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5021
A Data-Driven Comparative Analysis of Machine-Learning Models for Familial Hypercholesterolemia Detection
Published 2024-11-01“…The dataset was then split into training and test sets with an 80/20 ratio. Machine-learning models were trained, with hyperparameters optimized via grid search. …”
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5022
Robust zero-watermarking for color images using hybrid deep learning models and encryption
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5023
Towards an Efficient Remote Sensing Image Compression Network with Visual State Space Model
Published 2025-01-01“…Furthermore, in comparison to traditional codecs and learned image compression algorithms, our model achieves BD-rate reductions of −4.48%, −9.80% over the state-of-the-art VTM on the AID and NWPU VHR-10 datasets, respectively, as well as −6.73% and −7.93% on the panchromatic and multispectral images of the WorldView-3 remote sensing dataset.…”
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5024
Building Information Modelling- (BIM-) Based Generative Design for Drywall Installation Planning in Prefabricated Construction
Published 2021-01-01“…The integration of BIM with other analytical algorithms also allows optimization of designs, such as the generative design that can parametrize the design. …”
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5025
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5026
Reducing Safety Risks in Construction Tower Crane Operations: A Dynamic Path Planning Model
Published 2024-11-01“…The proposed model consists of three modules: first, a path information collection module preprocessing the video data to capture relevant operational path information; second, a path safety risk evaluation module employing You Only Look Once version 8 (YOLOv8) instance segmentation to identify potential risk factors along the operational path, e.g., potential drop zones and the positions of nearby workers; and finally, a path planning module utilizing an improved Dynamic Window Approach for tower cranes (TC-DWA) to avoid risky areas and optimize the operational path for enhanced safety. …”
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5027
Inversion Study of Hydrogeological Parameters for Metro Foundation Pit Confined Aquifiers Based on Surrogate Modeling
Published 2025-07-01“…The use of deep learning-based surrogate modeling combined with optimization algorithms enables efficient and accurate inversion analysis of groundwater parameters.…”
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5028
A multiobjective continuation method to compute the regularization path of deep neural networks
Published 2025-03-01“…For linear models, it is well known that there exists a regularization path connecting the sparsest solution in terms of the ℓ1 norm, i.e., zero weights and the non-regularized solution. …”
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5029
Comparison of Kolmogorov–Arnold Networks and Multi-Layer Perceptron for modelling and optimisation analysis of energy systems
Published 2025-05-01“…Considering the improved interpretable performance of Kolmogorov–Arnold Networks (KAN) algorithm compared to multi-layer perceptron (MLP) algorithm, a fundamental research question arises on how modifying the loss function of KAN affects its modelling performance for energy systems, particularly industrial-scale thermal power plants. …”
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5030
Power supply vehicle routing problem: formulation and solution
Published 2025-07-01“…Building on this definition, this problem is formulated as a two-stage mixed-integer nonlinear programming model. To solve this model, we adopted a genetic algorithm as the main algorithm framework. …”
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5031
Deep learning-based edge detection for random natural images
Published 2025-03-01“…Deep learning approaches offer significant advantages in capturing high-level representations, thereby improving the accuracy and robustness of edge detection algorithms. …”
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5032
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5033
Query scheduling based on cloud-edge multi-data warehouse architecture and cost prediction model
Published 2025-01-01“…The scheduling framework and optimization algorithm achieve significant performance improvement on SSB and TPC-DS datasets. …”
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5034
Query scheduling based on cloud-edge multi-data warehouse architecture and cost prediction model
Published 2025-01-01“…The scheduling framework and optimization algorithm achieve significant performance improvement on SSB and TPC-DS datasets. …”
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5035
Enhancing Fault Detection in AUV-Integrated Navigation Systems: Analytical Models and Deep Learning Methods
Published 2025-06-01“…Specifically, the particle swarm optimization (PSO) algorithm was employed to optimize the hyperparameters of a long short-term memory (LSTM) neural network, leading to the development of a PSO-LSTM fault detection model. …”
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5036
Exponential Squared Loss-Based Robust Variable Selection with Prior Information in Linear Regression Models
Published 2025-07-01“…Experimental results demonstrate that our model significantly improves estimation robustness compared to existing methods, even in outlier-contaminated scenarios.…”
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5037
Numerical model of surface morphology and solid-liquid contact angle in wire electrical discharge machining
Published 2025-03-01“…Combining the established numerical model and multi-objective optimization algorithm, the contact angle of the surface machined by WEDM is greater than 125°, and the stability and controllability of hydrophobic surface preparation are greatly improved. …”
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5038
Apple Rootstock Cutting Drought-Stress-Monitoring Model Based on IMYOLOv11n-Seg
Published 2025-07-01“…The neck part is optimized by the KFHA module (Kalman filter and Hungarian algorithm model), and the head part enhances post-processing effects through HIoU-SD (hierarchical IoU–spatial distance filtering algorithm). …”
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5039
YOLOv5-DTW: Gesture recognition based on YOLOv5 and dynamic time warping for digital media design
Published 2025-06-01“…In the recognition stage, firstly, the background and sensor thermal noise are used to enhance the classification data set, and the background optimization preprocessing algorithm is designed to improve the adaptability of the model to the complex background. …”
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5040
Storage life evaluation of photodetector based on multi-parameter performance degradation and competitive failure
Published 2025-04-01“…This method comprehensively considered whether the key performance parameters of the sample have deteriorated or improved trend. Firstly, the optimal degradation model with a single parameter was selected by performance degradation modeling, so that the pseudo-life of the sample with increasing degradation trend was calculated according to the failure threshold, and the pseudo-life was regarded as the right-censored data for the sample with decreasing degradation trend. …”
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