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Optimizing electric vehicle energy consumption prediction through machine learning and ensemble approaches
Published 2025-08-01“…Among the optimization techniques, Optuna proves to be the most effective for tuning the KNN model. …”
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303
Shape Optimization of Multi-chamber Acoustical Plenums Using the BEM, Neural Networks, and the GA Method
Published 2015-10-01“…The results reveal that the maximum value of the transmission loss (TL) can be improved at the desired frequencies. Consequently, the algorithm proposed in this study can provide an efficient way to develop optimal multi-chamber plenums for industry.…”
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304
A Tunnel Lining Line Identification Algorithm Based on Supervised Heatmap
Published 2024-07-01“…Therefore, using 8~10 outer points to supervise model learning in the first 10 rounds yields the most significant improvements. …”
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305
Bandit Algorithms for Efficient Toxicity Detection in Competitive Online Video Games
Published 2025-01-01“…This algorithm balances exploration and exploitation to optimize long-term performance and is designed intentionally for easy deployment in production environments. …”
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306
Wafer Defect Classification Algorithm With Label Embedding Using Contrastive Learning
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307
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Algorithm of reconstruction combined midface defects after resection malignant tumors
Published 2022-08-01“…This allows to determining the type and volume of the defect, plan optimal method of reconstruction, model the required flap geometry, making a template for harvesting flap, calculating the position and number of titanium plates for fixation, and, if necessary, print an individual mesh of the infraorbital wall.…”
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309
Reconstruction of Highway Vehicle Paths Using a Two-Stage Model
Published 2025-02-01“…To address the challenge of multiple possible paths due to missing trajectory data, this study proposes a novel two-stage model for vehicle path reconstruction. In the first stage, a Gaussian Mixture Model (GMM) is integrated into a path choice model to estimate the mean and standard deviation of travel times for each road segment, utilizing an improved Expectation Maximization (EM) algorithm. …”
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310
Identifying Capsule Defect Based on an Improved Convolutional Neural Network
Published 2020-01-01“…The Adam optimizer is introduced to accelerate model training and improve model convergence. …”
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311
Influence of soil parameters on dynamic compaction: numerical analysis and predictive modeling using GA-optimized BP neural networks
Published 2025-07-01“…Orthogonal experimental design and single factor analysis were used to quantify the influence of each parameter on the compaction volume. In order to improve the prediction accuracy, this paper introduces genetic algorithm (GA) to optimize the BP neural network model, constructs a multi-factor dynamic compaction prediction model, and compares it with the traditional BP model. …”
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312
Hybrid Darknet53-SVM model with random grid search optimization for enhanced colorectal cancer histological image classification
Published 2025-07-01“…To enhance the classification performance, Darknet53 was hybridized with a SVM by replacing the dense layer, and hyperparameters were optimized using a Random Grid Search algorithm. The optimized hybrid model exhibited a remarkable improvement, with an Acc. of 99.7%, Sen. of 99.7%, Spec. of 99.91%, Prec. of 99.98%, and F1-score of 99.98%, alongside significant improvements in other metrics. …”
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313
Construction of Clinical Predictive Models for Heart Failure Detection Using Six Different Machine Learning Algorithms: Identification of Key Clinical Prognostic Features
Published 2024-12-01“…Finally, a correlation analysis was conducted to examine the relationships between these features and other significant clinical features.Results: The logistic regression (LR) model was determined to be the optimal machine learning algorithm in this study, achieving an accuracy of 0.64, a precision of 0.45, a recall of 0.72, an F1 score of 0.51, and an AUC of 0.81 in the training set and 0.91 in the testing set. …”
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314
Recurrent academic path recommendation model for engineering students using MBTI indicators and optimization enabled recurrent neural network
Published 2025-07-01“…To address this issue, an intelligent recommendation model is proposed that assists students in discovering the most suitable academic path based on their personal background and personality traits. …”
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315
A Mobile Agent Routing Algorithm in Dual-Channel Wireless Sensor Network
Published 2012-05-01“…A mobile agent routing algorithm (MARA) is presented in this paper, and then based on the dual-channel communication model, the two-layer network combination optimization strategy is also proposed. …”
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316
Enhancing the prediction of groundwater quality index in semi-arid regions using a novel ANN-based hybrid arctic puffin-hippopotamus optimization model
Published 2025-06-01“…Study focus: This study presents a novel hybrid arctic puffin–hippopotamus optimization (HPHO) algorithm combined with an artificial neural network (ANN) to improve irrigation water quality index (IWQI) predictions in semi-arid areas. …”
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317
Mathematical Modeling of Optimal Drone Flight Trajectories for Enhanced Object Detection in Video Streams Using Kolmogorov–Arnold Networks
Published 2025-06-01“…While most research focuses on improving detection algorithms, the relationship between flight parameters and detection performance remains poorly understood. …”
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318
Implementation of SVM Algorithm to Predict Song Popularity based on Sentiment Analysis of Lyrics
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319
RRMSE-enhanced weighted voting regressor for improved ensemble regression.
Published 2025-01-01“…This uniform weighting approach doesn't consider that some models may perform better than others on different datasets, leaving room for improvement in optimizing ensemble performance. …”
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320
An optimal weighting-based hybrid classifier for Children's congenital heart diseases signal processing
Published 2025-09-01“…The main objective of the proposed optimal weighting-based CNN-LSTM-SVM (OCLS) hybrid classifier is to simultaneously leverage the unique advantages of CNN in feature extraction from input signals, LSTM in modeling the sequential patterns of signals, SVM in classifying regular patterns, and especially the proposed weighting algorithm to optimally integrate the outputs of these components. …”
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