An Integrated Bearing Fault Diagnosis Method Based on Multibranch SKNet and Enhanced Inception-ResNet-v2 by Baoquan Hu, Jun Liu, Yue Xu, Tianlong Huo

“…To solve the above problems, this paper proposes an integrated deep neural network that combines an improved selective kernel network (SKNet) with an enhanced Inception-ResNet-v2, named SIR-CNN. …”
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Development of a Neuroevolution Machine Learning Potential of Al-Cu-Li Alloys by Fei Chen, Han Wang, Yanan Jiang, Lihua Zhan, Youliang Yang

“…To address this issue, we apply a neural network-based neuroevolutionary machine learning potential (NEP) and use evolutionary strategies to train it for large-scale molecular dynamics (MD) simulations. …”
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MONet: cancer driver gene identification algorithm based on integrated analysis of multi-omics data and network models by Yingzan Ren, Tiantian Zhang, Jian Liu, Fubin Ma, Jiaxin Chen, Ponian Li, Guodong Xiao, Chuanqi Sun, Yusen Zhang

“…Our method utilizes two graph neural network algorithms on protein-protein interaction (PPI) networks to extract feature vector representations for each gene. …”
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Analysis of Noise Pollution during Dussehra Festival in Bhubaneswar Smart City in India: A Study Using Machine Intelligence Models by Sourav Kumar Bhoi, Chittaranjan Mallick, Chitta Ranjan Mohanty, Ranjan Soumya Nayak

“…The supervised ML models taken in this work are Decision Tree (DT), Neural Network (NN), k-Nearest Neighbor (k-NN), Naïve Bayes (NB), Support Vector Machine (SVM), and Random Forest (RF). …”
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A New Approach to Estimate Concentration Levels with Filtered Neural Nets for Online Learning by Woodo Lee, Junhyoung Oh, Jaekwoun Shim

“…This research aims to estimate more subtle levels as specified states by using a minimum amount of body movement data. The deep neural network is used to continuously recognize the human concentration model, and the concentration levels can be predicted and estimated by the Kalman filter. …”
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Evaluation of the Risk of Recurrence in Patients with Local Advanced Rectal Tumours by Different Radiomic Analysis Approaches by Alaa Khadidos, Adil Khadidos, Olfat M. Mirza, Tawfiq Hasanin, Wegayehu Enbeyle, Abdulsattar Abdullah Hamad

“…In deep learning, we built a 16-layer convolutional neural network model, driven by a 2D MRI image database comprising both the native images and the bounding box corresponding to each image.…”
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Re-locative guided search optimized self-sparse attention enabled deep learning decoder for quantum error correction by Umesh Uttamrao Shinde, Ravikumar Bandaru

“…Therefore, this research proposes a Re-locative Guided Search optimized self-sparse attention-enabled convolutional Neural Network with Long Short-Term Memory (RlGS2-DCNTM) for performing effective error correction in quantum codes. …”
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Study on Water Quality Inversion Model of Dianchi Lake Based on Landsat 8 Data by Jiaju Cao, Xingping Wen, Dayou Luo, Yinlong Tan

“…The results show that the relative errors of permanganate index (COD) in neural network and multiple regression are 9.68% and 17.48%, respectively; 3.81% and 3.36% in dissolved oxygen (DO); 1.25% and 1.58% in hydrogen ion (pH); in ammonia nitrogen (NH3-N), it is 15.39% and 24.97%, respectively. …”
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Estimating Network Flowing over Edges by Recursive Network Embedding by Liqun Yu, Hongqi Wang, Haoran Mo

“…We propose to embed the nodes to a continuous vector space so that the embedding vector of each node can be reconstructed from its neighbors by a recursive neural network model, linear normalized long short-term memory. …”
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Study of Microstructure and Wear Resistance of AA5052/B4C Nanocomposites as a Function of Volume Fraction Reinforcement to Particle Size Ratio by ANN by D. Dinesh Kumar, A. Balamurugan, K. C. Suresh, R. Suresh Kumar, N. Jayanthi, T. Ramakrishnan, S. K. Hasane Ahammad, S. Mayakannan, S. Venkatesa Prabhu

“…This research examines a model function developed from an artificial neural network (ANN). AA5052/B4C composites bent using a powder metallurgy technique to hardness and ball-on-disc wear testing. …”
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Machine learning algorithms in air quality modeling by A. Masih

“…Furthermore a factorial analysis named multi-component analysis performed show that pollution estimation is generally performed by using ensemble learning and linear regression based approaches, whereas, forecasting tasks tend to implement neural networks and support vector machines based algorithms.…”
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Efficient recognition of Parkinson’s disease mice on stepping characters with CNN by Yunsong Luo, Yiqi Huang, Guangzhan Fang, Ningping Tan, Yezhong Tang

“…By processing footprint images collected in the absence of light—employing numerical area summation for noise reduction, adaptive enhancement algorithms based on pixel values, and a high-accuracy Convolutional Neural Network algorithm. And integrating motion data analysis, we achieved effective fusion of footprint images and behavioral data. …”
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Polarimetric image recovery method with domain-adversarial learning for underwater imaging by Fei Tian, Jiuming Xue, Zhedong Shi, Hongling Luo, Wanyuan Cai, Wei Tao

“…In this paper, we collect, to the best of our knowledge, the richest polarization color image dataset with different water types and present a specially designed neural network UPD-Net firstly employing the domain-adversarial learning strategy to recover the degraded color images. …”
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Wheat Futures Prices Prediction in China: A Hybrid Approach by Yunpeng Sun, Jin Guo, Shan Shan, Yousaf Ali Khan

“…This research investigates whether China wheat futures price can be predicted by employing artificial intelligence neural network. This would add to our knowledge whether wheat futures market is resourceful and would enable traders, sellers, and investors to improve cost-effective trading strategy. …”
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Detecting Invalid Associations between Fare Machines and Metro Stations Using Smart Card Data by Pengfei Zhang, Zhenliang Ma, Xiaoxiong Weng

“…The isolation forest coupled with a neural network (NN) takes these features as inputs to detect the wrongly associated fare machines and infer the correct association stations. …”
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Optimized sequential model for superior classification of plant disease by Yogesh Chimate, Sangram Patil, K. Prathapan, Jaydeep Patil, Jayendra Khot

“…Deep learning architectures, like convolutional neural network, can autonomously learn and extract complicated characteristics and patterns from huge datasets. …”
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A High-Efficiency Charge-Domain Compute-in-Memory 1F1C Macro Using 2-bit FeFET Cells for DNN Processing by Nellie Laleni, Franz Muller, Gonzalo Cunarro, Thomas Kampfe, Taekwang Jang

“…The macro achieves 111.6 TOPS/W, highlighting its energy efficiency, and demonstrates robust performance on the CIFAR-10 dataset, achieving 89% accuracy with a VGG-8 neural network. These findings underscore the potential of charge-domain, multilevel NVM cells in pushing the boundaries of artificial intelligence (AI) acceleration and energy-efficient computing.…”
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Displacement-Based Back-Analysis of the Model Parameters of the Nuozhadu High Earth-Rockfill Dam by Yongkang Wu, Huina Yuan, Bingyin Zhang, Zongliang Zhang, Yuzhen Yu

“…In this method, an artificial neural network is used as a substitute for time-consuming finite element analysis, and an evolutionary algorithm is applied for both network training and parameter optimization. …”
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An improved quantitative assessment method on hazardous interference of power lines to the signal cable in high‐speed railway by Chang Liu, Shiwu Yang, Yong Cui, Shaotong Chu, Qihui Xiong

“…Abstract High‐speed railway (HSR) presents the characteristics of a heavy load, large traction current, and ballastless track‐bed. As the 'neural network' of the signalling system, the line‐side signal cable may threaten both human safety and control information transmission for an HSR operation when interfered with by a strong traction current. …”
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Automatic MRI Image Classification Using Attention and Residual CNNs With Enhanced Image Denoising Filters by Suganya Athisayamani, A. Robert Singh, Faten Khalid Karim, Samih M. Mostafa

“…The enhanced image features are used for classification with three different CNN classification models: Convolutional Neural Network (CNN), CNN with attention module (CNN-AM) and CNN with a residual module (CNN-RM). …”
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