AIMC Topic: Algorithms

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FoSSA Optimization-Based SVM Classifier for the Recognition of Partial Discharge Patterns in HV Cables.

Computational intelligence and neuroscience
In order to enhance the classification accuracy and the generalization performance of the SVM classifier in cable partial discharge (PD) pattern recognition, a firefly optimized sparrow search algorithm (FoSSA) is proposed to optimize its kernel func...

Application of a Hybrid Model of Big Data and BP Network on Fault Diagnosis Strategy for Microgrid.

Computational intelligence and neuroscience
Aiming at the characteristics of timely transmission, rapid update, and large magnitude of microgrid data, based on the large data samples generated by microgrid operation, a fault diagnosis and analysis method of microgrid systems supported by big d...

A Unified Neural Network Framework for Extended Redundancy Analysis.

Psychometrika
Component-based approaches have been regarded as a tool for dimension reduction to predict outcomes from observed variables in regression applications. Extended redundancy analysis (ERA) is one such component-based approach which reduces predictors t...

GHNN: Graph Harmonic Neural Networks for semi-supervised graph-level classification.

Neural networks : the official journal of the International Neural Network Society
Graph classification aims to predict the property of the whole graph, which has attracted growing attention in the graph learning community. This problem has been extensively studied in the literature of both graph convolutional networks and graph ke...

Diagnostic accuracy of a commercially available deep-learning algorithm in supine chest radiographs following trauma.

The British journal of radiology
OBJECTIVES: Trauma chest radiographs may contain subtle and time-critical pathology. Artificial intelligence (AI) may aid in accurate reporting, timely identification and worklist prioritisation. However, few AI programs have been externally validate...

Machine-Learning-Assisted Recognition on Bioinspired Soft Sensor Arrays.

ACS nano
Soft interfaces with self-sensing capabilities play an essential role in environment awareness and reaction. The growing overlap between materials and sensory systems has created a myriad of challenges for sensor integration, including the design of ...

Condition Monitoring of Ball Bearings Based on Machine Learning with Synthetically Generated Data.

Sensors (Basel, Switzerland)
Rolling element bearing faults significantly contribute to overall machine failures, which demand different strategies for condition monitoring and failure detection. Recent advancements in machine learning even further expedite the quest to improve ...

Structural Health Monitoring of Dams Based on Acoustic Monitoring, Deep Neural Networks, Fuzzy Logic and a CUSUM Control Algorithm.

Sensors (Basel, Switzerland)
Internal erosion is the most important failure mechanism of earth and rockfill dams. Since this type of erosion develops internally and silently, methodologies of data acquisition and processing for dam monitoring are crucial to guarantee a safe oper...

Fast protein structure comparison through effective representation learning with contrastive graph neural networks.

PLoS computational biology
Protein structure alignment algorithms are often time-consuming, resulting in challenges for large-scale protein structure similarity-based retrieval. There is an urgent need for more efficient structure comparison approaches as the number of protein...

A Multistage Heterogeneous Stacking Ensemble Model for Augmented Infant Cry Classification.

Frontiers in public health
Understanding the reason for an infant's cry is the most difficult thing for parents. There might be various reasons behind the baby's cry. It may be due to hunger, pain, sleep, or diaper-related problems. The key concept behind identifying the reaso...