Inicio  /  QUALITY PROGRESS  /  Vol: 39 Núm: 2 Par: 0 (2006)  /  Artículo
ARTÍCULO
TITULO

Data mining for quality

 Artículos similares

       
 
Zhen Liu, Qifeng Yang, Anlue Wang and Xingyu Gu    
In the process of driving in an underground interchange, drivers are faced with many challenges, such as being in a closed space, visual changes alternating between light and dark conditions, complex road conditions in the confluence section, and dense s... ver más
Revista: Infrastructures

 
Boris Stanoev, Goran Mitrov, Andrea Kulakov, Georgina Mirceva, Petre Lameski and Eftim Zdravevski    
With the exponential growth of data, extracting actionable insights becomes resource-intensive. In many organizations, normalized relational databases store a significant portion of this data, where tables are interconnected through some relations. This ... ver más

 
Lijun Zu, Wenyu Qi, Hongyi Li, Xiaohua Men, Zhihui Lu, Jiawei Ye and Liang Zhang    
The digital transformation of banks has led to a paradigm shift, promoting the open sharing of data and services with third-party providers through APIs, SDKs, and other technological means. While data sharing brings personalized, convenient, and enriche... ver más
Revista: Future Internet

 
Min Hu, Fan Zhang and Huiming Wu    
Various abnormal scenarios might occur during the shield tunneling process, which have an impact on construction efficiency and safety. Existing research on shield tunneling construction anomaly detection typically designs models based on the characteris... ver más
Revista: Applied Sciences

 
Yilei Wang, Yuelin Hu, Wenliang Xu and Futai Zou    
Dark web vendor identification can be seen as an authorship aliasing problem, aiming to determine whether different accounts on different markets belong to the same real-world vendor, in order to locate cybercriminals involved in dark web market transact... ver más
Revista: Applied Sciences