Feature selection is an important task in data mining and machine learning to reduce the
dimensionality of the data and increase the performance of an algorithm, such as a …

Feature selection (FS) is a fundamental big data task, improving classification performance
by selecting a relevant feature subset to mitigate thecurse of dimensionality'. As the number …

Construction productivity is a major research interest within the construction domain.
Because construction is a labor-intensive industry, previous research has often focused on …

Feature selection is an important data preprocessing step in machine learning and data
mining, such as classification tasks. Research on feature selection has been extensively …

The performance of construction systems (eg, activities, operations, projects) is commonly
measured using different indicators, such as productivity or production rate. The accurate …

In smart factories, the data collected by Internet-of-things sensors is enormous and includes
a lot of noise and missing values. To address this big data problem, metaheuristic is one of …

The dimension and size of data is growing rapidly with the extensive applications of
computer science and lab based engineering in daily life. Due to availability of vagueness …

The term “big data” characterizes the massive amounts of data generation by the advanced
technologies in different domains using 4Vs–volume, velocity, variety, and veracity-to …

Data reduction is becoming increasingly relevant due to the enormous amounts of data that
are constantly being produced in many fields of research. Instance selection is one of the …

Predicting and optimizing performance in earthmoving operations is critical, because they
are essential to many construction projects. The complexity of modeling earthmoving …