This thesis aims to estimate pore fluid saturation values in an oil sands reservoir using ensemble tree based machine learning models. Oil sands reservoirs provide an interesting opportunity to explore a relatively new ...

Inventory management, as an important business issue, plays a significant role in promoting business development. This study aims to apply data mining techniques, such as time series clustering and time series prediction ...

This research proposes a new network-based method for the assessment of earthquake relationships in space-time-magnitude patterns. The method is applied to the study of volcanic seismicity in Hawaii, over a time period ...

Identifying pattern groups from large temporal data sets, preserving clustering schemes obtained from different heuristic algorithms and presenting temporal pattern profiles for a specific day and previous days are significant ...

Clustering is an important aspect of data mining. Many data mining applications tend to be more amenable to non-conventional clustering techniques. In this research three clustering methods are employed to analyze the web ...