Research on Behavior Recognition and Online Monitoring System for Liaoning Cashmere Goats Based on Deep Learning by Geng Chen, Zhiyu Yuan, Xinhui Luo, Jinxin Liang, Chunxin Wang

“…YOLOv8n demonstrated superior performance, converging within 50 epochs with an average accuracy of 95.31%, making it a baseline for further improvements. We improved YOLOv8n through dataset expansion, algorithm lightweighting, attention mechanism integration, and loss function optimization. …”
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Minimum Error Integration Method for Quadrilateral Flat Plate Fitting in Steel Construction by Zhuoju Huang, Jiemin Ding

“…Our results demonstrate at most a 75.5% reduction in fitting errors for analytical curved plates with particularly significant improvements in biconvex curvature scenarios. A practical engineering validation reveals that the method increases the proportion of planarizable plates from 27% to 45% under identical tolerance criteria, effectively reducing curved-plate fabrication demands and thus reducing cost and carbon emissions. …”
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A dynamic service migration strategy based on mobility prediction in edge computing by Lanlan Rui, Shuyun Wang, Zhili Wang, Ao Xiong, Huiyong Liu

“…Furthermore, we build a network model and propose a based on Lyapunov optimization method with long-term cost constraints. …”
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Maximum likelihood self-calibration for direction-dependent gain-phase errors with carry-on instrumental sensors:case of deterministic signal model by WANG Ding1, PAN Miao2, WU Ying1

“…Aim at the self-calibration of direction-dependent gain-phase errors in case of deterministic signal model,the maximum likelihood method（MLM） for calibrating the direction-dependent gain-phase errors with carry-on instrumental sensors was presented.In order to maximize the high-dimensional nonlinear cost function appearing in the MLM,an improved alternative projection iteration algorithm,which could optimize the azimuths and direction-dependent gain-phase errors was proposed.The closed-form expressions of the Cramér-Rao bound（CRB） for azimuths and gain-phase errors were derived.Simulation experiments show the effectiveness and advantage of the novel method.…”
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Simulation analysis of path planning for workpiece clamping robots based on digital twin technology by Xin PAN, Min LIANG, Yanchao YIN, Zhong CHEN

“…These results underscore the ability of the algorithm to efficiently and cost-effectively navigate complex obstacle configurations. …”
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A comprehensive techno-economic analysis for a PHEV-integrated microgrid system involving wind uncertainty and diverse demand side management policies by Bishwajit Dey, Laishram Khumanleima Chanu, Gulshan Sharma, Pitshou N. Bokoro

“…The research investigation employed the Differential Evolution (DE) algorithm as an optimization technique. Numerical results show that the total operating cost (TOC) of the MG system reduced from $25,575 during the base load model to $24,521 when the proposed hybrid DSM was implemented. …”
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MC64-ClustalWP2: a highly-parallel hybrid strategy to align multiple sequences in many-core architectures. by David Díaz, Francisco J Esteban, Pilar Hernández, Juan Antonio Caballero, Antonio Guevara, Gabriel Dorado, Sergio Gálvez

“…The new parallelization approach has focused into the most time-consuming stages of this algorithm. In particular, the so-called progressive alignment has drastically improved the performance, due to a fine-grained approach where the forward and backward loops were unrolled and parallelized. …”
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Physically-constrained evapotranspiration models with machine learning parameterization outperform pure machine learning: Critical role of domain knowledge. by Yeonuk Kim, Monica Garcia, T Andrew Black, Mark S Johnson

“…We found a strong correlation (r = 0.93) between the sensitivity of ET estimates to machine-learned parameters and model error (root-mean-square error; RMSE), indicating that reduced sensitivity minimizes error propagation and improves performance. …”
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Empc-based V2G scheduling strategy for multi-attribute EVs aggregator by Haoyang Tang, Zhilu Liu, Lin Zheng, Jianfeng Zheng, Hao Hu, Jinpei Lu, Zhijian Hu

“…The results show that compared with other strategies, the proposed EMPC algorithm can achieve 4–47.4 % reduction in charging costs, significantly reduce the peak valley difference and variance of load, and improve the load curve.…”
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A Study on Hyperspectral Soil Moisture Content Prediction by Incorporating a Hybrid Neural Network into Stacking Ensemble Learning by Yuzhu Yang, Hongda Li, Miao Sun, Xingyu Liu, Liying Cao

“…Then, the gray wolf optimization (GWO) algorithm is adopted to optimize a convolutional neural network (CNN), and a gated recurrent unit (GRU) and an attention mechanism are added to construct a hybrid neural network model (GWO–CNN–GRU–Attention). …”
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Underwater acoustic signal denoising method based on DBO–VMD and singular value decomposition by A. Weiyi Chen, B. Shizhe Wang, C. Zongji Li, D. Li Dong

“…This method utilizes the Dung Beetle Optimization (DBO) algorithm to optimize Variational Mode Decomposition (VMD) and combines it with Singular Value Decomposition (SVD). …”
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Computational intelligence investigations on evaluation of salicylic acid solubility in various solvents at different temperatures by Adel Alhowyan, Wael A. Mahdi, Ahmad J. Obaidullah

“…The dataset was preprocessed using the Standard Scaler to standardize it, ensuring each feature has a mean of zero and a standard deviation of one, followed by outlier detection with Cook’s distance. Hyperparameter optimization made using the Differential Evolution (DE) method improved the performance of models. …”
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Multi-Agent Coordinated Dispatch of Power Grid and Pumped Hydro Storage with Embedded Market Game Model by LOU Wei, HU Rong, YU Jinming, ZHANG Xipeng, FAN Feilong, LIU Songyuan

“…The test results show that the proposed method can effectively coordinate the decision-making of direct grid dispatching and pumped storage participation in the electric energy spot market, enhancing the economic benefits of pumped storage, reducing the operating cost of the grid, and improving the consumption of renewable energy.…”
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A 5G heterogeneous network deployment strategy for power distribution network by Zhang Ping, Qiu Chao, Zhang Linjuan, Zheng Zheng, Fan Bing, Xin Yanan

“…Simulation results show that TI-BSDS is superior to the comparison algorithms in terms of weighted signal-to-noise ratio and deployment cost, and TI-BSDS can effectively improve the deployment benefit of 5G networks in power distribution networks.…”
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Adaptive Anomaly Detection in Network Flows With Low-Rank Tensor Decompositions and Deep Unrolling by Lukas Schynol, Marius Pesavento

“…An augmentation of the objective is introduced to decrease the computational cost. We apply deep unrolling to derive a novel deep network architecture based on our proposed algorithm, treating the regularization parameters as learnable weights. …”
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Simple and High-Precision Hamiltonian Simulation by Compensating Trotter Error with Linear Combination of Unitary Operations by Pei Zeng, Jinzhao Sun, Liang Jiang, Qi Zhao

“…For the lattice system, the second algorithm can achieve 3 to 4 orders of magnitude higher accuracy with the same gate costs as the optimal Trotter algorithm. …”
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Pig behavior recognition and disease warning based on compressed sensing and long-short term memory network by Ren Wang, Mingdong Zhao

“…By means of ellipse fitting based on the minimum cost function and target tracking based on the shortest distance matching, we design four motion information detection algorithms including motion displacement, motion velocity, motion acceleration and motion angular velocity. …”
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Driving Pattern Analysis, Gear Shift Classification, and Fuel Efficiency in Light-Duty Vehicles: A Machine Learning Approach Using GPS and OBD II PID Signals by Juan José Molina-Campoverde, Juan Zurita-Jara, Paúl Molina-Campoverde

“…Such integration could optimize gear shift timing based on dynamic factors like road conditions, traffic density, and driver behavior, ultimately contributing to improved fuel efficiency and overall vehicle performance.…”
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Methods to Quantitatively Evaluate the Effect of Shale Gas Fracturing Stimulation Based on Least Squares by DENG Cai, SUN Kexin, WEN Huan, HU Chaolang

“…Its significance to the industry lay in addressing the major challenge of the absence of a cost-effective, quantifiable assessment method. It offered detailed insights into the effectiveness of fracturing (in terms of the number and quality of perforations), enabling engineers to improve the fracturing stimulation process for improved production results. …”
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A Hybrid Method Based on the Iterative Fourier Transform and the Differential Evolution for Pattern Synthesis of Sparse Linear Arrays by Xin-Kuan Wang, Gui-Bao Wang

“…Therefore, the SLA with improved sidelobe performance can be obtained at relative low hardware cost. …”
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