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1981
Integrated Wavelet-Grey-Neural Network Model for Heritage Structure Settlement Prediction
Published 2025-06-01“…Finally, a wavelet reconstruction fusion algorithm is developed to achieve the collaborative optimization of dual-channel prediction results. …”
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1982
Distributed Photovoltaic Distribution Voltage Prediction Based on eXtreme Gradient Boosting and Time Convolutional Networks
Published 2024-01-01“…The model uses eXtreme gradient boosting for feature selection and time convolutional network and two-layer prediction strategy for voltage prediction. Then, the model is improved and optimized using residual module with bottle sea sheath algorithm. …”
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1983
Integrated Cloud-Twin Synchronization for Supply Chain 5.0
Published 2025-03-01“…The model determines optimal weights to balance objectives, achieving an optimal objective function value that reflects trade-offs among operational efficiency, cost, and sustainability. …”
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1984
A review on agrowaste based activated carbons for pollutant removal in wastewater systems
Published 2024-04-01“…The deployment of mathematical and machine learning approaches (ANN and novel GMDH algorithms) in optimization of batch and continuous adsorption processes are also highlighted. …”
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1985
High-Resolution Direction of Arrival Estimation of Underwater Multitargets Using Swarming Intelligence of Flower Pollination Heuristics
Published 2022-01-01“…For this purpose, particle swarm optimization (PSO), minimum variance distortion-less response (MVDR), multiple signal classification (MUSIC), and estimation of signal parameter via rotational invariance technique (ESPRIT) standard counterparts are employed along with Crammer–Rao bound (CRB) to improve the worth of the proposed setup further. …”
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1986
Dynamic characteristics of a semi-active fractional-order inerter-based suspension with acceleration-velocity switch control
Published 2025-06-01“…The dynamic model of the SA-FOIB suspension with AVS control is established, its dynamic response under road harmonic excitation is obtained using the averaging method, the dynamic performance under road harmonic and random excitations is analyzed and evaluated by the vehicle body acceleration, suspension dynamic deflection and wheel dynamic load, the optimized structural parameters are obtained using the genetic algorithm optimization method. …”
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1987
A Rice Leaf Area Index Monitoring Method Based on the Fusion of Data from RGB Camera and Multi-Spectral Camera on an Inspection Robot
Published 2024-12-01“…The model based on the LightGBM regression algorithm has the most improvement in accuracy, with a coefficient of determination (R<sup>2</sup>) of 0.892, a root mean square error (RMSE) of 0.270, and a mean absolute error (MAE) of 0.160. …”
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1988
Analytical framework for household energy management: integrated photovoltaic generation and load forecasting mechanisms
Published 2025-07-01“…The KNN-GA-MBP algorithm demonstrates the best prediction performance among the three algorithms, with an RMSE of only 0.39 kW, this represents a 43.37% improvement in RMSE over the KNN-MBP algorithm and a 71.89% improvement over the MBP algorithm.…”
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1989
Technology for risk assessment at product lifecycle stages using fuzzy logic
Published 2020-12-01“…It is suggested that if there is a priori information about previously occurred events that can be used for risk analysis and fore casting, the fuzzy conclusion should be refined using widely known methods of mathematical statistics, optimization algorithms, for example, gradient descent, simplex method or genetic algorithms. …”
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1990
A Dynamic Kalman Filtering Method for Multi-Object Fruit Tracking and Counting in Complex Orchards
Published 2025-07-01“…To address these challenges, this paper proposes a multi-object fruit tracking and counting method, which integrates an improved YOLO-based object detection algorithm with a dynamically optimized Kalman filter. …”
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1991
Predicting hydrocarbon reservoir quality in deepwater sedimentary systems using sequential deep learning techniques
Published 2025-07-01“…Three sequential deep learning models—Recurrent Neural Network and Gated Recurrent Unit—were developed and optimized using the Adam algorithm. The Adam-LSTM model outperformed the others, achieving a Root Mean Square Error of 0.009 and a correlation coefficient (R2) of 0.9995, indicating excellent predictive performance. …”
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1992
Nondestructive freshness recognition of chicken breast meat based on deep learning
Published 2025-07-01“…Experimental results show that in the improved algorithm, YOLOv8n_CA_DSC3 achieves suboptimal recall rate but optimal precision, average precision at IoU = 0.5, and average precision at IoU = 0.5:0.95. …”
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1993
A visual positioning method for tunnel boring machines in underground coal mines based on anchor net features
Published 2025-06-01“…The proposed method yielded a maximum error of 163 mm, indicating a 23.5% reduction compared to the 213 mm obtained using the PL-VINS algorithm. Additionally, the root mean square error (RMSE) decreased from 0.531 to 0.426, suggesting a reduction of 19.8%. …”
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1994
Sonar-Based Simultaneous Localization and Mapping Using the Semi-Direct Method
Published 2024-12-01“…To obtain better feature extraction results in specific directions, we propose a method that accelerates the computation of the two-dimensional SO-CFAR algorithm, with the time cost being only a very slight increase compared to the one-dimensional SO-CFAR. …”
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1995
Research on collaborative scheduling strategies of multi-agent agricultural machinery groups
Published 2025-03-01“…Finally, the solution is optimized through a local search strategy. In this study, three dispatch centers were selected within the maize growing area of Hebei Province, and comparative analyses were conducted for 20, 40, 50, 100 and 120 farmlands, respectively.The results indicate that the MCMPP-DRL algorithm achieves a reduction in total scheduling costs of at least 9.66%, 14.34% and 24.41% compared to Ant Colony Optimization (ACO), Simulated Annealing (SA) and Genetic Algorithms(GA), respectively.The significant optimization in scheduling costs demonstrates that the MCMPP-DRL algorithm establishes a robust theoretical foundation and offers technical support for addressing complex scheduling problems involving multiple dispatch centers and multiple.…”
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1996
P-Band PolInSAR Sub-Canopy Terrain Retrieval in Tropical Forests Using Forest Height-to-Unpenetrated Depth Mapping
Published 2025-06-01“…A nonlinear iterative optimization algorithm is then employed to estimate forest height, from which a fundamental mapping between forest height and unpenetrated depth is established. …”
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1997
Enhancing prediction of wildfire occurrence and behavior in Alaska using spatio-temporal clustering and ensemble machine learning
Published 2025-03-01“…A sequential Genetic Algorithm (GA) is employed for cost-effective feature selection from 49 geospatial features, including remote sensing and reanalysis data. …”
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1998
Enhancing Crowd Safety at Hajj: Real-Time Detection of Abnormal Behavior Using YOLOv9
Published 2025-01-01“…Leveraging deep learning, this research accurately identifies features of abnormal behavior from the HAJJv2 dataset, specifically curated and annotated for the Hajj context. Optimization of the YOLOv9 algorithm for this scenario demonstrated superior performance metrics (mean Average Precision (mAP@0.5), Recall, and Precision) when compared with its predecessors (YOLOv4, YOLOv5, YOLOv7, and YOLOv8), highlighting significant improvements in detection accuracy and real-time applicability. …”
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1999
Design and Prototype Verification of a 3-meter Aperture Wrap-rib Reflector
Published 2025-01-01“…The shape of the lenticular tube wrap-rib was optimized by combining the form-finding analysis of the flexible reflector with the genetic algorithm. …”
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2000
From Tables to Computer Vision: Transforming HPDC Process Data into Images for CNN-Based Deep Learning
Published 2025-06-01“…Utilizing a combination of statistical pre-processing, intelligent generative models, visual data transformations and deep learning, the methodology offers a comprehensive approach to enhancing production efficiency, ensuring superior process control and improving the quality of HPDC products. This development signifies a significant advancement in the field of intelligent systems for manufacturing process optimization, aligning with the principles of Industry 4.0 and Quality 4.0.…”
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