Abstract: This paper presents a novel approach for the detection and classification of shading and short-circuit faults in photovoltaic (PV) systems by comparing the performance of Support Vector ...
Abstract: Principal component analysis (PCA) is considered as an important technique for dimension reduction of the data in various artificial intelligence/machine learning applications. One of the ...
Inside living cells, mitochondria divide, lysosomes travel, and synaptic vesicles pulse—all in three dimensions (3Ds) and constant motion. Capturing these events with clarity is vital not just for ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Non-Commercial (NC): Only non-commercial uses of the work are permitted. No ...
The traditional coal type identification method needs to measure a variety of parameters of coal samples to obtain more accurate results, and the detection process is time-consuming and laborious, and ...
ABSTRACT: This study investigates the use of a decision tree classification model, combined with Principal Component Analysis (PCA), to distinguish between Assam and Bhutan ethnic groups based on ...
1 Department of Computer Engineering, Northeastern University, Boston, USA. 2 Department of Computer Science, Rochester Institute of Technology, Rochester, USA. 3 Department of Computer Engineering, ...
The authors present a critique of current usage of principal component analysis in geometric morphometrics, making a compelling case with benchmark data that standard techniques perform poorly. The ...
Revised: This Reviewed Preprint has been revised by the authors in response to the previous round of peer review; the eLife assessment and the public reviews have been updated where necessary by the ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results