽  
Xiao Zhi Wu ◽  
Chen Ling Pan ◽  
Guang Xin Zhu ◽  
...  
Keyword(s):  
Data Mining ◽  
Evaluation Model ◽  
Data Mining Algorithm ◽  
Decision Tools ◽  
Mining Algorithm ◽  
Performance Evaluation Model ◽  
Information Detection ◽  
And Performance ◽  
Evaluation Platform ◽  
Very High

It is obliged to do research on performance detection and analyzation technology of information system with deepen development of smart grid to avoid risk and investment. This paper proposed a method of information detection and analyzing based on data mining algorithm and performance evaluation model. It is constructed evaluation platform with related smart decision tools which provided by method mention above. Finally, it is proved that the platform has a very high practical value and promotion prospects.

scholarly journals A product-centric data mining algorithm for targeted promotions

2020 ◽  
Vol 54 ◽  
pp. 101940 ◽  
Author(s):  
Raymond Moodley ◽  
Francisco Chiclana ◽  
Fabio Caraffini ◽  
Jenny Carter
Keyword(s):  
Data Mining ◽  
Data Mining Algorithm ◽  
Mining Algorithm

scholarly journals Life-cycle Asset Management in Residential Developments Building on Transport System Critical Attributes via a Data-mining Algorithm

Buildings ◽  
2018 ◽  
Vol 9 (1) ◽  
pp. 1 ◽  
Author(s):  
Umair Hasan ◽  
Andrew Whyte ◽  
Hamad Al Jassmi
Keyword(s):  
Data Mining ◽  
Life Cycle ◽  
Built Environment ◽  
Transport System ◽  
Asset Management ◽  
Public Transport ◽  
Categorical Variables ◽  
Data Mining Algorithm ◽  
Large Set ◽  
Mining Algorithm

Public transport can discourage individual car usage as a life-cycle asset management strategy towards carbon neutrality. An effective public transport system contributes greatly to the wider goal of a sustainable built environment, provided the critical transit system attributes are measured and addressed to (continue to) improve commuter uptake of public systems by residents living and working in local communities. Travel data from intra-city travellers can advise discrete policy recommendations based on a residential area or development’s public transport demand. Commuter segments related to travelling frequency, satisfaction from service level, and its value for money are evaluated to extract econometric models/association rules. A data mining algorithm with minimum confidence, support, interest, syntactic constraints and meaningfulness measure as inputs is designed to exploit a large set of 31 variables collected for 1,520 respondents, generating 72 models. This methodology presents an alternative to multivariate analyses to find correlations in bigger databases of categorical variables. Results here augment literature by highlighting traveller perceptions related to frequency of buses, journey time, and capacity, as a net positive effect of frequent buses operating on rapid transit routes. Policymakers can address public transport uptake through service frequency variation during peak-hours with resultant reduced car dependence apt to reduce induced life-cycle environmental burdens of buildings by altering residents’ mode choices, and a potential design change of buildings towards a public transit-based, compact, and shared space urban built environment.

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