Analysis and Dynamic Prediction of Bus Dwell Time Under Rainfall Conditions by Baoyun SUN, Yaping YANG, Lei DONG, Honglin LU, Zimin WANG

“…Support vector machine, k-nearest neighbour and backpropagation (BP) prediction models were established, and the BP neural network model, having the best prediction effect, was optimised using a genetic algorithm (GA). …”
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Vision transformers for automated detection of diabetic peripheral neuropathy in corneal confocal microscopy images by Chaima Ben Rabah, Ioannis N. Petropoulos, Rayaz A. Malik, Ahmed Serag

“…The ViT model's performance was also compared to ResNet50, a convolutional neural network (CNN) previously applied for DPN detection using CCM images. …”
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Deep learning-enhanced defects detection for printed circuit boards by Van-Truong Nguyen, Xuan-Thuc Kieu, Duc-Tuan Chu, Xiem HoangVan, Phan Xuan Tan, Tuyen Ngoc Le

“…., a type of convolutional neural network (CNN)) model. The proposed algorithm is tested in three different lighting conditions: low light, normal light, and high light conditions. …”
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Reliability-Based Fatigue Life Prediction for Complex Structure with Time-Varying Surrogate Modeling by Lu-Kai Song, Guang-Chen Bai, Cheng-Wei Fei, Jie Wen

“…To improve the computational efficiency and accuracy of reliability-based fatigue life prediction for complex structure, a time-varying particle swarm optimization- (PSO-) based general regression neural network (GRNN) surrogate model (called as TV/PSO-GRNN) is developed. …”
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Learning model combined with data clustering and dimensionality reduction for short-term electricity load forecasting by Hyun-Jung Bae, Jong-Seong Park, Ji-hyeok Choi, Hyuk-Yoon Kwon

“…To verify the effectiveness of the proposed model, we extensively apply it to neural network-based models. We compare and analyze the performance of the proposed model with the comparisons using actual electricity usage data for 4710 households. …”
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Wind Power Assessment Based on a WRF Wind Simulation with Developed Power Curve Modeling Methods by Zhenhai Guo, Xia Xiao

“…These approaches are improvements on the power curve modeling that is originally fitted by the single layer feed-forward neural network (SLFN) in this paper; in addition, a data quality check and outlier detection technique and the directional curve modeling method are adopted to effectively enhance the original model performance. …”
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Multi-omic spatial effects on high-resolution AI-derived retinal thickness by V. E. Jackson, Y. Wu, R. Bonelli, J. P. Owen, L. W. Scott, S. Farashi, Y. Kihara, M. L. Gantner, C. Egan, K. M. Williams, B. R. E. Ansell, A. Tufail, A. Y. Lee, M. Bahlo

“…We processed the UK Biobank OCT images using a convolutional neural network to produce fine-scale retinal thickness measurements across > 29,000 points in the macula, the part of the retina responsible for human central vision. …”
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Ultrasonic-assisted extraction of luteolin from peanut shells using ionic liquid and its molecular mechanism by Liwei Niu, Siwen Zhang, Xiaoyu Si, Yuhan Fang, Shuang Wang, Lulu Li, Zunlai Sheng

“…Further optimization of the extraction conditions was performed using response surface methodology and neural network analysis, resulting in a significantly enhanced luteolin yield of 3.71 ± 0.06 mg/g. …”
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Balanced coarse-to-fine federated learning for noisy heterogeneous clients by Longfei Han, Ying Zhai, Yanan Jia, Qiang Cai, Haisheng Li, Xiankai Huang

“…However, heterogeneous clients have different deep neural network structures, and these models have different sensitivity to various noise types, the fixed noise-detection based methods may not be effective for each client. …”
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Integrating machine learning with advanced processing and characterization for polycrystalline materials: a methodology review and application to iron-based superconductors by Akiyasu Yamamoto, Akinori Yamanaka, Kazumasa Iida, Yusuke Shimada, Satoshi Hata

“…Specifically, we discuss a mechanochemical process involving high-energy milling, in situ observation of microstructural formation using 3D scanning transmission electron microscopy, phase-field modeling coupled with Bayesian data assimilation, nano-orientation analysis via scanning precession electron diffraction, semantic segmentation using neural network models, and the Bayesian-optimization-based process design using BOXVIA software. …”
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Nerve‐Inspired Optical Waveguide Stretchable Sensor Fusing Wireless Transmission and AI Enabling Smart Tele‐Healthcare by Tianliang Li, Qian'ao Wang, Zichun Cao, Jianglin Zhu, Nian Wang, Run Li, Wei Meng, Quan Liu, Shifan Yu, Xinqin Liao, Aiguo Song, Yuegang Tan, Zude Zhou

“…A speech recognition and human‐machine interaction system, based on sensor signal acquisition, is constructed, and the convolutional neural network algorithm is integrated for disease assessment. …”
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A Software Tool for Optimal Sizing of PV Systems in Malaysia by Tamer Khatib, Azah Mohamed, K. Sopian

“…The software has the capabilities of predicting the metrological variables such as solar energy, ambient temperature and wind speed using artificial neural network (ANN), optimizes the PV module/ array tilt angle, optimizes the inverter size and calculate optimal capacities of PV array, battery, wind turbine and diesel generator in hybrid PV systems. …”
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Exploring the Relationships between Subjective Evaluations and Objective Metrics of Vehicle Dynamic Performance by Jianyou Zhao, Jing Liu, Liping Yang, Ping He

“…Finally, an overall subjective evaluation model related to the three objective metrics was established based on the Probabilistic Neural Network (PNN). The analysis results demonstrated that the correlation coefficients of the three groups of data were greater than 0.5 and that each subjective evaluation was significantly correlated with its corresponding objective metric. …”
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Action Selection and Operant Conditioning: A Neurorobotic Implementation by André Cyr, Frédéric Thériault

“…We propose simulating an AS process by using a small spiking neural network (SNN) as the lower neural organisms, in order to control virtual and physical robots. …”
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Detecting Subtle Cyberattacks on Adaptive Cruise Control Vehicles: A Machine Learning Approach by Tianyi Li, Mingfeng Shang, Shian Wang, Raphael Stern

“…The proposed approach is observed to outperform contemporary neural network models in detecting irregular driving patterns of ACC vehicles.…”
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Distance Measurement and Error Compensation of High-Speed Coaxial Rotor Blades Based on Coded Ultrasonic Ranging by Yaohuan Lu, Shan Zhang, Wenchuan Hu, Zhen Qiu, Zurong Qiu, Yongqiang Qiu

“…The measurement error characteristics under different trigger phases and different rotational speeds are studied, and the error model is fitted by the back-propagation neural network method. After compensation, the vertical distance measurement errors are within ±2 mm in the range of 100–1000 mm under the condition that the rotational speed of the blade is up to 1020 RPM. …”
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Active Vibration Control of the Sting Used in Wind Tunnel: Comparison of Three Control Algorithms by Xing Shen, Yuke Dai, Mingxuan Chen, Lei Zhang, Li Yu

“…This paper details three algorithms, respectively, Classical PD Algorithm, Artificial Neural Network PID (NNPID), and Linear Quadratic Regulator (LQR) Optimal Control Algorithm, which can realize active vibration control of sting used in wind tunnel. …”
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YOLO-UNet Architecture for Detecting and Segmenting the Localized MRI Brain Tumor Image by Nur Iriawan, Anindya A. Pravitasari, Ulfa S. Nuraini, Nur I. Nirmalasari, Taufik Azmi, Muhammad Nasrudin, Adam F. Fandisyah, Kartika Fithriasari, Santi W. Purnami, null Irhamah, Widiana Ferriastuti

“…This paper employed deep learning to detect and segment brain tumor MRI images by combining the convolutional neural network (CNN) and fully convolutional network (FCN) methodology in serial. …”
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Effect of Caesalpinia decapetala on the Dry Sliding Wear Behavior of Epoxy Composites by Hailemariam Biratu, Mengistu Gelaw, Kiran Shahapurkar, Venkatesh Chenrayan, Manzoore Elahi M. Soudagar, Vineet Tirth, Ali Algahtani, Tawfiq Al-Mughanam

“…The grey relational analysis- (GRA-) coupled artificial neural network (ANN) hybrid technique was employed for the prediction and validation. …”
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DTI-MHAPR: optimized drug-target interaction prediction via PCA-enhanced features and heterogeneous graph attention networks by Guang Yang, Yinbo Liu, Sijian Wen, Wenxi Chen, Xiaolei Zhu, Yongmei Wang

“…Our approach initiates with the construction of a heterogeneous graph from various similarity metrics, which is then encoded via a graph neural network. We concatenate and integrate the resultant representation vectors to merge multi-level information. …”
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