Machine learning-based prediction of soil organic matter via smartphone by Qingying Gao, Yi Chen, Hui Zhang, Jingjing Chen, Liang Wang

“…Random forest of classification (RFC), random forest of logical regression (RFLR), convolutional neural network (CNN) and MobileNet models are compared, which is better for SOM prediction. …”
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An Enhancement Deep Feature Extraction Method for Bearing Fault Diagnosis Based on Kernel Function and Autoencoder by Fengtao Wang, Bosen Dun, Xiaofei Liu, Yuhang Xue, Hongkun Li, Qingkai Han

“…Subsequently, a deep neural network is constructed with one KAE and multiple AEs to extract inherent features layer by layer. …”
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Research on Fault Diagnosis for Pumping Station Based on T-S Fuzzy Fault Tree and Bayesian Network by Zhuqing Bi, Chenming Li, Xujie Li, Hongmin Gao

“…Finally, the feasibility of the method is verified through a fault diagnosis model of the rotor in the pumping unit, the accuracy of the method is verified by comparing with the methods based on traditional Bayesian network and BP neural network, respectively, when the historical data is sufficient, and the results are more superior to the above two when the historical data is insufficient.…”
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Compound Autoregressive Network for Prediction of Multivariate Time Series by Yuting Bai, Xuebo Jin, Xiaoyi Wang, Tingli Su, Jianlei Kong, Yutian Lu

“…Firstly, a compound neural network framework was designed with the primary and auxiliary networks. …”
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The Fault Diagnosis of Rolling Bearing Based on Improved Deep Forest by Xiwen Qin, Dingxin Xu, Xiaogang Dong, Xueteng Cui, Siqi Zhang

“…At present, the technology of intelligent identification of bearing mostly relies on deep neural network, which has high requirements for computer equipment and great effort in hyperparameter tuning. …”
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A hybrid model for prediction of software effort based on team size by Prerana Rai, Dinesh Kumar Verma, Shishir Kumar

“…These techniques are mostly based on statistical methods (viz. simple linear regression (SLR), multi linear regression, support vector machine, cascade correlation neural network (CCNN) etc.) and some probability‐based models. …”
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Small fishing boat classification and recognition method based on GASF temporal graph coding and EMPViT model by Jiaqi Deng, Xin Liu, Gang Du, Xu Yang, Liangzhong Jiang, Chenglong Sun

“…These experiments demonstrate that the EMPViT model surpasses traditional neural network models such as CNN and ViT in both accuracy and performance, achieving a peak accuracy of 99.98%.…”
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Dynamics Model Abstraction Scheme Using Radial Basis Functions by Silvia Tolu, Mauricio Vanegas, Rodrigo Agís, Richard Carrillo, Antonio Cañas

“…We address active sensing strategies to acquire object dynamical models with a radial basis function neural network (RBF). Experiments are done using a real robot’s arm, and trajectory data are gathered during various trials manipulating different objects. …”
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Fault Diagnosis of Gearbox in Multiple Conditions Based on Fine-Grained Classification CNN Algorithm by Pengcheng Jiang, Hua Cong, Jing Wang, Dongsheng Zhang

“…The use of the convolutional neural network for fault diagnosis has been a common method of research in recent years. …”
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Comparison of Fully Convolutional Networks and U-Net for Optic Disc and Optic Cup Segmentation by Jin Zixiao

“…This paper aims to compare two well-known convolutional neural network (CNN) structures, namely Fully Convolutional Networks (FCNs) and U-Net for the segmentation of the optic disc (OD) and optic cup (OC) from retinal fundus images which play an important role in glaucoma diagnosis. …”
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Transcranial Alternating Current and Random Noise Stimulation: Possible Mechanisms by Andrea Antal, Christoph S. Herrmann

“…Such findings are further supported by neural network simulations and knowledge from physics on entraining physical oscillators in the human brain. …”
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Gradient Enhancement Techniques and Motion Consistency Constraints for Moving Object Segmentation in 3D LiDAR Point Clouds by Fangzhou Tang, Bocheng Zhu, Junren Sun

“…In this paper, we introduce a novel deep neural network designed to enhance the performance of 3D LiDAR point cloud moving object segmentation (MOS) through the integration of image gradient information and the principle of motion consistency. …”
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Support Vector Regression Based on Grid-Search Method for Short-Term Wind Power Forecasting by Hong Zhang, Lixing Chen, Yong Qu, Guo Zhao, Zhenwei Guo

“…In order to investigate the performance of proposed strategy, forecasting results comparison between two different forecasting models, multiscale SVR and multilayer perceptron neural network applied for power forecasts, are presented. …”
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A Semi-supervised Deep Learning Method for Cervical Cell Classification by Siqi Zhao, Yongjun He, Jian Qin, Zixuan Wang

“…Cervical cell classification is a key technology in the intelligent cervical cancer diagnosis system. Training a deep neural network-based classification model requires a large amount of data. …”
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Design and Realization of the Intelligent Design System for Tunnel Blasting in Mine Based on Database by Zhengyu Wu, Dayou Luo, Guan Chen

“…Based on the T-S fuzzy neural network model, the intelligent search rules of excavation blasting data are also constructed in the new system. …”
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Segmentation Algorithm of Magnetic Resonance Imaging Glioma under Fully Convolutional Densely Connected Convolutional Networks by Jie Dong, Yueying Zhang, Yun Meng, Tingxiao Yang, Wei Ma, Huixin Wu

“…This work focused on the application value of magnetic resonance imaging (MRI) image segmentation algorithm based on fully convolutional DenseNet neural network (FCDNN) in glioma diagnosis. In this work, based on the fully convolutional DenseNet algorithm, a new MRI image automatic semantic segmentation method cerebral gliomas semantic segmentation network (CGSSNet) was established and was applied to glioma MRI image segmentation by using the BraTS public dataset as research data. …”
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Perception Analysis and Early Warning of Home-Based Care Health Information Based on the Internet of Things by Yi Mao, Lei Zhang, Xin Wu

“…In order to improve the accuracy of prediction, the DS evidence theory is used to optimize the traditional BP neural network (BPNN) algorithm and conduct experimental tests. …”
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A Hybrid Process Monitoring and Fault Diagnosis Approach for Chemical Plants by Lijie Guo, Jianxin Kang

“…Based on hazard and operability (HAZOP) analysis, kernel principal component analysis (KPCA), wavelet neural network (WNN), and fault tree analysis (FTA), a hybrid process monitoring and fault diagnosis approach is proposed in this study. …”
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Deep-Learning-Based Bughole Detection for Concrete Surface Image by Gang Yao, Fujia Wei, Yang Yang, Yujia Sun

“…A deep convolutional neural network for detecting bugholes on concrete surfaces was developed, by adding the inception modules into the traditional convolution network structure to solve the problem of the relatively small size of input image (28 × 28 pixels) and the limited number of labeled examples in training set (less than 10 K). …”
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Locality preserving binary face representations using auto‐encoders by Mohamed Amine Hmani, Dijana Petrovska‐Delacrétaz, Bernadette Dorizzi

“…A novel approach to binarising biometric data using Deep Neural Networks applied to facial biometric data is introduced. …”
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