Real-time and precise prediction of geological conditions is extremely beneficial to the safe
and efficient construction of slurry pressure balanced shield machines (SPBMs), especially …

Modifying the metaheuristics as a striking alternative of basic algorithms is outstanding and
efficient scientific approach in optimization of engineering problems to improve robustness …

The detection of faulty machinery and its automated diagnosis is an industrial priority
because efficient fault diagnosis implies efficient management of the maintenance times …

The quality of training data plays a decisive role in the establishment of intelligent models.
Since raw data obtained from the real world are usually entwined with noise due to variety of …

Instance selection, as an important data pre-processing task, is widely used in supervised
classification. Recently, a series of instance selection algorithms with different techniques …

The problem of simultaneously predicting multiple real-valued outputs using a shared set of
input variables is known as multi-target regression and has attracted considerable interest in …

The large amount of data that is produced today with new technologies is an impediment for
machine learning algorithms to work correctly, both due to the memory requirements and the …

Multilabel classification as a data mining task has recently attracted greater research
interest. Many current data mining applications address problems having instances that …

Instance selection and construction methods were originally designed to improve the
performance of the k-nearest neighbors classifier by increasing its speed and improving the …

Multi-label classification has recently attracted research interest as a data mining task. Many
current applications in data mining address problems that have instances belonging to more …