Real-time urban regional route planning model for connected vehicles based on V2X communication by Pangwei Wang, Hui Deng, Juan Zhang, Mingfang Zhang

“…Second, according to the topology structure of the current regional road network, all predicted routes are listed based on the Dijkstra algorithm. Third, the predicted travel time of each alternative route is calculated, while the predicted route with the least travel time is selected as the optimal route. …”
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Rethinking Exploration and Experience Exploitation in Value-Based Multi-Agent Reinforcement Learning by Anatolii Borzilov, Alexey Skrynnik, Aleksandr Panov

“…We aim to optimize a deep MARL algorithm with minimal modifications to the well-known QMIX approach. …”
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Assigning Priorities for Fixed Priority Preemption Threshold Scheduling by Saehwa Kim

“…Based on the developed theorems, we correct the previously proposed optimal priority assignment algorithm for PTS. We also propose a performance improved optimal priority assignment algorithm for PTS proving its optimality. …”
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Retracted: Computer Medical Image Segmentation Based on Neural Network by Xiaopeng Wang, Lei Gu, Zhongyi Wang

“…This article proposes an image segmentation method based on an optimized cellular neural network. This method introduces a non-linear template and data quantization on the basis of a basic network model, which greatly reduces the computational complexity while maintaining the accuracy of image segmentation. …”
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MAOOA‐Residual‐Attention‐BiConvLSTM: An Automated Deep Learning Framework for Global TEC Map Prediction by Haoran Wang, Haijun Liu, Jing Yuan, Huijun Le, Weifeng Shan, Liangchao Li

“…Optimization can help find a better quasi‐optimal hyperparameter combination and improve the performance of the model. …”
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Multi-Feature Long Short-Term Memory Facial Recognition for Real-Time Automated Drowsiness Observation of Automobile Drivers with Raspberry Pi 4 by Michael Julius R. Moredo, James Dion S. Celino, Joseph Bryan G. Ibarra

“…Through algorithm optimization, dataset expansion, and the integration of additional features and feedback mechanisms, the model can be improved in terms of performance and reliability.…”
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Quantum circuit unoptimization by Yusei Mori, Hideaki Hakoshima, Kyohei Sudo, Toshio Mori, Kosuke Mitarai, Keisuke Fujii

“…In this paper, we define and construct a quantum algorithmic primitive called quantum circuit unoptimization, which makes a given quantum circuit complex by introducing some redundancies while preserving circuit equivalence, i.e., the inverse operation of circuit optimization. …”
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GYS-RT-DETR: A Lightweight Citrus Disease Detection Model Based on Integrated Adaptive Pruning and Dynamic Knowledge Distillation by Linlin Yang, Zhonghao Huang, Yi Huangfu, Rui Liu, Xuerui Wang, Zhiwei Pan, Jie Shi

“…Secondly, the model adopts two model optimization strategies: (1) The Group_taylor local pruning algorithm is used to reduce memory occupation and the number of computing parameters of the model. (2) The feature-logic knowledge distillation framework is proposed and adopted to solve the problem of information loss caused by the structural difference between teachers and students, and to ensure a good detection performance, while realizing the lightweight character of the model. …”
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CFTformer: End-to-End Cross-Frame Multi-Object Tracking With Transformer by Abdollah Amirkhani, Seyed Alireza Khoshnevis

“…Overall, the model was able to achieve 1.7% and 0.6% improvement in the identification F1 score (IDF1) metric on MOT17 and MOT20 datasets while having ~0-15% lower number of identity switches, compared to other transformer-based approaches. …”
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Adaptive enhancement of shoulder x-ray images using tissue attenuation and type-II fuzzy sets. by Qifeng Liu, Yong Han, Lu Shen, Jialei Du, Marzia Hoque Tania

“…The method integrates automatic tissue attenuation techniques, which enhance the image contrast by removing non-essential tissue components while preserving important tissues and bones. Additionally, we apply an improved Type-II fuzzy set algorithm to further optimize image sharpness. …”
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Reinforcement learning-based assimilation of the WOFOST crop model by Haochong Chen, Xiangning Yuan, Jian Kang, Danni Yang, Tianyi Yang, Xiang Ao, Sien Li

“…Our results demonstrate that the Time-Series Driven RL model achieved assimilation accuracy comparable to the SUBPLEX optimization algorithm, with an average MAE of 0.65 compared to 0.76 for SUBPLEX, and a slight decrease in RMSE, while significantly reducing the computational burden by 365 times. …”
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Consider the master-slave game model of integrated energy system with step carbon trading and demand response by Yi Zhang, Zhezhou Zhang

“…A stepped carbon pricing mechanism is introduced to constrain the carbon emissions of each entity, while comprehensive demand response is introduced on the user side to improve user economic benefits and energy use comfort. …”
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RIM-Net: A Real-Imaginary-Magnitude Network for NLOS/LOS Identification in UWB Indoor Positioning Systems by Jiacheng Ni, Fang Li, Shuai Cao, Linsong Li

“…Furthermore, the optimization of the TOA algorithm validated the effectiveness of RIM-Net in localization, achieving an average performance improvement of 9.66%. …”
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A model predictive control method for directional borehole trajectories in underground coal mines by Hao LI, Ningping YAO, Chengda LU, Jinbao ZHANG, Hongchao WEI, Jiajun WU, Jinyu LI

“…Compared to the human experience-controlled decision-making method based on the deflection rules of a screw drill, the improved MPC method reduces the average absolute errors of the dip angle and azimuth by 79.5% and 70.5%, respectively, providing a novel control algorithm for directional borehole trajectories in complex strata.…”
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Effect of Voltage Dependent Load Model on Placement and Sizing of Distributed Generator in Large Scale Distribution System by Gopisetti Manikanta, Ashish Mani, Hemender Pal Singh, Devendra Kumar Chaturvedi

“…In addition to AQiEA, four other algorithms (Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Grey Wolf Optimization (GWO), and Ecogeography-based Optimization (EBO) with Classification based on Multiple Association Rules (CMAR)) have also been employed for comparison. …”
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Deep knowledge tracing and cognitive load estimation for personalized learning path generation using neural network architecture by Chunyan Tong, Changhong Ren

“…A dual-objective optimization algorithm balances knowledge acquisition with cognitive load management to generate paths that maintain optimal challenge levels. …”
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Energy-Efficient Secure Cell-Free Massive MIMO for Internet of Things: A Hybrid CNN–LSTM-Based Deep-Learning Approach by Ali Vaziri, Pardis Sadatian Moghaddam, Mehrdad Shoeibi, Masoud Kaveh

“…Additionally, a multi-objective improved biogeography-based optimization (MOIBBO) algorithm is utilized to optimize hyperparameters, ensuring an improved balance between convergence speed and model performance. …”
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PID Control and Input Shaping for Quadrotor UAV Stabilization and Payload Swing Reduction by Liyana Ramli, Izzuddin M. Lazim, Amalin Aisya Awi, Aina Syazwin Shukor

“…To enhance swing suppression, the input shaper parameters are optimized using the Particle Swarm Optimization (PSO) algorithm. …”
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DLML-PC: an automated deep learning and metric learning approach for precise soybean pod classification and counting in intact plants by Yixin Guo, Jinchao Pan, Xueying Wang, Hong Deng, Hong Deng, Mingliang Yang, Mingliang Yang, Enliang Liu, Qingshan Chen, Qingshan Chen, Rongsheng Zhu, Rongsheng Zhu

“…By improving the Siamese Network in metric learning, the optimal Siamese Network model was obtained. …”
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Fairness-Aware Computation Offloading for Mobile Edge Computing With Energy Harvesting by Dedi Triyanto, I. Wayan Mustika, Widyawan, Praphan Pavarangkoon

“…This research formulates the Fairness-aware Computation Offloading Optimization (FACOO) algorithm. The Lyapunov approach and sequential least squares quadratic programming (SLSQP) are used to ascertain the best offloading ratio, transmission power, and CPU frequency while complying with signal-to-interference-plus-noise ratio (SINR) limitations. …”
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