Nonlinear Model Predictive Control for Trajectory Tracking of Omnidirectional Robot Using Resilient Propagation by Mahmoud El-Sayyah, Mohamad R. Saad, Maarouf Saad

“…This paper proposes an enhanced Nonlinear Model Predictive Control (NMPC) framework that incorporates a robust, convergent variant of the resilient propagation (RPROP) algorithm to efficiently solve the Nonlinear Optimization Problem (NOP) in real time. …”
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PolicySegNet: a policy-based reinforcement learning framework with pretrained embeddings and transformer decoder for joint brain tumors segmentation and classification in MRI by Vishv Patel, Vandana Patel, Aakash Shinde

“…PolicySegNet uniquely integrates a policy-based reinforcement learning algorithm—specifically proximal policy optimization (PPO)—to jointly optimize the decoder and classifier based on a reward signal that balances segmentation accuracy with classification performance. …”
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Prediction of river dissolved oxygen (DO) based on multi-source data and various machine learning coupling models. by Yubo Zhao, Mo Chen

“…In this study, a hybrid machine learning model for river DO prediction, called DWT-KPCA-GWO-XGBoost, is proposed, which combines the discrete wavelet transform (DWT), kernel principal component analysis (KPCA), gray wolf optimization algorithm (GWO), and extreme gradient boosting (XGBoost). …”
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The balance between traffic control and economic development in tourist cities under the context of COVID-19: A case study of Xi'an, China. by Wang Xiang, Zezhi Wang, Xin Pan, Xiaobing Liu, Xuedong Yan, Li Chen

“…After determining the functional relationship between the control intensity and the number of tourists and the cumulative number of confirmed cases, the NSGA-II algorithm is employed to perform multi-objective optimization with consideration of the requirements for epidemic prevention and control and for economic development to get an appropriate traffic control intensity and suggest scientific traffic control measures. …”
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A novel mechanism-guided residual network for accurate modelling of scroll expander under noisy and sparse data conditions by Xiaoshuang Lv, Xin Ma, Wei Peng, Ke Li, Chengdong Li

“…This framework is based on the architecture of residual network, where the mechanistic laws are embedded as constraints in the training of the network through an improved loss function. Then, a hybrid optimization algorithm is detailed, which can achieve efficient and accurate updating of the parameters of the network and mechanistic equations. …”
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Hyperspectral Imaging for Non-Destructive Moisture Prediction in Oat Seeds by Peng Zhang, Jiangping Liu

“…Bayesian optimization was used for global tuning of network structural parameters, while ASFSSA was applied to fine-tune the initial weights and thresholds, improving convergence efficiency and predictive accuracy. …”
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Vehicle Routing Problem for Collaborative Multidepot Petrol Replenishment under Emergency Conditions by Guangcan Xu, Qiguang Lyu

“…Meanwhile, usage of distribution trucks is optimized in the distribution network, that is, usage of single- and double-compartment trucks is reduced while that of three-compartment trucks is increased. …”
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Design of FPGA-Based Accelerator for Convolutional Neural Network under Heterogeneous Computing Framework with OpenCL by Li Luo, Yakun Wu, Fei Qiao, Yi Yang, Qi Wei, Xiaobo Zhou, Yongkai Fan, Shuzheng Xu, Xinjun Liu, Huazhong Yang

“…Simulation results show that the calculation speed could be improved by adopting the proposed optimizing strategy. …”
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GTrXL-SAC-Based Path Planning and Obstacle-Aware Control Decision-Making for UAV Autonomous Control by Jingyi Huang, Yujie Cui, Guipeng Xi, Shuangxia Bai, Bo Li, Geng Wang, Evgeny Neretin

“…Experimental results in the AirSim drone simulation environment demonstrate that compared to PPO and SAC algorithms, GTrXL-SAC achieves more precise policy exploration and optimization, enabling superior control of drone velocity and attitude for stabilized flight while accelerating convergence speed by nearly 20%.…”
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Energy management in a microgrid equipped with an electric vehicle based on the internet of things considering responsive load by Mohamad Mahdi Erfani Majd, Reza Davarzani, Mahmoud Samiei Moghaddam, Ali Asghar Shojaei, Mojtaba Vahedi

“…A novel Energy-Trading Management Algorithm (ETMA), based on the Meerkat Optimization Algorithm (MOA), is proposed to tackle the complexities of this system. …”
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FPGA Acceleration With Hessian-Based Comprehensive Intra-Layer Mixed-Precision Quantization for Transformer Models by Woohong Byun, Jongseok Woo, Saibal Mukhopadhyay

“…Coupled with the proposed algorithm and dataflow optimization, it enables on-chip storage of all necessary parameters, minimizing off-chip memory access. …”
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Adaptive Multi-Robot Exploration for Unknown Environments Using Edge-Weighted Path Planning by Farhad Baghyari, Tyler Parsons, Jaho Seo, Byeongjin Kim, Mingeuk Kim, Hanmin Lee

“…Experimental results demonstrate that the algorithm achieves improved exploration efficiency and adaptability compared to a real-time scheduling method while maintaining computational feasibility. …”
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Comparative analysis of machine learning models for malaria detection using validated synthetic data: a cost-sensitive approach with clinical domain knowledge integration by Gudi V. Chandra Sekhar, Chekol Alemu

“…While synthetic data enables controlled algorithm comparison, real-world clinical validation remains essential before deployment.…”
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Local Search-Based Metaheuristic Methods for the Solid Waste Collection Problem by Haneen Algethami

“…Local search methods, notably GLS, have significantly improved the route construction process. The nearest neighbour algorithm has often outperformed the Clarke and Wright's methods. …”
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ADAM-DETR: an intelligent rice disease detection method based on adaptive multi-scale feature fusion by Hanyu Song, Xinyue Huang, Ziqiang Wang, Jianwei Hu, Huasheng Zhang, Hui Yang

“…The algorithm requires only 42.8G FLOPs with 14.3M parameters, achieving an optimal balance between accuracy and efficiency, providing an effective technical solution for disease monitoring in smart agriculture.…”
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Continuous Train Positioning Using Visible Light Communication Assisted with Zero Velocity Update by Yanpeng ZHANG, Rongrong ZHANG, Nan MENG, Bingqing ZHANG, Xia XIAO

“…The zero velocity update (ZUPT) algorithm can correct IMU errors by detecting the vehicle’s motion state and attitude angle to improve the accuracy and stability of positioning. …”
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Obstacle Avoidance Control of Autonomous Undersea Vehicle Based on DVFH+ in Ocean Current Environment by Zhongben ZHU, Jiahao ZHANG, Yifan XUE, Hongde QIN

“…Additionally, by considering the drift angle compensation in the real ocean current environment, the obstacle avoidance algorithm was optimized to improve its robustness and adaptability. …”
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Fast Processing of Massive Hyperspectral Image Anomaly Detection Based on Cloud-Edge Collaboration by Yunchang Wang, Jin Sun, Yang Xu, Zhihui Wei, Shangdong Zheng, Zebin Wu

“…With the improvement of hyperspectral image resolution, existing anomaly detection algorithms find it challenging to quickly process large volumes of hyperspectral data while fully exploiting spectral information. …”
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Selection Based on Colony Fitness for Differential Evolution by Zi Ming, Yang Li, Shijie Peng, Xuechao Wu, Jinyi Guo

“…Selection based on the first version of the colony is embodied in DE/rand/1, a basic DE algorithm, while selection based on the second version is used in CoBiDE, a state-of-the-art DE algorithm. …”
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A Design Framework for Scalable and Adaptive Multi-Agent Coordination in Dynamic Environments: Addressing Concurrent Agent and Environment Interactions by Raza Muhammad Kazim, Guoxin Wang, Zhenjun Ming, Jinhui Cao, Janet K. Allen, Farrokh Mistree

“…In this study, we explore the integration of surrogate response surface modeling (SRSM) with optimization algorithms, comparing Stochastic Gradient Descent (SGD) with a fixed learning rate, and adaptive learning rate (ALR) optimizers—including Adaptive Moment Estimation (ADAM) and Adaptive Approximate Direction Method Algorithm (AADMA)—to enhance MAS performance metrics, such as Agent Collision Rate (ACR), Agent Movement Frequency (AMF), and Task Completion Time (TCT). …”
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