Optimization of surgical treatment of abdominal hernias in patients with obesity by V. I. Belokonev, V. P. Zakharov, D. B. Grachev, S. Y. Pushkin, Z. V. Kovaleva, D. S. Pushkina

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Control Optimization of Steam Boilers via Reinforcement Learning by Emmanuel Okafor, Maad Alowaifeer

“…Extensive experimental validation confirms the superiority of hybrid controllers, achieving significantly faster settling times, peak overshoot reductions to <inline-formula> <tex-math notation="LaTeX">$(\leq 2\%)$ </tex-math></inline-formula>, and lower error metrics than MRAC alone. While optimized PID serves as a baseline, hybrid controllers consistently achieve faster settling times and improved robustness under most nonlinear operating conditions. …”
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An efficient fire detection algorithm based on Mamba space state linear attention by Yuming Li, Yongjie Wang, Xiaorui Shao, Anbo Zheng

“…Instead, it performs dimensionality reduction on input features through adaptive average pooling and utilizes the state update mechanism of the SSM module to significantly enhance feature representation and optimize information flow. Second, to address the limitations of SSM models in local feature modeling, this study incorporates the ConvNeXtV2 module to optimize the backbone network, improving the model’s ability to capture fine-grained local details and thereby strengthening its overall representation capability. …”
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Carbon emission forecasting in Zhejiang Province based on LASSO algorithm and grey model by HONG Jingke, DU Wei, SHAO Jin*, LAO Huimin

“…In light of these findings, It is recommended that Zhejiang Province should focus on optimizing its industrial structure, improving energy efficiency, increasing investment in low-carbon research and development, and steadily advancing the goal of "carbon peaking" .…”
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Multivariate machine learning algorithms for energy demand forecasting and load behavior analysis by Farhan Hussain, M. Hasanuzzaman, Nasrudin Abd Rahim

“…This article presents deep learning frameworks for predicting electricity demand in the Western region of Bangladesh, utilizing Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithms. Critical hyperparameters, such as the number of hidden neurons in ANN and the number of input membership functions in ANFIS, are optimized to effectively capture uncertainties in load patterns. …”
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Research on a traffic flow statistical algorithm based on YBOVDT and SAM2 by Yuanyuan Wang, Zheng Ding, Jiange Liu, Kexiao Wu, Md Sharid Kayes Dipu, Tingmei Ma, Yonghao Ma, Haiyan Zhang

“…A comparative analysis with YOLO-v3,YOLO-v5, YOLO-v6,and YOLO-v8 algorithms indicated that, while balancing spatial and temporal resource consumption and accuracy, the proposed algorithm offers higher recognition accuracy and environmental adaptability. …”
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CKRT coagulation risk prediction and nursing feedback model based on intelligent algorithms by Xianrong Xu, Mou Chen, Lvjing Chen, Kaixing Huang, Shiqi Cao, Wenwen Gao, Kang Liu, Buyun Wu, Huijuan Mao

“…Conclusion The intelligent Continuous Kidney Replacement Therapy nursing feedback model improves prediction accuracy while reducing redundant information. …”
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Enhancing Camera Source Identification: A Rapid Algorithm with Enhanced Discriminative Power by Zhimao Lai, Lijuan Cheng, Renhai Feng

“…Compared to the traditional brute-force search algorithm (BFSA), our method significantly reduces computational complexity in large-scale databases, optimizing from <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>O</mi><mo>(</mo><mi>n</mi><mi>N</mi><mo>)</mo></mrow></semantics></math></inline-formula> to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>O</mi><mo>(</mo><mi>n</mi><mo form="prefix">log</mo><mi>N</mi><mo>)</mo></mrow></semantics></math></inline-formula>, where <i>n</i> is the length of the fingerprint, and <i>N</i> is the number of fingerprints in the database. …”
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A New Approach to Circulatory System-Based Optimization for the Shape and Sizing Design of Truss Structures by Ibrahim Behram Ugur, Sadik Ozgur Degertekin

“…This paper presents a new approach to the circulatory system-based optimization algorithm called NCSBO. The proposed method incorporates an adaptive parameter-tuning strategy and a refined mutation approach to improve the performance of optimizing the shape and size of truss structures. …”
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Signal Timing Optimization Model for Intersections in Traffic Incidents by Jiawen Wang, Jiayu Hang, Xizhao Zhou

“…The proposed method is capable of improving the signalized intersection throughput while preventing the congestion from spreading to the upstream intersection.…”
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Social Media Users' Expression, Formation Mechanism, and Coping Strategies for Algorithm Aversion by Yan MOU

“…These insights are invaluable for improving and optimizing algorithms to ensure that they not only meet user expectations, but also enhance their overall experience and satisfaction. …”
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Engine Optimization Model for Accurate Prediction of Friction Model in Marine Dual-Fuel Engine by Mina Tadros

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Research on Sparse Code Multiple Access Detection Technology in Satellite Communication Systems by Yiting JIANG, Lidong ZHU

“…SCMA detection algorithms in the satellite communication system was studied,and optimal allocation of codebook and the incomplete iterative MPA detection algorithm were combined to improve system performance while reducing system complexity.The convergence of the SCMA detection algorithm was studied,and an improved serial-parallel MPA algorithm was proposed.This algorithm could accelerate the system convergence speed while reducing the processing delay,and the system complexity was also reduced.…”
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Machine Learning for Decision Support and Automation in Games: A Study on Vehicle Optimal Path by Gonçalo Penelas, Luís Barbosa, Arsénio Reis, João Barroso, Tiago Pinto

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Hybrid Estimation of Distribution Algorithm for Solving Three-Stage Multiobjective Integrated Scheduling Problem by Chao Deng, Rong Hu, Bin Qian, Huai P. Jin

“…A variable neighborhood hybrid operation based on the speed scheduling set is designed in Local Search II to further improve the quality of the solution while balancing the optimization goals. …”
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Joint user association and dynamic resource allocation algorithm for LEO-RAN slicing scenarios by Geng CHEN, Zhiwei XING, Fei SHEN, Qingtian ZENG

“…A joint user association and dynamic resource allocation algorithm was proposed for the slicing scenario of ultra dense low earth orbit-radio access network (LEO-RAN) in order to address the efficient utilization of resources of the integrated terrestrial-satellite network for 6G .Considering the constraints of the minimum rate, maximum delay and resource proportion of different slices, a joint optimization problem of user association and resource allocation was established to maximize the weighted sum of the SE and the differentiated SLA of different slices as the optimization objective.A network slicing algorithm based on multi-agent deep deterministic policy gradient (MADDPG) was proposed to determine the proportion of slicing resources, a Lagrange dual based user association algorithm was proposed to determine the optimal user association policy and the resources were allocated to users by using the round-robin scheduling mechanism.The simulation results show that the proposed algorithm can effectively improve SE while satisfying the differentiated SLA of different slices.Compared with MADDPG-RA, MATD3-LG, MATD3-RA, MASAC-LG and MASAC-RA algorithms, the system utility of the proposed algorithm is improved by 2.0%, 2.3%, 5.7%, 8.7% and 9.4%, respectively.…”
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Joint user association and dynamic resource allocation algorithm for LEO-RAN slicing scenarios by Geng CHEN, Zhiwei XING, Fei SHEN, Qingtian ZENG

“…A joint user association and dynamic resource allocation algorithm was proposed for the slicing scenario of ultra dense low earth orbit-radio access network (LEO-RAN) in order to address the efficient utilization of resources of the integrated terrestrial-satellite network for 6G .Considering the constraints of the minimum rate, maximum delay and resource proportion of different slices, a joint optimization problem of user association and resource allocation was established to maximize the weighted sum of the SE and the differentiated SLA of different slices as the optimization objective.A network slicing algorithm based on multi-agent deep deterministic policy gradient (MADDPG) was proposed to determine the proportion of slicing resources, a Lagrange dual based user association algorithm was proposed to determine the optimal user association policy and the resources were allocated to users by using the round-robin scheduling mechanism.The simulation results show that the proposed algorithm can effectively improve SE while satisfying the differentiated SLA of different slices.Compared with MADDPG-RA, MATD3-LG, MATD3-RA, MASAC-LG and MASAC-RA algorithms, the system utility of the proposed algorithm is improved by 2.0%, 2.3%, 5.7%, 8.7% and 9.4%, respectively.…”
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Optimization of PID Controllers Using Groupers and Moray Eels Optimization with Dual-Stream Multi-Dependency Graph Neural Networks for Enhanced Dynamic Performance by Vaishali H. Kamble, Manisha Dale, R. B. Dhumale, Aziz Nanthaamornphong

“…Additionally, it minimizes overshoot to 1.5% and reduces the steady-state error to just 0.005 V, demonstrating superior accuracy and efficiency compared to existing methods. These improvements demonstrate the system’s ability to deliver optimal performance while effectively adapting to dynamic environments, showcasing its superiority over existing techniques.…”
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Nonlinear waveform optimization for wireless power transfer systems by Lina Yuan, Huajun Chen, Maoxue Hu, Jing Gong

“…We develop single-user and multi-user algorithms that maximize the output DC voltage of the weighted and/or minimum moment antennas by optimizing waveform design. …”
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Performance assessment of basalt fibre concrete under freeze-thaw cycles using hybrid long short-term memory models by Qingguo Yang, Honghu Wang, Qigui Yi, Liuyuan Zeng, Rui Xiang, Longfei Guan, Jiawei Cheng, Keling Chen, Yunhao Li

“…The two modified particle swarm optimization algorithms showed notable improvements: AsyLnCPSO performed well on the training set but exhibited limited adaptability to overall data variations, while the GA-HIDMS-PSO excelled in high-dimensional and complex constraint problems, demonstrating the strongest stability with a fitting accuracy of 0.938, significantly improving the prediction accuracy of concrete performance under FTCs. …”
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