A Modular Neural Network Scheme Applied to Fault Diagnosis in Electric Power Systems by Agustín Flores, Eduardo Quiles, Emilio García, Francisco Morant, Antonio Correcher

Get full text

Finding Neural Biomarkers for Motor Learning and Rehabilitation Using an Explainable Graph Neural Network by J. Han, A. Embs, F. Nardi, S. Haar, A. A. Faisal

Subjects: Get full text

Dynamic Spatial–Temporal Graph Neural Network for Cooling Capacity Prediction in HVDC Systems by Hao Sun, Shaosen Li, Jianxiang Huang, Hao Li, Guanxin Jing, Ye Tao, Xincui Tian

Subjects: Get full text

A Deep Neural Network-Based Fault Detection Scheme for Aircraft IMU Sensors by Yiming Zhang, Hang Zhao, Jinyi Ma, Yunmei Zhao, Yiqun Dong, Jianliang Ai

“…This scheme adopts a deep neural network with a CNN-LSTM-fusion architecture (CNN: convolution neural network; LSTM: long short-term memory). …”
Get full text

Discriminative training of spiking neural networks organised in columns for stream‐based biometric authentication by Enrique Argones Rúa, Tim Vanhamme, Davy Preuveneers, Wouter Joosen

“…One of the challenges when using SNNs is the discriminative training of the network since it is not straightforward to apply the well‐known error backpropagation (EBP), massively used in traditional artificial neural networks (ANNs). A network structure based on neuron columns is proposed, resembling cortical columns in the human cortex, and a new derivation of error backpropagation for the spiking neural networks that integrate the lateral inhibition in these structures. …”
Get full text

Synchronization in Array of Coupled Neural Networks with Unbounded Distributed Delay and Limited Transmission Efficiency by Xinsong Yang, Mengzhe Zhou, Jinde Cao

“…This paper investigates global synchronization in an array of coupled neural networks with time-varying delays and unbounded distributed delays. …”
Get full text

Evaluating Item Content and Scale Characteristics Using a Pretrained Neural Network Model by Jeffrey Stanton, Angela Ramnarine-Rieks, Yisi Sang

Subjects: Get full text

ResNet15: Weather Recognition on Traffic Road with Deep Convolutional Neural Network by Jingming Xia, Dawei Xuan, Ling Tan, Luping Xing

“…With the rapid development of deep learning, deep convolutional neural networks (CNN) are used to recognize weather conditions on traffic road. …”
Get full text

Improved Quantile Convolutional and Recurrent Neural Networks for Electric Vehicle Battery Temperature Prediction by Andreas M. Billert, Runyao Yu, Stefan Erschen, Michael Frey, Frank Gauterin

Subjects: “…convolutional and recurrent neural network…”
Get full text

Password strength verification based on machine learning algorithms and LSTM recurrent neural networks by V. V. Belikov, I. A. Prokuronov

Subjects: Get full text

Detection of Fungal Infections in Gloriosa Superba Plant Using the Convolution Neural Network Model by Guillermo Napoleón Pelaez-Diaz, Rosa Vílchez-Vásquez, Antonio Huaman-Osorio, R. Mahaveerakannan, S. Pushpa, Nilesh Shelke, Sumitha Jagadibabu, Jenifer Mahilraj

“…We used a deep learning-based convolution neural network (CNN) classifier model to optimize the CNN algorithm parameter for better prediction. …”
Get full text

A graph neural network approach for hierarchical mapping of breast cancer protein communities by Xiao Zhang, Qian Liu

Subjects: Get full text

Option Volatility Investment Strategy: The Combination of Neural Network and Classical Volatility Prediction Model by Yuanyang Teng, Yicun Li, Xiaobo Wu

“…This work setup a bridge of previous financial studies and machine learning studies by proposing an algorithm integrating neural network and three traditional volatility models, called “Quantile based neural network and model integration combination algorithm.” …”
Get full text

Ranking of Search Requests in the Digital Information Retrieval System Based on Dynamic Neural Networks by Viera Bartosova, Svetlana Drobyazko, Sergii Bogachov, Olga Afanasieva, Maria Mikhailova

“…The algorithm of functioning of the neural network ranking unit based on Hopfield neural network is built. …”
Get full text

Multi-objective design of multi-material truss lattices utilizing graph neural networks by Ramón Frey, Michael R. Tucker, Mohamadreza Afrasiabi, Markus Bambach

“…In this work, we propose a novel approach that incorporates material properties as edge features within the graph representation of multi-material truss lattices, utilizing graph neural networks (GNNs) to develop a fast and efficient inverse design framework. …”
Get full text

Estimation of Maximum Daily Fresh Snow Accumulation Using an Artificial Neural Network Model by Gun Lee, Dongkyun Kim, Hyun-Han Kwon, Eunsoo Choi

“…For estimation of maximum daily fresh snow accumulation (MDFSA), a novel model based on an artificial neural network (ANN) was proposed. Daily precipitation, mean temperature, and minimum temperature were used as the input data for the ANN model. …”
Get full text

Rolling Force Prediction in Heavy Plate Rolling Based on Uniform Differential Neural Network by Fei Zhang, Yuntao Zhao, Jian Shao

“…When its original function is transferred with a transfer function, the uniform differential evolution algorithms can quickly solve complex optimization problems. Neural network structure and weights threshold are optimized by uniform differential evolution algorithm, and a uniform differential neural network is formed to improve rolling force prediction accuracy in process control system.…”
Get full text

Fall Detection Based on Continuous Wave Radar Sensor Using Binarized Neural Networks by Hyeongwon Cho, Soongyu Kang, Yunseong Sim, Seongjoo Lee, Yunho Jung

“…In this study, we propose a lightweight fall detection method using a continuous-wave (CW) radar sensor and a binarized neural network (BNN) to meet these requirements. We used a CW radar sensor, which is more affordable than other types of radar sensors, and employed a BNN with binarized features and parameters to reduce memory usage and make the system lighter. …”
Get full text

Visualization of multidimensional data taking into account the learning flow of the self organizing neural network by Gintautas Dzemyda, Olga Kurasova

“… In the paper we discuss the visualization of multidimensional vectors taking into account the learning flow of the self organizing neural network. A new algorithm realizing a combination of the self-organizing map (SOM) and Sammon's mapping has been proposed. …”
Get full text

Sensor fusion with high‐order moments constraints using projection‐based neural network by Yousef Alipouri, Reza Rafati Bonab, Lexuan Zhong

“…To do this, a projection‐based neural network‐based optimization method is used to calculate the optimal fusion weights that satisfy moment constraints. …”
Get full text