Spatiotemporal Traffic Flow Prediction with KNN and LSTM by Xianglong Luo, Danyang Li, Yu Yang, Shengrui Zhang

“…Experimental results indicate that the proposed model can achieve a better performance compared with well-known prediction models including autoregressive integrated moving average (ARIMA), support vector regression (SVR), wavelet neural network (WNN), deep belief networks combined with support vector regression (DBN-SVR), and LSTM models, and the proposed model can achieve on average 12.59% accuracy improvement.…”
Get full text

Prediction of Passive Torque on Human Shoulder Joint Based on BPANN by Shuyang Li, Paolo Dario, Zhibin Song

“…Accordingly, a prediction method of shoulder joint passive torque based on a Backpropagation neural network (BPANN) was proposed in the present study to expand the passive torque distribution of the shoulder joint of a patient with less measurement data. …”
Get full text

Integrating electrocardiogram and fundus images for early detection of cardiovascular diseases by K. A. Muthukumar, Dhruva Nandi, Priya Ranjan, Krithika Ramachandran, Shiny PJ, Anirban Ghosh, Ashwini M, Aiswaryah Radhakrishnan, V. E. Dhandapani, Rajiv Janardhanan

“…These EMD values were then concatenated, forming a comprehensive feature set that was fed into a Neural Network classifier. This approach, leveraging the FFT’s spectral insights and EMD’s capability to capture nuanced data differences, offers a robust representation for CVD classification. …”
Get full text

Development and validation of a deep learning-enhanced prediction model for the likelihood of pulmonary embolism by Yu Tian, Yu Tian, Jingjie Liu, Shan Wu, Yucong Zheng, Rongye Han, Qianhui Bao, Lei Li, Lei Li, Tao Yang

“…Our prediction model uses a convolutional neural network (CNN), enhanced with three custom-designed modules for better performance. …”
Get full text

FlowMFD: Characterisation and classification of tor traffic using MFD chromatographic features and spatial–temporal modelling by Liukun He, Liangmin Wang, Keyang Cheng, Yifan Xu

“…In addition, FlowMFD utilises a cascaded model with a two‐dimensional convolutional neural network (2D‐CNN) and a bidirectional gated recurrent unit to capture spatial‐temporal dependencies between MFDCF. …”
Get full text

High-Dose Neural Stem/Progenitor Cell Transplantation Increases Engraftment and Neuronal Distribution and Promotes Functional Recovery in Rats after Acutely Severe Spinal Cord Inju... by Taoyang Yuan, Qian Liu, Jie Kang, Hua Gao, Songbai Gui

“…At 8 weeks postgrafting, subjects that received the higher cell dose exhibited abundant nerve regeneration, extensive neuronal distribution, increased proportions of neurons and oligodendrocytes, and nascent functional neural network formation in the lesion area. Notably, a significant functional recovery was also observed. …”
Get full text

A Machine Learning-Based Model for Predicting Atmospheric Corrosion Rate of Carbon Steel by Ngoc-Long Tran, Trong-Ha Nguyen, Van-Tien Phan, Duy-Duan Nguyen

“…The purpose of this study is to develop a practical artificial neural network (ANN) model for predicting the atmospheric corrosion rate of carbon steel. …”
Get full text

A Convection Nowcasting Method Based on Machine Learning by Aifang Su, Han Li, Liman Cui, Yungang Chen

“…The test analysis demonstrated that the algorithm combined the image feature extraction ability of the convolutional neural network (CNN) and the sequential learning ability of the long short-term memory network (LSTM) model to establish an end-to-end deep learning network, which could deeply extract high-order features of radar echoes such as structural texture, spatial correlation, and temporal evolution compared with the traditional algorithm. …”
Get full text

Improving Proton Exchange Membrane Fuel Cell Operational Reliability Through Cabin-Based Fuzzy Control in Costal Standalone Observation Systems in Antarctica by Jin Wang, Yinke Dou, Guangyu Zuo, Bo Fan, Yuru Xing

“…A temperature-coordinated control system leveraging a BP neural network, fuzzy logic rules, and the fuzzy-based active disturbance rejection control (Fuzzy-ADRC) strategy are proposed to ensure that the temperature of the PEMFC and cabin can reach the optimal state rapidly and that the output voltage is stable. …”
Get full text

A Semi-Supervised Attention Model for Identifying Authentic Sneakers by Yang Yang, Nengjun Zhu, Yifeng Wu, Jian Cao, Dechuan Zhan, Hui Xiong

“…The model draws on the weighted average of the output feature representations, where the weights are determined by an additional shallow neural network. This allows the SSA model to focus on the most important images of a sneaker for use in identification. …”
Get full text

Neural ODEs for holographic transport models without translation symmetry by Zhuo-Fan Gu, Yu-Kun Yan, Shao-Feng Wu

“…We convert the flow equation to a Neural Ordinary Differential Equation (Neural ODE), which is a neural network with continuous depth and produces output through a black-box ODE solver. …”
Get full text

Prediction of Mine Dust Concentration Based on Grey Markov Model by Zhou Xu, Guo Liwen, Zhang Jiuling, Qin Sijia, Zhu Yi

“…The model was applied to the prediction of mine dust concentration and compared with the prediction results of the BP neural network model, grey prediction model, and ARIMA (1, 2, 1) model. …”
Get full text

A guidance to intelligent metamaterials and metamaterials intelligence by Chao Qian, Ido Kaminer, Hongsheng Chen

“…For metamaterials intelligence, we particularly unfold three canonical categories, i.e., wave-based neural network, mathematical operation, and logic operation, all of which directly execute computation, detection, and inference task in physical space. …”
Get full text

A study comparing energy consumption and environmental emissions in ostrich meat and egg production by Behrooz Behboodi, Mohammad Gholami Parashkoohi, Davood Mohammad Zamani, Saeed Firouzi

“…This study delves into the impact of egg and meat production on human health, revealing a slight difference of 0.23 disability adjusted life years (DALY), hinting that egg production could potentially have marginally more negative health effects than meat production. Artificial neural network (ANN) analysis indicates that optimizing machinery, diesel fuel, and energy usage can enhance the productivity of meat production. …”
Get full text

Predicting the urban water demand by equipping intelligent-based methods with discrete wavelet transform function by Mohammad Reza Alikhani, Ramtin Moeini

“…For this purpose, in this research, artificial intelligence and data mining methods, including genetic programming (GP), gene expression programming (GEP), artificial neural network (ANN), and discrete wavelet transform function, are used to predict the daily drinking water consumption values of WDN. …”
Get full text

Evaluating CNN Architectures and Hyperparameter Tuning for Enhanced Lung Cancer Detection Using Transfer Learning by Mohd Munazzer Ansari, Shailendra Kumar, Umair Tariq, Md Belal Bin Heyat, Faijan Akhtar, Mohd Ammar Bin Hayat, Eram Sayeed, Saba Parveen, Dustin Pomary

“…This study evaluates the performance of six convolutional neural network (CNN) architectures, ResNet-50, VGG-16, ResNet-101, VGG-19, DenseNet-201, and EfficientNet-B4, using the LIDC-IDRI dataset. …”
Get full text

Sustainable Selection of Machine Learning Algorithm for Gender-Bias Attenuated Prediction by Raik Orbay, Evelina Wikner

“…An investigation into the environmental burden of seven different types of ML algorithms was conducted and the popular neural network algorithm had the highest environmental burden.…”
Get full text

A Calibration Approach for Elasticity Estimation with Medical Tools by Grube S., Neidhardt M., Hermann A.-K., Sprenger J., Abdolazizi K., Latus S., Cyron C. J., Schlaefer A.

“…Second, we propose to use a more complex material model, e.g., a neural network, that can be trained with the determined elasticities. …”
Get full text

A novel deep learning-based 1D-CNN-optimized GRU approach for heart disease prediction by Jini Mol G., Ajith Bosco Raj T.

“…To identify the irregularities in the cardiac data pattern, a gated recurrent unit (GRU) classifier and a one-dimensional convolutional neural network (1D-CNN) are introduced. A typical genetic algorithm (GA) is used to optimize the suggested GRU network in order to pass over the local minima. …”
Get full text

Emergency Medical Resources Allocation of Periphery for Epidemic Areas: Based on Infectious Diseases Spatial-Temporal Transmission Path by Xuan Zhao, Benhong Peng, Chaoyu Zheng, Anxia Wan

“…Finally, a graph convolutional neural network (GCN) is conducted to select the supply-side areas for peripheral-epicenter supplies distribution based on information achieved from the bipartite graph. …”
Get full text