Research on the Influence of Composite Modification Design on Tooth Surface Wear of Transmission Gears by Bai Xiaoning, Li Yonghua, Wang Denglong, Zhang Dongxu

“…Moreover, the sparrow search algorithm (SSA) improved by the Sine chaotic mapping is used to optimize the back propagation (BP) neural network, and the accuracy of Sine-SSA-BP is verified by comparing it with the traditional BP, so as to characterize the implicit relationship between the modification parameters and the gear wear. …”
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Research on Performance Degradation Prediction Method of Electric Vehicle Reducers Based on MDS-GA-SVR by He Yinda, Li Weilin, Chen Feng, He Qingchuan, Pan Jun, Ma Xingjian

“…The experiment results show that the prediction accuracy by using the proposed method is much higher than the results using PSO-SVR, GS-SVR and back propagation (BP) neural network. The RMSE values are reduced by 50.63%, 75.16% and 84.73%, and the <italic>R</italic>² values are increased respectively by 3.93%, 6.51% and 9.51%, which proves the superiority of the proposed method.…”
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Surface Feature Prediction Modeling and Parameter Optimization for Turning TC17 Titanium Alloy by Zhibo Deng, Zhe Wang, Xuehong Shen

“…Data obtained from the Box-Behnken design experiments were used to develop the response surface methodology (RSM) and artificial neural network (ANN) models. Through analysis of variance (ANOVA), the relative effects of each cutting parameter on the responses have been determined. …”
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Learning from Large-Scale Wearable Device Data for Predicting the Epidemic Trend of COVID-19 by Guokang Zhu, Jia Li, Zi Meng, Yi Yu, Yanan Li, Xiao Tang, Yuling Dong, Guangxin Sun, Rui Zhou, Hui Wang, Kongqiao Wang, Wang Huang

“…In addition to a physiological anomaly detection algorithm defined based on data from wearable devices, an online neural network prediction modelling methodology combining both detected physiological anomaly rate and historical COVID-19 infection rate is explored. …”
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Distributionally Robust Policy and Lyapunov-Certificate Learning by Kehan Long, Jorge Cortes, Nikolay Atanasov

“…We integrate this condition into a loss function for training a neural network-based controller and show that, for the resulting closed-loop system, the global asymptotic stability of its equilibrium can be certified with high confidence, even with Out-of-Distribution (OoD) model uncertainties. …”
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Rules-Based Energy Management System for an EV Charging Station Nanogrid: A Stochastic Analysis by Gabriel Henrique Danielsson, Leonardo Nogueira Fontoura da Silva, Joelson Lopes da Paixão, Alzenira da Rosa Abaide, Nelson Knak Neto

“…The methodology includes forecasting models based on an Artificial Neural Network for photovoltaic generation, a parametric estimation for wind generation, and a Monte Carlo simulation to predict the energy consumption of electric vehicles. …”
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Improving Accuracy and Calibration of Deep Image Classifiers With Agreement-Driven Dynamic Ensemble by Pedro Conde, Rui L. Lopes, Cristiano Premebida

“…The merits of the proposed algorithm are shown through a series of representative experiments, leveraging two different neural network architectures and three different datasets against multiple state-of-the-art baselines.…”
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MICE city ecosystems: building collaboration through information systems – a case study from Thailand by Pattaraporn Warintarawej, Nattaporn Thongsri, Jariya Seksan, Witchuta Marchoo

“…Objectives include developing an information system based on design thinking, investigating factors affecting the intention to use the system by examining MICE background knowledge, benefits, and Technology Acceptance Model (TAM) factors using correlation analysis and neural network techniques, and studying stakeholder satisfaction with the system. …”
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A machine learning technique for optimizing load demand prediction within air conditioning systems utilizing GRU/IASO model by Meng He, Hui Wang, Myo Thwin

“…GRU is a recurrent neural network that has the ability to comprehend intricate temporal relationships within the input data. …”
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Edge-AI Enabled Wearable Device for Non-Invasive Type 1 Diabetes Detection Using ECG Signals by Maria Gragnaniello, Vincenzo Romano Marrazzo, Alessandro Borghese, Luca Maresca, Giovanni Breglio, Michele Riccio

“…A spectrogram-based preprocessing method is combined with a 1-Dimensional Convolutional Neural Network (1D-CNN) to analyze the ECG signals directly on the device. …”
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Optimization Modeling and Empirical Research on Gasoline Octane Loss Based on Data Analysis by Ji Guo, Yujia Lou, Wanyi Wang, Xianhua Wu

“…Firstly, the data are screened and the high-dimensional data are reduced to construct the neural network prediction model optimized by genetic algorithm. …”
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Load Transfer Efficiency Analysis and Void Evaluation of Composite Pavement Cement Concrete Slab by Hao Li, Naren Fang, Xuancang Wang, Yang Fang, Xianghang Li, Chao Li, Siyin Ding

“…Taking into consideration the spring stiffness, void size, and soil base elastic modulus, the void evalua\tion method of composite pavement cement concrete slab is established by using back propagation neural network algorithm. The results show that the void evaluation method can provide the void determination map with two parameters. …”
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Multisegment Mapping Network for Massive MIMO Detection by Yongzhi Yu, Jianming Wang, Limin Guo

“…This paper proposes a deep neural network for massive MIMO detection, named Multisegment Mapping Network (MsNet). …”
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A new approach for bin packing problem using knowledge reuse and improved heuristic by Jie Fang, Xubing Chen, Yunqing Rao, Yili Peng, kuan Yan

“…In this study, the similarity measurement method based on the twin neural network model is used to evaluate the similarity of pieces in the source task and the target task. …”
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The Study on Modeling of Global Plasmaspheric Hiss Amplitude Based on Deep Learning Algorithm by Rongxin Tang, Zhenghan Wang, Haimeng Li, Zhou Chen, Zhihai Ouyang, Xiaohua Deng

“…Then the geomagnetic indices in corresponding time series are considered as input of deep neural network model, and the samples of plasmaspheric hiss waves observed from Van Allen Probe A are utilized for training and validation. …”
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Sports Augmented Cognitive Benefits: An fMRI Study of Executive Function with Go/NoGo Task by Qingguo Ding, Lina Huang, Jie Chen, Farzaneh Dehghani, Juan Du, Yingli Li, Qin Li, Hongqiang Zhang, Zhen Qian, Wenbin Shen, Xiaowei Yin, Pei Liang

“…This study explores the effect of dynamic neural network processing with the classic Go/NoGo task with regular exercisers. …”
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A Generalized Zero-Shot Deep Learning Classifier for Emotion Recognition Using Facial Expression Images by Vishal Singh Bhati, Namita Tiwari, Meenu Chawla

“…This study proposes a generalized deep learning classifier, Generalized Zero-Shot Convolutional Neural Network (GZS-ConvNet), to solve the problem of generalization. …”
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Fault Diagnosis of Train Axle Box Bearing Based on Multifeature Parameters by Xiaofeng Li, Limin Jia, Xin Yang

“…In the third part, a fault classifier based on BP neural network is designed for automatic fault pattern recognition. …”
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Prediction of Residual Gas Content during Coal Roadway Tunneling Based on Drilling Cuttings Indices and BA-ELM Algorithm by Zhenhua Yang, Hongwei Zhang, Sheng Li, Chaojun Fan

“…Then, the correlation between drilling cuttings indices and residual gas content was established, as well as the neural network prediction model based on BA-ELM. Finally, the prediction result of the proposed method was compared with that of back-propagation (BP), support vector machine (SVM), and extreme learning machine (ELM) to verify the accuracy. …”
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Compressive Strength Evaluation of Fiber-Reinforced High-Strength Self-Compacting Concrete with Artificial Intelligence by Tu T. Nguyen, Hoa Pham Duy, Tung Pham Thanh, Hoang Hiep Vu

“…It is shown that the performances of the artificial neural network (ANN) were better than that of the adaptive neurofuzzy inference system (ANFIS) model. …”
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