Lightweight coal mine conveyor belt foreign object detection based on improved Yolov8n by Jierui Ling, Zhibo Fu, Xinpeng Yuan

“…Abstract To resolve the drawbacks of slow speed, excessive parameters, and high computational demands associated with deep learning-based conveyor belt foreign object detection methods, a lightweight algorithm for detecting foreign objects on conveyors based on an improved Yolov8n model is proposed. …”
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Construction of an oligometastatic prediction model for nasopharyngeal carcinoma patients based on pathomics features and dynamic multi-swarm particle swarm optimization support ve... by Yunfei Li, Dongni Zhang, Yiren Wang, Yiren Wang, Yiheng Hu, Zhongjian Wen, Zhongjian Wen, Cheng Yang, Ping Zhou, Wen-Hui Cheng

“…ObjectiveThis study aimed to develop a risk prediction model for post-treatment oligometastasis in nasopharyngeal carcinoma (NPC) by integrating pathomics features and an improved Support vector machine (SVM) algorithm, offering precise early decision support.MethodsThis study retrospectively included 462 NPC patients, without or with oligometastasis defined by ESTRO/EORTC criteria. …”
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Tackling Blind Spot Challenges in Metaheuristics Algorithms Through Exploration and Exploitation by Matej Črepinšek, Miha Ravber, Luka Mernik, Marjan Mernik

“…Furthermore, evaluations on standard benchmarks without blind spots, such as CEC’15 and the soil model problem, confirm that LTMA+ maintains strong optimization performance without introducing significant computational overhead.…”
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An adaptive hybrid framework for IIoT intrusion detection using neural networks and feature optimization using genetic algorithms by Mohammad Zubair Khan, Aijaz Ahmad Reshi, Shabana Shafi, Ibrahim Aljubayri

“…Additionally, Genetic Algorithms were employed to optimize feature selection, further refining the ANN’s input space to improve computational efficiency without sacrificing predictive power. …”
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Lightweight and Efficient CSI-Based Human Activity Recognition via Bayesian Optimization-Guided Architecture Search and Structured Pruning by Sungkwan Youm, Sunghyun Go

“…Experimental results across multiple benchmark datasets demonstrate that our method not only maintains but often improves accuracy after pruning, resulting in models that are both smaller and more accurate. …”
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Direct methanol fuel cells parameter identification with enhanced algorithmic technique by Manish Kumar Singla, Muhammed Ali S.A, Ramesh Kumar, Hamed Zeinoddini-Meymand, Farhad Shahnia

“…The parameter of a direct methanol fuel cell (DMFC) can be identified using optimization techniques to determine the optimal unknown parameter values that are needed for creating an accurate fuel cell performance prediction model. …”
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An enhanced multi-objective reactive power dispatch for hybrid Wind-Solar power system using Archimedes optimization algorithm by Prisma Megantoro, Syahirah Abd Halim, Nor Azwan Mohamed Kamari, Lilik Jamilatul Awalin, Ramizi Mohamed, Hazwani Mohd Rosli

“…This paper proposes a solution to the ORPD problem in systems with RE-DG integration using the Archimedes Optimization Algorithm (AOA). The uncertainties of wind and solar power generation were modelled using Weibull and lognormal probability density functions (PDFs), respectively, and the optimization model was tested using a scenario-based method. …”
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Smart village construction and college students’ skills entrepreneurship path based on LSTM and simulated annealing algorithm by Xueli Dong

“…At the same time, in order to improve the success rate and profitability of college students’ skill entrepreneurship projects, a series of simulation experiments were carried out with the help of simulated annealing algorithm, and an optimal path taking into account costs and benefits was determined through the simulation and comparison of different entrepreneurial models. …”
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Land Use Structure Optimization in Rail Transit Station Area under TOD (Transit Oriented Development) Mode by HE Jun, WANG Junfeng, ZHANG Dongchi

“…The rationality of optimized land use structure in rail transit station area has been improved, and the the proportion of each land type has been adjusted steadily, verifying the good applicability of the model and its effectiveness for land use structure optimization in rail transit station area.…”
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Enhanced prediction of heating value of municipal solid waste using hybrid neuro-fuzzy model and decision tree-based feature importance assessment by Oluwatobi Adeleke, Obafemi O. Olatunji, Tien-Chien Jen, Iretioluwa Olawuyi

“…Moreover, understanding the relative importance and contribution of different waste properties to HHV prediction is critical for improving the model's predictive capability and optimizing the waste-to-energy (WTE) process. …”
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Optimal Coverage Path Planning for Unmanned Surface Vehicles Using Flexible Formation Tracking Control by Minsung Park, Bo Woo Nam

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Research on Sensitivity Improvement Methods for RTD Fluxgates Based on Feedback-Driven Stochastic Resonance with PSO by Rui Wang, Na Pang, Haibo Guo, Xu Hu, Guo Li, Fei Li

“…Simulink is used to construct the sensor model of odd polynomial feedback control, and the Particle Swarm Optimization (PSO) algorithm is used to optimize the coefficients of the feedback function so that the sensor reaches a resonance state, thus reducing the noise interference and improving the sensitivity of the sensor. …”
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Adversarial Reinforcement Learning-Based Converged Communication Efficiency Improvement Method for Power Distribution Network by Linyu PENG, Xu LIU, Wei TANG, Qing LIU, Hao FANG, Guanghui ZHANG

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Coal-rock interface real-time recognition based on the improved YOLO detection and bilateral segmentation network by Shuzhan Xu, Wanming Jiang, Quansheng Liu, Hongsheng Wang, Jun Zhang, Jinlong Li, Xing Huang, Yin Bo

“…To improve the accuracy and efficiency of coal-rock interface recognition, this study proposes a model built on the real-time detection algorithm, you only look once (YOLO), and the lightweight bilateral segmentation network. …”
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Bi-objective optimization of magnetic core loss and magnetic energy transfer of magnetic element based on a hybrid model integrating GAN and NSGA-II by Xiaoyan Shen, Hongkui Zhong, Haixin Wu, Yaqian Mao, Ruiqing Han

“…Furthermore, a comparison with the NSGA-II algorithm is conducted to verify the efficiency of the bi-objective optimization model.…”
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Shape Optimization of Multi-chamber Acoustical Plenums Using the BEM, Neural Networks, and the GA Method by Ying-Chun CHANG, Ho-Chih CHENG, Min-Chie CHIU, Yuan-Hung CHIEN

“…The results reveal that the maximum value of the transmission loss (TL) can be improved at the desired frequencies. Consequently, the algorithm proposed in this study can provide an efficient way to develop optimal multi-chamber plenums for industry.…”
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A Prescriptive Approach Based on Fuzzy Cognitive Maps and Genetic Algorithms for Disease Management in Beef Production by Rodrigo Garcia, Jose Aguilar, Angel Pinto, William Hoyos

“…The prescriptive model yielded high performance with average <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> values above 0.93 and low RMSE values, demonstrating that the recommended treatments closely matched the optimal solutions. …”
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RON‐based cross‐chain routing optimization strategy in metaverse by Junjie Huang, Liang Tan, Jianmei Xiao

“…The current cross‐chain communication mode is dominated by direct‐connect routing, leading to network congestion and high propagation delay once the direct‐connect link fails and cannot be recovered quickly. To optimize direct‐connect routing, this paper proposed a cross‐chain routing optimization strategy based on RON (Resilient Overlay Network), that is, Cross‐Chain_RON, which firstly applies RON to reconstruct the direct‐connect routing model, and then selects the optimal link through the shortest‐path algorithm and policy routing, and combines with the RON performance database to improve the data transmission efficiency. …”
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Preamble Allocation and Access Delay Reduction for Improved Massive Random Access in 5G Beamforming Networks by Gangwoo Lee, Jaewook Jung, Jong-Moon Chung

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Bayesian-optimized ensemble deep learning models for demand forecasting in the volatile situations: A case study of grocery demand during Covid-19 outbreaks by Nader AL Theeb, Hazem Smadi, Naser Al-qaydeh

“…Furthermore, using BO algorithm for hyperparameters tuning improved the forecasting accuracy. …”
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