COMQ: A Backpropagation-Free Algorithm for Post-Training Quantization by Aozhong Zhang, Zi Yang, Naigang Wang, Yingyong Qi, Jack Xin, Xin Li, Penghang Yin

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Short-Term Load Forecasting Based on Pelican Optimization Algorithm and Dropout Long Short-Term Memories–Fully Convolutional Neural Network Optimization by Haonan Wang, Shan Huang, Yue Yin, Tingyun Gu

“…In order to improve the prediction accuracy of short-term power loads in a power system, this paper proposes a short-term load prediction method (POA-DLSTMs-FCN) based on a combination of multi-layer lost long short-term memory (DLSTM) neural networks, fully convolutional neural networks (FCNs) and the pelican optimization algorithm (POA). …”
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A Multi-Objective Optimization Framework That Incorporates Interpretable CatBoost and Modified Slime Mould Algorithm to Resolve Boiler Combustion Optimization Problem by Shan Gao, Yunpeng Ma

“…In order to solve the above-mentioned problem, a new multi-objective optimization framework that incorporates an interpretable CatBoost model and modified slime mould algorithm is proposed. …”
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Optimal Coordination of Directional Overcurrent Relays Using an Innovative Fractional-Order Derivative War Algorithm by Bakht Muhammad Khan, Abdul Wadood, Herie Park, Shahbaz Khan, Husan Ali

“…This innovative approach integrates the principles of fractional calculus (FC) into the conventional war optimization (WO) algorithm, significantly improving its optimization properties. …”
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The Path Tracking Control of Unmanned Surface Vehicles Based on an Improved Non-Dominated Sorting Genetic Algorithm II-Based Multi-Objective Nonlinear Model Predictive Control Meth... by Yunzhe Guo, Qidan Zhu, Jinyou Mou

“…This paper proposes a multi-objective nonlinear model predictive control (MOMPC) method based on an improved non-dominated sorting genetic algorithm II (NSGAII) for the path tracking problem of unmanned surface vehicles (USVs). …”
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Intelligent Teaching Recommendation Model for Practical Discussion Course of Higher Education Based on Naive Bayes Machine Learning and Improved <i>k</i>-NN Data Mining Algorithm by Xiao Zhou, Ling Guo, Rui Li, Ling Liu, Juan Pan

“…Then, relying on the student grouping, we use the matching features between the students’ interest vector and the practical topic vector to construct an intelligent teaching recommendation model based on an improved <i>k</i>-NN data mining algorithm, in which the optimal complete binary encoding tree for the discussion topic is modeled. …”
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A New Reliability Rock Mass Classification Method Based on Least Squares Support Vector Machine Optimized by Bacterial Foraging Optimization Algorithm by S. Zheng, A. N. Jiang, X. R. Yang, G. C. Luo

“…LSSVM parameters were optimized by the BFOA to form a hybrid BFOA-LSSVM algorithm. …”
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Enhanced skill optimization algorithm: Solution to the stochastic reactive power dispatch framework with optimal inclusion of renewable resources using large‐scale network by Noor Habib Khan, Yong Wang, Raheela Jamal, Sheeraz Iqbal, Mohamed Ebeed, Yazeed Yasin Ghadi, Z. M. S. Elbarbary

“…To avoid stagnation problems in skilled optimization algorithm (SOA), three strategies such as fitness‐distance balance selection, mutation, and gorilla troops‐based approaches are utilized to improve overall strength of SOA. …”
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A Lightweight Algorithm for Detection and Grading of Olive Ripeness Based on Improved YOLOv11n by Fengwu Zhu, Suyu Wang, Min Liu, Weijie Wang, Weizhi Feng

“…To address these limitations, this study proposes a lightweight algorithm for detection and grading of olive ripeness based on an Improved YOLOv11n framework. …”
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Research on Food Image Classification Algorithm based on Improved MobileNetV3-Large by HE Wei-chan, YANG Zhi-jing, QIN Jing-hui

“…In order to address these issues, this paper proposed a food image classification algorithm based on improved MobileNetV3-Large. Firstly, building upon the pre-trained MobileNetV3-Large model, the PReLu activation function and NAM attention mechanism were introduced to enhance the model's focus on key features by capturing non-local dependencies in images. …”
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DV-DETR: Improved UAV Aerial Small Target Detection Algorithm Based on RT-DETR by Xiaolong Wei, Ling Yin, Liangliang Zhang, Fei Wu

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Disease Detection Algorithm for Tea Health Protection Based on Improved Real-Time Detection Transformer by Zhijie Lin, Zilong Zhu, Lingling Guo, Jingjing Chen, Jiyi Wu

“…While the precision improves, the FPS value also increases by 109, which is superior to the traditional model in terms of precision and real-time processing. …”
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Advancing overbreak prediction in drilling and blasting tunnel using MVO, SSA and HHO-based SVM models with interpretability analysis by Yulin Zhang, Jian Zhou, Jialu Li, Biao He, Danial Jahed Armaghani, Shuai Huang

“…To address these limitations, this research proposes three innovative hybrid models that integrate metaheuristic optimization algorithms with support vector machine (SVM): multi-verse optimizer-SVM (MVO-SVM), salp swarm algorithm-SVM (SSA-SVM), and Harris’s Hawk optimization-SVM (HHO-SVM). …”
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Human resource management model based on multi-objective differential evolution and multi-skill scheduling by Yanxia Dong, Tiantian Lu

“…This study proposes an innovative human resource management model that integrates multi-objective differential evolution algorithm and learning curve model, and adopts a multidimensional chromosome encoding scheme for multi skill scheduling. …”
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UWB Base Station Deployment Optimization Method Considering NLOS Effects Based on Levy Flight-Improved Particle Swarm Optimizer by Shengliang Wang, Ming Gao, Ling’ai Li, Dong Lv, Yingqi Li

“…In this paper, we propose a new UWB BS deployment optimization method that takes into account the influence of NLOS occlusion, determines the BS deployment range and occlusion by indoor map information, uses the locatable points coverage rate in the whole indoor positioning area as the fitness function, and proposes an improved particle swarm optimization algorithm based on the Levy flight strategy (LPSO) to solve the optimization problem. …”
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Multi-Factor Optimization and Failure-Tolerant Design of Cable-Driven Parallel Manipulators in Deep-Sea Robotics by Asim Ghaffar, Muhammad Zia Ur Rahman, Victor Leiva, Cecilia Castro, Carlos Martin-Barreiro

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Improved UAV Target Detection Model for RT-DETR by Yong He, Yufan Pang, Guolin Ou, Renfeng Xiao, Yifan Tang

“…In light of the shortcomings pertaining to UAV small target detection, the detection of complex scenes, and the detection of multi-scale targets, a time-frequency dual-domain feature extraction algorithm, TF-DETR, has been proposed. This algorithm has been optimized for RT-DETR.Firstly, a time-frequency domain feature extraction module, TF-CSPNet, has been introduced into the backbone network. …”
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Mobile Robot Path Planning Based on Enhanced Dynamic Window Approach and Improved A∗ Algorithm by Hongxia Yang, Xingqiang Teng

“…In the improved A∗ algorithm, in order to improve the algorithm efficiency, so that a single planning path can pass through multiple target points, the search point selection strategy and evaluation function are optimized. …”
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Access selection algorithm for heterogeneous wireless network based on DA optimized fuzzy neural network by Zhihong QIAN, Yinuo FENG, Jiani SUN, Xue WANG

“…To solve the access selection problem of heterogeneous wireless network, an access selection algorithm based on dragonfly algorithm (DA) optimized fuzzy neural network (FNN) was proposed, considering the user’s business type and network state.In view of the low convergence speed of the fuzzy neural network, the dragonfly algorithm was used to optimize the membership function parameters of the second and fifth layers of the fuzzy neural network, so as to obtain the initial value of membership function parameters of the fuzzy neural network.The most suitable network was selected for the users according to their preference to the network and the output score of the network under different business types.The experimental results show that dragonfly algorithm optimization can improve the convergence speed of fuzzy neural network, improve system throughput, reduce blocking rate, and reduce switching times to some extent.…”
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Access selection algorithm for heterogeneous wireless network based on DA optimized fuzzy neural network by Zhihong QIAN, Yinuo FENG, Jiani SUN, Xue WANG

“…To solve the access selection problem of heterogeneous wireless network, an access selection algorithm based on dragonfly algorithm (DA) optimized fuzzy neural network (FNN) was proposed, considering the user’s business type and network state.In view of the low convergence speed of the fuzzy neural network, the dragonfly algorithm was used to optimize the membership function parameters of the second and fifth layers of the fuzzy neural network, so as to obtain the initial value of membership function parameters of the fuzzy neural network.The most suitable network was selected for the users according to their preference to the network and the output score of the network under different business types.The experimental results show that dragonfly algorithm optimization can improve the convergence speed of fuzzy neural network, improve system throughput, reduce blocking rate, and reduce switching times to some extent.…”
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