Analysis of the Correlation between Emerging Industry Development and University Students’ Entrepreneurship Based on Big Data by Yufeng Pan, Hui Huang

“…Experiments show that the big data integration system established by GM correlation analysis and ant colony Elman regression artificial neural network has high accuracy and can well identify the priority relevance of the industrial direction of strategic emerging industries to college students’ entrepreneurship. …”
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Random Target Localization for an Upper Limb Prosthesis by Xinglei Zhang, Binghui Fan, Chuanjiang Wang, Xiaolin Cheng, Hongguang Feng, Zhaohui Tian

“…Secondly, an error correction algorithm where a multipopulation genetic algorithm (MPGA) optimizes backpropagation neural network (BPNN) is utilized to improve the accuracy of ILA. …”
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Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach by E. Golden Julie, S. Tamil Selvi

“…NFEACS consists of two parts: fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. …”
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Physics-aware machine learning for glacier ice thickness estimation: a case study for Svalbard by V. Steidl, J. L. Bamber, J. L. Bamber, X. X. Zhu, X. X. Zhu

“…We incorporate mass conservation and other physically derived conditions into a neural network to predict plausible ice thicknesses even for glaciers without any in situ ice thickness measurements. …”
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Fault Diagnosis of Electromechanical Actuator Based on VMD Multifractal Detrended Fluctuation Analysis and PNN by Hongmei Liu, Jiayao Jing, Jian Ma

“…Finally, the probabilistic neural network (PNN) was utilized to classify the fault modes. …”
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Models, systems, networks in economics, engineering, nature and society by A.A. Sapogov

“…A methodological approach to neural network parametric aggregation was used as an aggregation technique. …”

Bi-directional Pre-trained Network for Single-station Seismic Waveform Analysis by Yuqi CAI, Ziye YU, Weitao WANG, Yanru AN, Lu LI

“…Based on the CSNCD dataset released by the China Earthquake Networks Center, we have developed a bi-directional neural network pre-trained model for single-station data analysis. …”
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Robust Face Detection and Identification under Occlusion using MTCNN and RESNET50 by Eiman Wahab, Wajeeha Shafique, Habiba Amir, Sameena Javed, Muhammad Marouf

“…We used the face detector algorithm called Multi-Task Cascaded Convolutional Neural Network (MTCNN) for face detection with 99.8% accuracy. …”
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Vehicle Attribute Recognition for Normal Targets and Small Targets Based on Multitask Cascaded Network by Fang Liu, Yong Zhang, Hua Gong, Ke Xu, Ligang Cai

“…For vehicle targets with normal size, the multitask cascaded convolution neural network MC-CNN-NT uses the improved Faster R-CNN as the location subnetwork. …”
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BCL6 (B-cell lymphoma 6) expression in adenomyosis, leiomyomas and normal myometrium. by Loreta Canivilo Salas, Bruna Mielczarski, Raquel Camara Rivero, João Sabino Lahogue da Cunha Filho, Ricardo Francalacci Savaris

“…A supervised deep learning neural network was employed to classify samples based on DAB staining. …”
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Deep learning application for stellar parameter determination: III-denoising procedure by Gebran Marwan, Bentley Ian, Brienza Rose, Paletou Frédéric

“…This is true with and without applying data augmentation to the stellar parameters neural network.…”
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Predicting Quality of Service via Leveraging Location Information by Liang Chen, Fenfang Xie, Zibin Zheng, Yaoming Wu

“…Specifically, we propose a location-aware QoS prediction approach, called LANFM, by exploiting neural network techniques and factorization machine to improve user-perceived experience. …”
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Research on RBV Control Strategy of Large Angle Maneuver by Jiangtao Xu, Na Luo, Yu Fu, Litong Wang, Xiande Wu

“…To the high precision and reliable control problem of this vehicle, nonlinear flight control strategy based on neural network robust adaptive dynamic inversion is proposed. …”
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Similarity-Based Summarization of Music Files for Support Vector Machines by Jan Jakubik, Halina Kwaśnicka

“…Recent advancements in the area rely on the use of deep learning, which allows researchers to operate on a low-level description of the music. Deep neural network architectures can learn to build feature representations that summarize music files from data itself, rather than expert knowledge. …”
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Improving Diabetic Patients Monitoring System Using (NCA-CNN) Algorithm based on loT by Ayas Talib Mohammad, Jaber Parchami

“…After that, the most salient characteristics are categorized by a deep convolutional neural network, and an accurate diagnosis of the condition is accomplished. …”
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DLD: An Optimized Chinese Speech Recognition Model Based on Deep Learning by Hong Lei, Yue Xiao, Yanchun Liang, Dalin Li, Heow Pueh Lee

“…To improve the performance of offline Chinese speech recognition, we propose a hybrid acoustic model of deep convolutional neural network, long short-term memory, and deep neural network (DCNN-LSTM-DNN, DLD). …”
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An Incremental Self-Adaptive Wood Species Classification Prototype System by Peng Zhao, Zhen-Yu Li, Yue Li

“…Second, the wood samples of known species are sent into the BP neural network for subsequent wood species classification. …”
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Using Improved XGBoost Algorithm to Obtain Modified Atmospheric Refractive Index by Yanbo Mai, Zheng Sheng, Hanqing Shi, Qixiang Liao

“…Finally, the mean absolute percentage error (MAPE) and root mean-squared error (RMSE) are used as evaluation criteria to compare the prediction results of improved XGBoost algorithm with backpropagation (BP) neural network and traditional XGBoost algorithm. The results show that the MAPE and RMSE of the improved XGBoost algorithm are 39% less than those of BP neural network and 32% less than those of the traditional XGBoost. …”
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Federated Learning-Based Credit Card Fraud Detection: A Comparative Analysis of Advanced Machine Learning Models by Zheng Han

“…This paper introduced federated learning and discussed a few federated learning algorithms applied to the problem—these methods include Federated Graph Attention Network with Dilated Convolution Neural Network (FedGAT-DCNN), FedAvg with Convolutional Neural Network (CNN), and Federated Averaging with Distance-based Weighted Aggregation (FedAvg-DWA) with Random Forest (RF). …”
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Application of VIS/NIR Spectroscopy and SDAE-NN Algorithm for Predicting the Cold Storage Time of Salmon by Ting Wu, Nan Zhong, Ling Yang

“…Meanwhile, a double-layer stacked denoising autoencoder neural network (SDAE-NN) algorithm was introduced to establish the prediction model without spectral pre-preprocessing. …”
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