Structural health monitoring (SHM) techniques have been widely used in long-span bridges. However, due to limitations of computational ability and data analysis methods, the knowledge in ma...

Review of Bridge Structural Health Monitoring Aided by Big Data and Artificial Intelligence: From Condition Assessment to Damage Detection

The artificial neural network for solar radiation prediction and designing solar systems: a systematic literature review

Data mining and wind power prediction: A literature review

https://eis.hu.edu.jo/deanshipfiles/pub110915421.pdf

Knowledge-Based Risk Management framework for Information Technology project

Knowledge elicitation based on genetic programming for non destructive testing of critical aerospace systems

Knowledge discovery and data mining have become areas of growing significance because of the recent increasing demand for KDD techniques, including those used in machine learning, databases, statistics, knowledge acquisition, data visualization, and high performance computing. Knowledge discovery and data mining can be extremely beneficial for the field of Artificial Intelligence in many areas, such as industry, commerce, government, education and so on. The relation between Knowledge and Data Mining, and Knowledge Discovery in Database (KDD) process are presented in the paper. Data mining theory, Data mining tasks, Data Mining technology and Data Mining challenges are also proposed. This is an belief abstract for an invited talk at the workshop.

Advancing Knowledge Discovery and Data Mining

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Advancing Knowledge Discovery and Data Mining