Application of Improved Deep Learning Method in Intelligent Power System by HuiJie Liu, Yang Liu, ChengWen Xu

“…The method uses the convolutional neural network to establish the energy prediction calculation model, uses CNN adaptive data features to mine characteristics, quantifies power uncertainty, uses drop regularization to optimize the deep network structure, uses the deep forest to learn the extracted data features, and builds a prediction model, in order to achieve accurate prediction of power load and solve the problem that the accuracy of existing forecasting methods decreases due to random fluctuations of power. …”
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Artificial Intelligence Scribe and Large Language Model Technology in Healthcare Documentation: Advantages, Limitations, and Recommendations by Sarah A. Mess, MD, Alison J. Mackey, PhD, David E. Yarowsky, PhD

“…Insidious and potentially significant errors of omission, fabrication, or substitution may occur. The neural network algorithms of LLMs have unpredictable sensitivity to user input and inherent variability in their output. …”
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Research on the Prediction Model of the Friction Coefficient of Asphalt Pavement Based on Tire-Pavement Coupling by Miao Yu, Xinquan Xu, Chuanhai Wu, Shanqiang Li, Mingxia Li, Haifeng Chen

“…By integrating the above influence factors, the BP neural network method was applied to the regression of the prediction model for the asphalt pavement friction coefficient. …”
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Perfusion MRI in automatic classification of multiple sclerosis lesion subtypes by Ehsan Homayouny, Rasoul Mahdavifar Khayati, Seyed Massood Nabavi, Vania Karami

“…Therefore, a Bayesian classifier based on the adaptive mixture method was used to segment all lesions, and an artificial neural network (ANN) employed a multi‐layer Perceptron as a subtype classifier. …”
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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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Discrimination of Melanoma Using Laser-Induced Breakdown Spectroscopy Conducted on Human Tissue Samples by Muhammad Nouman Khan, Qianqian Wang, Bushra Sana Idrees, Geer Teng, Xutai Cui, Kai Wei

“…Chemometric methods, artificial neural network (ANN), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and partial least square discriminant analysis (PLS-DA) are used to build the classification models. …”
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Intelligent On/Off Dynamic Link Management for On-Chip Networks by Andreas G. Savva, Theocharis Theocharides, Vassos Soteriou

“…., expected future utilization link levels), where links are turned off and on via the use of a small and scalable neural network. Simulation results with various synthetic traffic models over various network topologies show that the proposed work can reach up to 13% power savings when compared to a trivial threshold computation, at very low (<4%) hardware overheads.…”
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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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MAF-CNER : A Chinese Named Entity Recognition Model Based on Multifeature Adaptive Fusion by Xuming Han, Feng Zhou, Zhiyuan Hao, Qiaoming Liu, Yong Li, Qi Qin

“…The model uses bidirectional long short-term memory (BiLSTM) neural network to extract stroke and radical features and adopts a weighted concatenation method to fuse two sets of features adaptively. …”
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Research on TCN Model Based on SSARF Feature Selection in the Field of Human Behavior Recognition by Wei Zhang, Guibo Yu, Shijie Deng

“…To overcome this problem, this paper investigates a temporal convolutional neural network (TCN) model based on improved sparrow search algorithm random forest (SSARF) feature selection to accurately identify human behavioral traits based on wearable devices. …”
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Sudden Intrabulbar Amyloid Increase Simultaneously Disrupts Olfactory Bulb Oscillations and Odor Detection by Rebeca Hernández-Soto, Keila Dara Rojas-García, Fernando Peña-Ortega

“…Moreover, this loss of smell appears to be related to alterations in neural network activity in several olfactory-related circuits, including the OB, as has been observed in anesthetized animals and brain slices. …”
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A Photovoltaic Array Fault Diagnosis Method Considering the Photovoltaic Output Deviation Characteristics by Jian Zhao, Qian Sun, Ning Zhou, Hao Liu, Haizheng Wang

“…Finally, the fault diagnosis of a PV array is realized by using the probabilistic neural network (PNN), and the effectiveness of the proposed method is verified. …”
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Adaptive calibration of the angle sensor for gyroscope by V. A. Smirnov, A. B. Snedkov

“…A comparative analysis of the traditional method of joint calibration of angle sensors with the method based on the use of neural networks is performed.…”
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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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English Phrase Speech Recognition Based on Continuous Speech Recognition Algorithm and Word Tree Constraints by Haifan Du, Haiwen Duan

“…Through simulation experiments, the NWBP algorithm improves the degree of fitting and convergence speed in the training of complex convolutional neural networks compared with other algorithms, reduces the redundant computation, and shortens the training time to a certain extent, and the algorithm has the advantage of accelerating the convergence of the network compared with simple networks. …”
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Implementation of the Human-Like Lane Changing Driver Model Based on Bi-LSTM by Junyu Cai, Haobin Jiang, Junyan Wang

“…This paper uses four neural network models to compare the prediction on the test set, then uses different input types to compare the prediction accuracy of the model, and finally verifies the generalization ability of the model on the verification set. …”
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Automatic Tracking and Characterization of Cumulonimbus Clouds from FY-2C Geostationary Meteorological Satellite Images by Yu Liu, Du-Gang Xi, Zhao-Liang Li, Chun-Xiang Shi

“…First, a seeded region growing (SRG) algorithm is used with artificial neural network (ANN) cloud classification as preprocessing to identify consistent homogeneous Cb patches from infrared images. …”
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Detection and Attribution of a Spatial Heterogeneity in the Temporal Evolution of Bulgarian River Discharge by Natalya A. Kilifarska, Gergana I. Metodieva, Antonia Ch. Mokreva

“…., temperature, precipitation, and ozone at 70 hPa), combined with neural network analysis results, suggests ozone as a possible reason for the heterogeneous hydrological response. …”
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Multi-Resolution Wavelet-Transformed Image Analysis of Histological Sections of Breast Carcinomas by Hae-Gil Hwang, Hyun-Ju Choi, Byeong-Il Lee, Hye-Kyoung Yoon, Sang-Hee Nam, Heung-Kook Choi

“…In the classification step, we applied two types of classifiers to the extracted features, namely a statistics-based multivariate (discriminant) analysis and a neural network. Using features from second-level Haar transform wavelet images in combination with discriminant analysis, we obtained classification accuracies of 96.67 and 87.78% for the training and testing set (90 images each), respectively. …”
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