Rethinking Exploration and Experience Exploitation in Value-Based Multi-Agent Reinforcement Learning by Anatolii Borzilov, Alexey Skrynnik, Aleksandr Panov

“…In this paper, we focus on the exploration problem inherent in many MARL algorithms. These algorithms often introduce new hyperparameters and incorporate auxiliary components, such as additional models, which complicate the adaptation process of the underlying RL algorithm to better fit multi-agent environments. …”
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Machine learning analysis of pharmaceutical cocrystals solubility parameters in enhancing the drug properties for advanced pharmaceutical manufacturing by Tareq Nafea Alharby, Bader Huwaimel

“…Abstract A new computational framework based on machine learning was developed for prediction of Hansen solubility parameters in preparation of pharmaceutical cocrystals with improved properties. The models of Kernel Ridge Regression (KRR), Multi-Linear Regression (MLR), and Orthogonal Matching Pursuit (OMP) were optimized in prediction of three Hansen solubility parameters. …”
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Research on RF Intensity Temperature Sensing based on 1D-CNN by DING Meiqi, GUI Lin, WANG Ziyi, SHANG Disen, QIAN Min, LI Qiankun

“…The model is trained with the training set data and validated with the test set data to optimize the model parameters for optimal performance. …”
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Safety helmet detection methods in heavy machinery factory by Liu Baoju, Wei Xiangqian, Chen Qingshan, Liu Jiaqi, Chen Ye, Yu Peng, Lei shi, Hu Yongfeng

“…When compared with mainstream object recognition algorithms such as SSD, Faster RCNN, and various YOLO versions, the optimized model shows its superiority. …”
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A Hotspot Prediction Scheme Based on Ensemble Learning With Adaptive Beamforming for Virtual Small Cell in 5G Networks by Aws Majeed Ghalib Alawadi, Hadi Seyedarabi, Reza Afrouzian, Javad Musevi Niya

“…For this purpose, at first, using the location map of users, the location of hotspots is predicted by an Ensemble deep learning algorithm. Ensemble deep learning algorithm in this research combines the advantages of GRU and GRN networks and creates an efficient and accurate deep model that is more accurate than previous approaches that used single networks. …”
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I-YOLOv11n: A Lightweight and Efficient Small Target Detection Framework for UAV Aerial Images by Yukai Ma, Caiping Xi, Ting Ma, Han Sun, Huiyang Lu, Xiang Xu, Chen Xu

“…While significantly reducing the model size (parameter 3.87 M, calculation 14.7 GFLOPs), the detection accuracy of small targets is effectively maintained and improved. …”
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Traffic light detection and recognition based on deep learning for autonomous-rail rapid tram by XIONG Qunfang, LIN Jun, YUAN Xiwen, XU Yanghan, YUE Wei, LI Yuanzhengyu

“…In order to further enhance the model's generalization performance, an image diagnosis algorithm was introduced before signal recognition, which generates warnings for complex conditions, such as overexposure and backlighting. …”
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Automatic Quality Assessment of Speech-Driven Synthesized Gestures by Zhiyuan He

“…At the same time, in terms of performance, the model has an improvement of about 20% compared to before the algorithm adjustment.…”
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Identification of Maize Kernel Varieties Using LF-NMR Combined with Image Data: An Explainable Approach Based on Machine Learning by Chunguang Bi, Xinhua Bi, Jinjing Liu, He Chen, Mohan Wang, Helong Yu, Shaozhong Song

“…Subsequently, LF-NMR features and image morphological data were integrated to construct a classification model and the SVM hyperparameters were optimized using an improved differential evolution algorithm, achieving a final classification accuracy of 96.36%, which demonstrated strong robustness and precision. …”
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Ecological and Real-Time Route Selection Method for Multiple Vehicles in Urban Road Network by Liping Yan, Yue Tang, Chan Peng, Yu Cai, Wenbo Zhang, Jing Wang

“…Compared with three non-negotiated optimization algorithms based on swarm technology, EMR2SM is verified by experiments that it improves the efficiency and accuracy of the optimal route selection for multiple vehicles and reduces vehicle emissions, which can effectively reduce traffic congestion and environmental pollution.…”
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A Real-Time Signal Measurement System Using FPGA-Based Deep Learning Accelerators and Microwave Photonic by Longlong Zhang, Tong Zhou, Jie Yang, Yin Li, Zhiwen Zhang, Xiang Hu, Yuanxi Peng

“…The results show that the time of inference saves 28–31% for the DNN model and 71–73% for the LSTM + DNN model compared to running on graphic processing unit (GPU). …”
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Economic sizing and placement of hydrogen fueling and electric vehicles charging stations powered by renewable and battery systems in smart distribution network by Mehdi Veisi

“…The solution is derived using Benders decomposition algorithm to achieve optimal results. The primary innovation highlighted in this paper includes integrating renewable resources and battery systems to power the refueling station, leveraging reactive power control for improved station performance, and addressing both operational and economic objectives in the distribution system. …”
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Securing federated learning: a defense strategy against targeted data poisoning attack by Ansam Khraisat, Ammar Alazab, Moutaz Alazab, Tony Jan, Sarabjot Singh, Md. Ashraf Uddin

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A Study on Vector-Based Processing and Texture Application Techniques for 3D Object Creation and Visualization by Donghwi Kang, Jeongyeon Kim, Jongchan Lee, Haeju Lee, Jihyeok Kim, Jungwon Byun

“…In this research, data weight reduction, parallel processing, and polygon simplification algorithms were applied to optimize the 3D model generation speed. …”
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Expected Length of the Shortest Path of the Traveling Salesman Problem in 3D Space by Hongtai Yang, Xiaoqian Lu, Xinan Zhou, Rong Zheng, Yugang Liu, Siyu Tao

“…Under each scenario, the specified number of demand points is randomly generated, and an improved genetic algorithm and Gurobi are used to find the shortest path. …”
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Green and Reliable Freight Routing Problem in the Road-Rail Intermodal Transportation Network with Uncertain Parameters: A Fuzzy Goal Programming Approach by Yan Sun

“…The reliability of the routing is improved by modeling the uncertainty of the road-rail intermodal transportation network. …”
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Intra-day dispatch method via deep reinforcement learning based on pre-training and expert knowledge by Yanbo Chen, Qintao Du, Huayu Dong, Tao Huang, Jiahao Ma, Zitao Xu, Zhihao Wang

“…In recent years, due to high self-learning and self-optimization ability, reinforcement learning has emerged in the field of economic dispatch, which can solve model-free dynamic programming problems that cannot be effectively solved by traditional optimization methods. …”
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The artificial intelligence-based agricultural field irrigation warning system using GA-BP neural network under smart agriculture. by Xiying Wang

“…To address these problems, a genetic algorithm (GA) is adopted for optimizing the BPNN, and the EGA-BPNN model is used to predict irrigation flow in agricultural fields. …”
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Driving Pattern Analysis, Gear Shift Classification, and Fuel Efficiency in Light-Duty Vehicles: A Machine Learning Approach Using GPS and OBD II PID Signals by Juan José Molina-Campoverde, Juan Zurita-Jara, Paúl Molina-Campoverde

“…A multiple linear regression model was developed to estimate instantaneous fuel consumption (in L/100 km) using the gear predicted by the KNN algorithm and other relevant variables. …”
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Blind source separation and unmanned aerial vehicle classification using CNN with hybrid cross-channel and spatial attention module by Jiangong Ni, Zhigang Zhou

“…The experimental results show that the improved network recognition accuracy reaches an impressive 96.30%, which is 3.01% higher than the baseline model. …”
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