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Introduction: The motion of a ship at sea is complex. This motion is affected by environmental factors such as wind, waves, and currents. These factors cause the ship’s movement to be nonlinear, ...
Abstract: This work aims to compare two different Feature Extraction Algorithms (FEAs) viz. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), using a K-Nearest Neighbor (KNN) ...
ABSTRACT: This study applies Principal Component Analysis (PCA) to evaluate and understand academic performance among final-year Civil Engineering students at Mbeya University of Science and ...
ABSTRACT: To improve the efficiency of air quality analysis and the accuracy of predictions, this paper proposes a composite method based on Vector Autoregressive (VAR) and Random Forest (RF) models.
The primary goal of this research was to minimise the energy consumed by heating and cooling loads in residential buildings in a sub-humid Mediterranean climate zone. This was achieved by optimising ...
Abstract: Traditional principal component analysis (PCA) is a common linear dimension reduction algorithm, but its dimension reduction effect is relatively poor, and the algorithm takes a long time, ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Mass spectrometry imaging (MSI) is constantly improving in spatial resolving power, ...
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