Cloud-Based Framework for COVID-19 Detection through Feature Fusion with Bootstrap Aggregated Extreme Learning Machine by Amjad Rehman Khan, Tanzila Saba, Tariq Sadad, Seng-phil Hong

“…An extreme learning machine (ELM) is a neural network modification with a high capability for pattern recognition and classification problems for COVID-19 detection. …”
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A METHOD FOR MONITORING RICE SEED LOSS BASED ON WOA-BP ALGORITHM by Jin Chen, Ting Shi, Yaoming Li, Yahui Zhu, Caoyuan Niu

“…Aiming at the problems of the slow response speed and low monitoring accuracy of the existing domestic seed loss rate monitoring models, this paper proposed a rice seed loss rate monitoring method based on the whale optimization algorithm-back propagation neural network (WOA-BP). The loss rate monitoring device consisted of a piezoelectric ceramic sensor module, charge amplification circuit, band-pass filter circuit, analog-to-digital (AD) converter, main control unit, etc. …”
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Research on Mechanical Properties and Parameter Identification of Beam-Column Joint with Gusset Plate Angle Using Experiment and Stochastic Sensitivity Analysis by Xian Dong, Yadi Wang

“…An improved chaotic particle swarm optimization (ICPSO) neural network algorithm was used to study the stochastic sensitivity. …”
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A novel RNN architecture to improve the precision of ship trajectory predictions by Martha Dais Ferreira, Jessica N. A. Campbell

“…To solve these challenges, Recurrent Neural Network (RNN) models have been applied to STP to allow scalability for large data sets and to capture larger regions or anomalous vessels behavior. …”
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Optimizing the Prediction Accuracy of Friction Capacity of Driven Piles in Cohesive Soil Using a Novel Self-Tuning Least Squares Support Vector Machine by Doddy Prayogo, Yudas Tadeus Teddy Susanto

“…The prediction accuracy of the ST-LSSVM was then compared to other machine learning methods, namely, LS-SVM and BPNN, and was benchmarked with the previous results by neural network (NN) from Goh using coefficient of correlation (R), mean absolute error (MAE), and root mean square error (RMSE). …”
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IoT-based approach to multimodal music emotion recognition by Hanbing Zhao, Ling Jin

“…The proposed CGF-Net model combines a 3D Convolutional Neural Network (3D-CNN), Gated Recurrent Unit (GRU), and Fully Connected Network (FCN). …”
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Unsupervised Learning in a Ternary SNN Using STDP by Abhinav Gupta, Sneh Saurabh

“…This paper proposes a novel implementation of a ternary Spiking Neural Network (SNN) and investigates it using a hierarchical simulation framework. …”
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Cross-ViT based benign and malignant classification of pulmonary nodules. by Qinfang Zhu, Liangyan Fei

“…There are many methods using Convolutional neural network (CNN) for benign and malignant classification of pulmonary nodules, but traditional CNN models focus more on the local features of pulmonary nodules and lack the extraction of global features of pulmonary nodules. …”
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SOC and SOH Prediction of Lithium‐Ion Batteries Based on LSTM–AUKF Joint Algorithm by Yancheng Song, Jiaqi Lu, Huai Zhang, Guangjun Liu

“…The approach leverages a multihead‐attention‐enhanced long short‐term memory (LSTM) neural network combined with an adaptive unscented Kalman filter to accurately calculate the battery's state of charge (SOC) and state of health (SOH). …”
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Federated Learning for Brain Tumor Diagnosis: Methods, Challenges and Future Prospects by Ma Yuhan

“…This paper analyzes various Convolutional Neural Network (CNN) models, including VGG16, ResNet50, DenseNet121, and EfficientNet, exploring their integration within the FL framework to enhance diagnostic accuracy while preserving patient data privacy. …”
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GA-Attention-Fuzzy-Stock-Net: An optimized neuro-fuzzy system for stock market price prediction with genetic algorithm and attention mechanism by Burak Gülmez

“…The research investigates the effectiveness of different architectural configurations, including variations in fuzzy layer membership functions (triangular, trapezoidal, Gaussian) and neural network architectures (1D ANN, 2D ANN, 1D LSTM, 2D LSTM). …”
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Artificial Intelligence-Based Real-Time Signal Sample and Analysis of Multiperson Dragon Boat Race in Complex Networks by Yu Li, Peihua Liu

“…Based on the complex network theory, we regard the 23 dragon boat athletes in the dragon boat race as 23 nodes so as to establish a network with 23 nodes and reflect the importance of nodes by measuring the impact of node deletion on the results of the race. The neural network multilayer perceptron (MLP) model is used for training to obtain the optimal combined value with speed and heart rate for each race stage. …”
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Prediction of Frequency for Simulation of Asphalt Mix Fatigue Tests Using MARS and ANN by Ali Reza Ghanizadeh, Mansour Fakhri

“…Two methods including Multivariate Adaptive Regression Splines (MARS) and Artificial Neural Network (ANN) methods were then employed to predict the effective length (i.e., frequency) of tensile stress and strain pulses in longitudinal and transverse directions based on haversine waveform. …”
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Analysis of Psychological and Emotional Tendency Based on Brain Functional Imaging and Deep Learning by Lin Zhou

“…Then, combining data enhancement (Mixup) with three-dimensional convolutional neural network (3D-CNN), an emotion-related EEG topographic map classification method based on M-3DCNN is proposed. …”
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Image Recognition and Simulation Based on Distributed Artificial Intelligence by Tao Fan

“…By analyzing the existing digital image recognition methods, an improved BP neural network algorithm is proposed. Under the premise of ensuring accuracy, the recognition speed of digital images is accelerated, the time required for recognition is reduced, real-time performance is guaranteed, and the effectiveness of the algorithm is verified.…”
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Automatic Evaluation of Internal Combustion Engine Noise Based on an Auditory Model by Kai Liang, Haijun Zhao

“…To improve the accuracy and efficiency of the objective evaluation of noise quality from internal combustion engines, an automatic noise quality classification model was constructed by introducing an auditory model-based acoustic spectrum analysis method and a convolutional neural network (CNN) model. A band-pass filter was also designed in the model to automatically extract the features of the noise samples, which were later used as input data. …”
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A No-Reference Modular Video Quality Prediction Model for H.265/HEVC and VP9 Codecs on a Mobile Device by Debajyoti Pal, Vajirasak Vanijja

“…We also use an Artificial Neural Network approach for building the model and compare its performance with the regressive approach.…”
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Haptic Perception with Self-Organizing ANNs and an Anthropomorphic Robot Hand by Magnus Johnsson, Christian Balkenius

“…The four systems differ in the kind of self-organizing neural network used for clustering. For the mapping of the explored objects, one system uses a Self-Organizing Map (SOM), one uses a Growing Cell Structure (GCS), one uses a Growing Cell Structure with Deletion of Neurons (GCS-DN), and one uses a Growing Grid (GG). …”
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Bifurcation Analysis and Synchronous Patterns between Field Coupled Neurons with Time Delay by Li Zhang, Xinlei An, Jiangang Zhang, Qianqian Shi

“…Exploring the biophysical properties of coupling channels is of great significance for further understanding the rhythm transitions of neural network electrical activity patterns and preventing neurological diseases. …”
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Integration and Fusion of Geologic Hazard Data under Deep Learning and Big Data Analysis Technology by Feng He, Chunxue Liu, Hongjiang Liu

“…On the premise of optimizing the processing of landslide images, first, the Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) based on the natural statistical characteristics of the spatial domain is introduced, which is initially combined with Super-Resolution Convolutional Neural Network (SRCNN). Then, the AlexNet is fine-tuned and applied to highway landslide monitoring and surveying. …”
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