Calibration of miniature air quality detector monitoring data with PCA–RVM–NAR combination model by Bing Liu, Yirui Zhang

“…Finally, the nonlinear autoregressive neural network is used to correct the error and finally complete the establishment of the PCA–RVM–NAR model. …”
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Electricity Theft Detection in Power Grids with Deep Learning and Random Forests by Shuan Li, Yinghua Han, Xu Yao, Song Yingchen, Jinkuan Wang, Qiang Zhao

“…In order to help utility companies solve the problems of inefficient electricity inspection and irregular power consumption, a novel hybrid convolutional neural network-random forest (CNN-RF) model for automatic electricity theft detection is presented in this paper. …”
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Fault Diagnosis for Rolling Bearing under Variable Conditions Based on Image Recognition by Bo Zhou, Yujie Cheng

“…Third, due to the redundancy of the high-dimensional feature, kernel principal component analysis is utilized to reduce the feature dimensionality. Finally, a neural network classifier trained by probabilistic neural network is used to perform fault diagnosis. …”
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An Effective Self-Attention-Based Hybrid Model for Short-Term Traffic Flow Prediction by Zhihong Li, Xiaoyu Wang, Kairan Yang

“…The proposed model includes an encoder-decoder neural network module and a self-attention mechanism module. …”
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Distribution and functional significance of KLF15 in mouse cerebellum by Dan Li, Shuijing Cao, Yanrong Chen, Yueyan Liu, Kugeng Huo, Zhuangqi Shi, Shuxin Han, Liecheng Wang

“…Considering the complexity and importance of neural network development, in this study, we investigated the potent regulatory role of KLF15 in neural network development. …”
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Intelligent Modeling; Single (Multi-layer perceptron) and Hybrid (Neuro-Fuzzy Network) Method in Forest Degradation (Case Study: Sari County) by somayeh mehrabadi

“…In this study, forest degradation was modeled by employing the single-perceptron neural network and hybrid neuro-fuzzy method. For this purpose, the images from Landsat-5 TM sensor in 1999 and Landsat 8 OLI sensor in 2017 were utilized. …”
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A Time-Aware CNN-Based Personalized Recommender System by Dan Yang, Jing Zhang, Sifeng Wang, XueDong Zhang

“…With the in-depth study and application of deep learning algorithms, deep neural network is gradually used in recommender systems. …”
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Singularity-Free Neural Control for the Exponential Trajectory Tracking in Multiple-Input Uncertain Systems with Unknown Deadzone Nonlinearities by J. Humberto Pérez-Cruz, José de Jesús Rubio, Rodrigo Encinas, Ricardo Balcazar

“…The unknown dynamics is identified by means of a continuous time recurrent neural network in which the control singularity is conveniently avoided by guaranteeing the invertibility of the coupling matrix. …”
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A novel and highly efficient botnet detection algorithm based on network traffic analysis of smart systems by Li Duan, Jingxian Zhou, You Wu, Wenyao Xu

“…Then, the autoencoder neural network for feature selection is used to improve the efficiency of model construction. …”
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Position Verification in Connected Vehicles for Cyber Resilience Using Geofencing and Fuzzy Logic by Maria Drolence Mwanje, Omprakash Kaiwartya, Abdallah Naser

“…An experimental analysis of a dataset of simulated driving scenarios in MATLAB demonstrates that the feedforward neural network records the highest direction classification performance at 99.8% in conjunction with the centroid defuzzification method. …”
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Graph Convolutional Network with Neural Collaborative Filtering for Predicting miRNA-Disease Association by Jihwan Ha

“…<b>Methods:</b> Here, we discuss a novel machine-learning model that effectively predicts disease-related miRNAs using a graph convolutional neural network with neural collaborative filtering (GCNCF). …”
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Modeling Evapotranspiration Response to Climatic Forcings Using Data-Driven Techniques in Grassland Ecosystems by Xianming Dou, Yongguo Yang

“…These models were compared with the extensively utilized data-driven models, including artificial neural network, generalized regression neural network, and support vector machine (SVM). …”
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Cavitation Detection in Centrifugal Pump Based on Interior Flow-Borne Noise Using WPD-PCA-RBF by Liang Dong, Kan Wu, Jian-cheng Zhu, Cui Dai, Li-xin Zhang, Jin-nan Guo

“…In this work, to improve the accuracy and efficiency of identification, an approach combining wavelet packet decomposition (WPD) with principal component analysis (PCA) and radial basic function (RBF) neural network is introduced to detect the cavitation status for centrifugal pumps. …”
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Bone Mineral Density Prediction from CT Image: A Novel Approach using ANN by S. L. Resmi, V. Hashim, Jesna Mohammed, P. N. Dileep

“…In this approach, the BMD is predicted using clinical CT scan images taken for other indications based on image processing and artificial neural network (ANN). The network used in this study is a standard backpropagation neural network having five input neurons with one hidden layer having 40 neurons with a tan-sigmoidal activation function. …”
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Design and Control of an Upper Limb Bionic Exoskeleton Rehabilitation Device Based on Tensegrity Structure by Peng Ni, Jianwei Sun, Jialin Dong

“…Finally, we designed the impedance control scheme of the PSO–BP neural network based on a fuzzy rehabilitation state evaluator. …”
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Applied aspects of modern non-blind image deconvolution methods by O.B. Chaganova, A.S. Grigoryev, D.P. Nikolaev, I.P. Nikolaev

“…Nevertheless, neural network models have made notable progress in their robustness to noise and distortions. …”
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RETRACTED ARTICLE: Conceptualising a channel-based overlapping CNN tower architecture for COVID-19 identification from CT-scan images by Ravi Shekhar Tiwari, Lakshmi D, Tapan Kumar Das, Kathiravan Srinivasan, Chuan-Yu Chang

“…Abstract Convolutional Neural Network (CNN) has been employed in classifying the COVID cases from the lungs’ CT-Scan with promising quantifying metrics. …”
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Ferrography Wear Particles Image Recognition Based on Extreme Learning Machine by Qiong Li, Tingting Zhao, Lingchao Zhang, Wenhui Sun, Xi Zhao

“…With the rapid development of computer image processing technology, neural network based on traditional gradient training algorithm can be used to recognize them. …”
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Monitoring Population Phenology of Asian Citrus Psyllid Using Deep Learning by Maria Bibi, Muhammad Kashif Hanif, Muhammad Umer Sarwar, Muhammad Irfan Khan, Shouket Zaman Khan, Casper Shikali Shivachi, Asad Anees

“…Multiple linear regression, random forest regressor, and deep neural network approaches were compared to predict population dynamics of Asian citrus psyllid. …”
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Self-adaptive fuzzing optimization method based on distribution divergence by XU Hang, JI Jiangan, MA Zheyu, ZHANG Chao

“…Then, a deep graph convolutional neural network was constructed to extract the feature embeddings of the interprocedural comparison flow graph, and this neural network was used as the deep Q-network for deep reinforcement learning. …”
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