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Machine learning-based fatigue life prediction of metal materials: Perspectives of physics-informed and data-driven hybrid methods
Fatigue life prediction is critical for ensuring the safe service and the structural integrity of
mechanical structures. Although data-driven approaches have been proven effective in …
mechanical structures. Although data-driven approaches have been proven effective in …
A survey on underwater computer vision
Underwater computer vision has attracted increasing attention in the research community
due to the recent advances in underwater platforms such as of rovers, gliders, autonomous …
due to the recent advances in underwater platforms such as of rovers, gliders, autonomous …
Recent advances in machine learning-assisted fatigue life prediction of additive manufactured metallic materials: A review
Additive manufacturing features rapid production of complicated shapes and has been
widely employed in biomedical, aeronautical and aerospace applications. However, additive …
widely employed in biomedical, aeronautical and aerospace applications. However, additive …
A review on imbalanced data classification techniques
Most all datasets that hold real-time data have an imbalanced organization of class
instances. The total quantity of instances in certain classes is substantially greater than other …
instances. The total quantity of instances in certain classes is substantially greater than other …
Machine learning classifiers based classification for IRIS recognition
Classification is the most widely applied machine learning problem today, with
implementations in face recognition, flower classification, clustering, and other fields. The …
implementations in face recognition, flower classification, clustering, and other fields. The …
A multi-joint continuous motion estimation method of lower limb using least squares support vector machine and zeroing neural network based on semg signals
In this paper, an active motion intention recognition technology in view of least squares
support vector machine (LS-SVM) and zeroing neural network (ZNN) is proposed, and the …
support vector machine (LS-SVM) and zeroing neural network (ZNN) is proposed, and the …
A Filter-APOSD approach for feature selection and linguistic knowledge discovery
J Yu, L Yuan, T Zhang, J Fu, Y Cao… - Journal of Intelligent & …, 2023 - content.iospress.com
The development of natural language processing promotes the progress of general
linguistic studies. Based on the selected features and the extracted rules for word sense …
linguistic studies. Based on the selected features and the extracted rules for word sense …
Intelligent fault prediction with wavelet-SVM fusion in coal mine
Fault prediction in coal mining is crucial for safety, and recent technological advancements
are steering this field towards supervised intelligent interpretation, moving beyond traditional …
are steering this field towards supervised intelligent interpretation, moving beyond traditional …
Animal-borne acoustic data alone can provide high accuracy classification of activity budgets
Background Studies on animal behaviour often involve the quantification of the occurrence
and duration of various activities. When direct observations are challenging (eg, at night, in a …
and duration of various activities. When direct observations are challenging (eg, at night, in a …
A method for class-imbalance learning in android malware detection
J Guan, X Jiang, B Mao - Electronics, 2021 - mdpi.com
More and more Android application developers are adopting many different methods
against reverse engineering, such as adding a shell, resulting in certain features that cannot …
against reverse engineering, such as adding a shell, resulting in certain features that cannot …