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2141
The application of machine learning approaches to classify and predict fertility rate in Ethiopia
Published 2025-01-01“…The best ML models to classify and predict fertility rates were random forest, one-dimensional convolutional neural network, logistic regression, and gradient boost classifier. …”
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2142
Computer Vision-assisted Wireless Channel Simulation for Millimeter Wave Human Motion Recognition
Published 2025-02-01“…The Doppler spectrograms obtained from the simulation can be used to train deep neural network for real wireless human motion recognition. …”
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2143
LSTM+MA: A Time-Series Model for Predicting Pavement IRI
Published 2025-01-01“…The performance of the LSTM+MA is compared with other state-of-the-art models, including logistic regressor (LR), support vector regressor (SVR), random forest (RF), K-nearest-neighbor regressor (KNR), fully connected neural network (FNN), XGBoost (XGB), recurrent neural network (RNN) and LSTM. …”
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2144
Analysis and Prediction of Grouting Reinforcement Performance of Broken Rock Considering Joint Morphology Characteristics
Published 2025-01-01“…In this study, six algorithms—Random Forest (RF), Support Vector Regression (SVR), BP Neural Network, GA-BP Neural Network, Genetic Programming (GP), and ANN-based MCD—are evaluated using 300 samples. …”
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2145
FingerDTA: A Fingerprint-Embedding Framework for Drug-Target Binding Affinity Prediction
Published 2023-03-01“…Artificial intelligence methods, such as Convolutional Neural Network (CNN), are widely used to facilitate new drug discovery. …”
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2146
Prediction Model of Soybean Meal Protein Content Based on Low-field Nuclear Magnetic Resonance and Near-infrared Data Fusion
Published 2025-01-01“…The partial least squares method, BP (Back Propagation) neural network and Sparrow Search Algorithm (SSA) were employed to optimize the BP neural network (SSA-BP). …”
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2147
Presenting a model for the diagnosis of heart failure using cumulative and deep learning algorithms: a case study of tehran heart center
Published 2022-03-01“…In the classification phase, basic techniques were used, including a decision tree, a neural network, and different cumulative techniques such as gradient boosting, random forest, and the novel deep learning method. …”
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2148
Robust Prediction of Healthcare Inflation Rate With Statistical and AI Methods in Iran
Published 2024-01-01“…In the next process, by doubling the forecasting window, it is observed that artificial neural network (ANN) (i.e., Bayesian NARANN) strictly outperformed other models. …”
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2149
Long-term forecasting of shield tunnel position and attitude deviation using the 1DCNN-informer method
Published 2025-03-01“…This study introduces a novel deep learning model, termed 1DCNN-Informer, which integrates the one-dimensional convolutional neural network (1DCNN) and the Informer model. The model was trained and validated using datasets from the Nanjing Metro shield tunnel project in China. …”
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2150
A New Bearing Fault Diagnosis Method Based on Deep Transfer Network and Supervised Joint Matching
Published 2024-01-01“…Second, a deep transfer convolutional neural network is built by the way of fine-tuning, and the trained network is used to extract deep features from different domains. …”
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2151
A Hybrid Approach for Sports Activity Recognition Using Key Body Descriptors and Hybrid Deep Learning Classifier
Published 2025-01-01“…The system utilized a hybrid CNN (Convolutional Neural Network) + RNN (Recurrent Neural Network) classifier for event recognition, with Grey Wolf Optimization (GWO) for feature selection. …”
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2152
Knowledge-Based Deep Learning for Time-Efficient Inverse Dynamics
Published 2025-01-01“…The Bidirectional Gated Recurrent Unit (BiGRU) neural network is selected as the backbone of our model due to its proficient handling of time-series data. …”
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2153
Seasonal Tree Height Dynamic Estimation Using Multi-source Remotely Sensed Data in Shenzhen
Published 2025-01-01“…It was found that (a) the seasonal tree height neural network demonstrated the highest prediction accuracy in tree height estimation (R2 = 0.72, mean absolute error = 1.89 m), and the optimization process of Shapley additive explanations reduced 23 features, which improved the prediction accuracy (R2 = 0.80, mean absolute error = 1.58 m) and saved computational resources; (b) the seasonal tree height neural network has a strong generalizability for estimating tree height across seasons and regions; and (c) during 2018 to 2023, tree heights in Shenzhen were mainly concentrated in 6 to 14 m, and the spatial distribution has a strong autocorrelation. …”
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2154
A two-step machine learning approach for predictive maintenance and anomaly detection in environmental sensor systems
Published 2025-06-01“…The models confirmed the proposed framework's accuracy, whereas Random Forest 99.93 %, Neural Network 99.05 %, and AdaBoost 98.04 % validated the effectiveness of the suggested framework. …”
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2155
Rapid learning with phase-change memory-based in-memory computing through learning-to-learn
Published 2025-02-01“…We demonstrate the versatility of our approach in two scenarios: a convolutional neural network performing image classification and a biologically-inspired spiking neural network generating motor commands for a real robotic arm. …”
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2156
Investigating the Working Efficiency of Typical Work in High-Altitude Alpine Metal Mining Areas Based on a SeqGAN-GABP Mixed Algorithm
Published 2021-01-01“…Finally, three high-altitude alpine metal mines in Xinjiang were selected as representative examples to verify the proposed framework by comparing it with other state-of the art models (multiple linear regression prediction model, backpropagation (BP) neural network model, and genetic algorithm back propagation (GA-BP) neural network model). …”
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2157
Application of Extreme Gradient Boosting Based on Grey Relation Analysis for Prediction of Compressive Strength of Concrete
Published 2021-01-01“…Another highlight is that its performance was compared with the frequently used artificial neural network (ANN) and genetic algorithm-artificial neural network (GA-ANN) by using random dataset and the same testing datasets. …”
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2158
Study on an Intelligent Prediction Method of Ticket Price in a Subway System with Public-Private Partnership
Published 2021-01-01“…To effectively cope with the effects of multiple influencing factors and strong nonlinearity among them, the mean impact value (MIV) method and the back-propagation (BP) feed-forward neural network improved by the sparrow search algorithm (SSA) are used in this study to develop an intelligent prediction model. …”
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2159
Analysis and Risk Assessment of Corporate Financial Leverage Using Mobile Payment in the Era of Digital Technology in a Complex Environment
Published 2022-01-01“…Combined with a single-layer neural network or CNN model, the comparison experiment is carried out in two ways. …”
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2160
A Stock Closing Price Prediction Model Based on CNN-BiSLSTM
Published 2021-01-01“…CNN-BiSLSTM is compared with multilayer perceptron (MLP), recurrent neural network (RNN), long short-term memory (LSTM), BiLSTM, CNN-LSTM, and CNN-BiLSTM. …”
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