A machine learning based credit card fraud detection using the GA algorithm for feature selection
The recent advances of e-commerce and e-payment systems have sparked an increase in
financial fraud cases such as credit card fraud. It is therefore crucial to implement …
financial fraud cases such as credit card fraud. It is therefore crucial to implement …
An improved ant colony optimization algorithm based on hybrid strategies for scheduling problem
W Deng, J Xu, H Zhao - IEEE access, 2019 - ieeexplore.ieee.org
In this paper, an improved ant colony optimization (ICMPACO) algorithm based on the multi-
population strategy, co-evolution mechanism, pheromone updating strategy, and …
population strategy, co-evolution mechanism, pheromone updating strategy, and …
Research on expansion and classification of imbalanced data based on SMOTE algorithm
S Wang, Y Dai, J Shen, J Xuan - Scientific reports, 2021 - nature.com
With the development of artificial intelligence, big data classification technology provides the
advantageous help for the medicine auxiliary diagnosis research. While due to the different …
advantageous help for the medicine auxiliary diagnosis research. While due to the different …
Daily activity feature selection in smart homes based on pearson correlation coefficient
Y Liu, Y Mu, K Chen, Y Li, J Guo - Neural processing letters, 2020 - Springer
In the case of a smart home, the ability to recognize daily activities depends primarily on the
strategy used for selecting the appropriate features related to these activities. To achieve the …
strategy used for selecting the appropriate features related to these activities. To achieve the …
Fault diagnosis method based on principal component analysis and broad learning system
H Zhao, J Zheng, J Xu, W Deng - IEEE Access, 2019 - ieeexplore.ieee.org
Traditional feature extraction methods are used to extract the features of signal to construct
the fault feature matrix, which exists the complex structure, higher correlation, and …
the fault feature matrix, which exists the complex structure, higher correlation, and …
Knowledge discovery for course choice decision in Massive Open Online Courses using machine learning approaches
M Nilashi, B Minaei-Bidgoli, A Alghamdi… - Expert Systems with …, 2022 - Elsevier
Abstract Massive Open Online Courses (MOOCs) provide learners with high-quality and
flexible online courses with no limitations regarding time and location. Detecting users' …
flexible online courses with no limitations regarding time and location. Detecting users' …
[HTML][HTML] Improving laser cutting quality of polymethylmethacrylate sheet: experimental investigation and optimization
Motivated by the need to enhance the kerf quality during cutting of Poly (methyl
methacrylate)(PMMA) sheets using pulsed CO 2 laser beam, this study presents an …
methacrylate)(PMMA) sheets using pulsed CO 2 laser beam, this study presents an …
[HTML][HTML] Integrating deep learning and logging data analytics for lithofacies classification and 3D modeling of tight sandstone reservoirs
JJ Liu, JC Liu - Geoscience Frontiers, 2022 - Elsevier
The lithofacies classification is essential for oil and gas reservoir exploration and
development. The traditional method of lithofacies classification is based on “core calibration …
development. The traditional method of lithofacies classification is based on “core calibration …
Developer activity motivated bug triaging: via convolutional neural network
S Guo, X Zhang, X Yang, R Chen, C Guo, H Li… - Neural Processing …, 2020 - Springer
As bugs become prevalent in software development, bug triaging has become one of the
most important activities in software maintenance. To decrease the time cost in manual work …
most important activities in software maintenance. To decrease the time cost in manual work …
An oversampling method for class imbalance problems on large datasets
F Rodríguez-Torres, JF Martínez-Trinidad… - Applied Sciences, 2022 - mdpi.com
Several oversampling methods have been proposed for solving the class imbalance
problem. However, most of them require searching the k-nearest neighbors to generate …
problem. However, most of them require searching the k-nearest neighbors to generate …