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

“…Our improved model achieved the highest detection accuracy of 98.11% compared to other state-of-the-art (SOTA) target detection algorithms. …”
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Adaptive Variational Modal Decomposition–Dual Attention Mechanism Parallel Residual Network: A Tool Lifetime Prediction Method Based on Adaptive Noise Reduction by Jing Kang, Taiyong Wang, Yi Li, Ye Wei, Yaomin Zhang, Ying Tian

“…The method first adapts the parameters of the variational modal noise reduction algorithm using an improved sparrow optimization algorithm, and then reconstructs the original vibration signal with noise reduction. …”
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Intelligent Dual Basal–Bolus Calculator for Multiple Daily Insulin Injections via Offline Reinforcement Learning by Junyoung Yoo, Vega Pradana Rachim, Suyeon Jung, Sung-Min Park

“…By analyzing the control performance metrics of time-in-range (TIR) and time-below-range (TBR) before and after implementing the proposed algorithm, we observed a TIR improvement of 9.7% and a TBR improvement of 1.1% when comparing the proposed algorithm with conventional basal–bolus calculation algorithms. …”
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Power Allocation for 5G Mobile Multiuser Cooperative Networks by Fagen Yin, Wencai Du

“…To solve the optimization problem, we propose an intelligent power allocation optimization algorithm based on grey wolf optimization (GWO). …”
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A Location Selection Policy of Live Virtual Machine Migration for Power Saving and Load Balancing by Jia Zhao, Yan Ding, Gaochao Xu, Liang Hu, Yushuang Dong, Xiaodong Fu

“…We propose a novel approach MOGA-LS, which is a heuristic and self-adaptive multiobjective optimization algorithm based on the improved genetic algorithm (GA). …”
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Design and Implementation of Hybrid GA-PSO-Based Harmonic Mitigation Technique for Modified Packed U-Cell Inverters by Hasan Iqbal, Arif Sarwat

“…This paper proposes a hybrid version of the GA-PSO algorithm that exploits the exploratory strengths of GA and the convergence efficiencies of PSO in determining the optimized switching angles for SHM techniques applied to modified five-level and seven-level PUC inverters. …”
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Robust collaborative mesh networking with large-scale distributed wireless heterogeneous terminals in industrial cyber-physical systems by Tao Wang, Jun Liu, Lianglun Cheng, Hong Xiao

“…Second, the robustness-aware collaborative mesh networking problem is formulated with a multi-objective optimization model, and an improved multi-objective particle swarm optimization algorithm based on self-adaptive evolutionary learning is exploited to search out the Pareto optimal particles with better distribution and diversity. …”
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Robust design of bicycle infrastructure networks by Christoph Steinacker, Mads Paulsen, Malte Schröder, Jeppe Rich

“…Interestingly, while the more complex optimization models yield better overall welfare results, the improvements over simpler methods are small. …”
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A New Method for Solving Supervised Data Classification Problems by Parvaneh Shabanzadeh, Rubiyah Yusof

“…To improve classification performance and efficiency in generating classification model, a new feature selection algorithm based on techniques of convex programming is suggested. …”
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SGO enhanced random forest and extreme gradient boosting framework for heart disease prediction by Anima Naik, Ghanshyam G. Tejani, Seyed Jalaleddin Mousavirad

“…Both models are further optimized through hyperparameter tuning using the Social Group Optimization (SGO) algorithm. …”
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Efficient and Motion Correction-Free Myocardial Perfusion Segmentation in Small MRI Data Using Deep Transfer Learning From Cine Images: A Promising Framework for Clinical Implement... by German Garcia-Jara, Angel Jimenez-Molina, Esteban Reyes, Nicolas Tapia-Rivas, Cristobal Ramos-Gomez, Jose De Grazia, Matias Sepulveda

“…This methodology includes normalization and cropping of cine images using a Region-of-Interest detector based on a Markovian, graph-based visual saliency algorithm improved by a sequence of morphological operations. …”
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Low-Carbon Dispatch Method for Active Distribution Network Based on Carbon Emission Flow Theory by Jiang Bian, Yang Wang, Zhaoshuai Dang, Tianchun Xiang, Zhiyong Gan, Ting Yang

“…Finally, the effectiveness of the proposed model and the superiority of the improved algorithm are demonstrated using a modified IEEE 33-bus distribution network test case.…”
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Multi-Intersection Signal Control Based on Asynchronous Reinforcement Learning by Jixiang Wang, Siqi Chen, Jing Wei, Boao Wang, Haiyang Yu

“…Simulation experiments show that the asynchronous decision-making method proposed in this paper not only improves the model convergence speed by at least 19% compared to the multiagent deep RL (MADRL) algorithm used for synchronous decision-making, but also improves the model by at least 10.5% in vehicle driving speed, maximum queue length, and average queue length within the decodable range (the traffic density is between 100 vehicles/km and 400 vehicles/km). …”
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Two-Sided Matching on Comprehensive Transportation Network Emergency Vehicles’ Allocation by Kunwei Xie, Heying Xu, Hongxia Lv

“…Firstly, based on the needs of both parties involved in the matching, the satisfaction evaluation systems are constructed; with the goal of maximizing the weighted satisfaction of the affected areas and vehicles, the optimization model of the materials and emergency vehicles matching is established; then, an improved National Intern Matching Program (NIMP) algorithm is designed to solve the model, which is based on the k: 1 experimental pairing and updating ideas, and can take into account the capacity and destination constraints of vehicles in the matching process. …”
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An efficient approach for broadband sound absorption using periodic multi-layer solid inclusions in acoustic coatings. by Xiaogang Li, Peng Liu, Xilong Zhang, Xiaoyang Zhu, Hongbo Zhang

“…The optimized structure, featuring subwavelength thicknesses, has significantly improved its sound absorption performance across a wide frequency range spanning from 1780 Hz to 8890 Hz, covering over two octaves. …”
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Intelligent building design based on green and low-carbon concept by Qian Lv

“…The air conditioning system reduced energy consumption by 7238 kWh/month through a load forecasting model. The results showed that the intelligent building energy optimization system established in the study, through multi-system algorithm linkage, improved overall energy efficiency by 23% compared to traditional solutions. …”
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Double-layer energy transaction strategy of multi-microgrids and distribution network with leased shared energy storage by WANG Hui, WU Zuohui, LI Xin, ZOU Zhichao, ZHOU Kerui

“…In profit allocation of microgrid alliance, an asymmetric Nash bargaining method is proposed that fairly distribute profits according to the contribution size of each member in providing energy. Finally, an improved particle swarm optimization algorithm combined with the alternating direction multiplier method is adopted to solve the hybrid game model. …”
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Fault Diagnosis and Data Reconstruction of Temperature Sensors for Wind Turbine Stator Winding by Ling Zhou, Qiancheng Zhao, Jinhui Zeng, Anfeng Zhu, Xiafei Long, Ling He

“…The method combines supervisory control and data acquisition (SCADA) with an improved firefly sparrow search algorithm (FISSA)–optimized deep belief network (DBN). …”
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Tomato Leaf Disease Identification Framework FCMNet Based on Multimodal Fusion by Siming Deng, Jiale Zhu, Yang Hu, Mingfang He, Yonglin Xia

“…Furthermore, to enhance both training efficiency and parameter optimization capabilities of the model, we introduce a Multi-strategy Improved Coati Optimization Algorithm (MSCOA). …”
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A novel method for power transformer fault diagnosis considering imbalanced data samples by Jun Chen, Yong Wang, Lingming Kong, Yilong Chen, Mianzhi Chen, Qian Cai, Gehao Sheng

“…Hyperparameter tuning is achieved through the Bayesian optimization algorithm to identify the model parameter set that maximizes test set accuracy.ResultsAnalysis of the transformer fault case library reveals that the model proposed in this paper reduces diagnostic time by nearly half compared to traditional machine learning diagnosis models. …”
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