Pickup and delivery planning for the crowdsourced freight delivery routing problem. by Jingxian Zhang

“…The objective is to minimize total service costs, including fixed vehicle costs, transportation costs, and penalty costs for delays, while planning routes that cover all orders. To solve this combinatorial optimization problem, we propose an improved partheno genetic algorithm (IPGA) and a simulated annealing algorithm (SA). …”
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Microservice selection approach for mobile users in edge computing environment by ZHAO Shuxu, JIANG Kaijun, WANG Xiaolong

“…Firstly, a microservice selection architecture was established based on containers and workflows, and a migration load optimization model incorporating service quality evaluation metrics was formulated. …”
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Using Graph Neural Networks in Reinforcement Learning With Application to Monte Carlo Simulations in Power System Reliability Analysis by Oystein Rognes Solheim, Boye Annfelt Hoverstad, Magnus Korpas

“…Recent efforts from the authors indicate that optimal power flow solvers could potentially be replaced with the policies of deep reinforcement learning agents, to obtain significant speedups of Monte Carlo simulations while retaining close to optimal accuracies. …”
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State-Aware Energy Management Strategy for Marine Multi-Stack Hybrid Energy Storage Systems Considering Fuel Cell Health by Pan Geng, Jingxuan Xu

“…A hybrid Genetic Algorithm–Particle Swarm Optimization (GA-PSO) approach achieves global optimization. …”
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IMPROVING EFFICIENCY OF RADIO MAINTENANCE TO ENSURE SAFETY by V. E. Emelyanov, I. A. Polotnyanschicov

“…The Algorithm of solving the task of optimal control is given.…”
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Machine learning for defect condition rating of wall wooden columns in ancient buildings by Yufeng Li, Wu Ouyang, Zhenbo Xin, Houjiang Zhang, Shuqi Sun, Dian Zhang, Wenbo Zhang

“…The RBF neural network model achieved the highest accuracy (94.57 %) on the feature fusion dataset, while Grey Wolf Optimizer (GWO) optimization further improved accuracy to 96.74 %. …”
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Finding a suitable chest x-ray image size for the process of Machine learning to build a model for predicting Pneumonia by Kriengsak Yothapakdee, Yosawaj Pugtao, Sarawoot Charoenkhun, Tanunchai Boonnuk, Kreangsak Tamee

“…The neural network algorithm achieved an accuracy rate of 87.00% across different image sizes. …”
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Development of Adaptive Testing Method Based on Neurotechnologies by E. V. Chumakova, D. G. Korneev, M. S. Gasparian

“…SGD, Adam, NAdam and RMSprop implemented in Keras were compared as optimizers to achieve faster convergence. Adam showed the best results in terms of accuracy, while the MSE loss function (mean square error) was used together with the optimizer. …”
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Eecs-fl: energy-efficient client selection for federated learning in AIoT by Yiyang Zhang, Yiming Luo, Tao Yang, Xiaofeng Wu, Bo Hu

“…This paper presents a novel energy-efficient client selection algorithm for FL, designed to address these challenges by integrating Wireless Power Transfer (WPT), where WPT involves in the client selection optimization, based on real-time energy availability and resource heterogeneity. …”
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Multiobjective Coverage Control Strategy for Energy-Efficient Wireless Sensor Networks by Hui Zhou, Tian Liang, Chen Xu, Jing Xie

“…A new evolutionary algorithm named Multiobjective free search algorithm (MOFS) is designed for WSN optimization problem based on fitness functions and binary coding schemes. …”
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Automatic collaborative water surface coverage and cleaning strategy of UAV and USVs by Tianping Deng, Xiaohui Xu, Zeyan Ding, Xiao Xiao, Ming Zhu, Kai Peng

“…Second, we design a task scheduling and assignment algorithm for USVs to balance the garbage loads based on the particle swarm optimization algorithm. …”
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Identification of green leafhoppers (cicadellidae) in vineyards through an automatic image acquisition system from yellow sticky traps associated with deep-learning by Proença Maria da Conceição, Rebelo Maria Teresa, Valent Riccardo, Mateus Rebeca, Gaspar Pedro Diniz, Lopes Carlos Manuel, Franco José Carlos

“…The results demonstrated the algorithm’s capability to accurately identify green leafhopper species, improving the speed of identification compared to conventional methods while maintaining a high level of precision (80%), and a harmonic mean of the precision and recall (F1) of 0.85. …”
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UAV Mission Path Planning Based on Reinforcement Learning in Dynamic Environment by Gui Fu, Yang Gao, Liwen Liu, Mingye Yang, Xinyu Zhu

“…The path planning and optimization of UAV in dynamic environment is studied, and the path planning algorithm and Hungarian algorithm are added. …”
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Fault reconfiguration control strategy of islanded marine ranching power supply system based on deep reinforcement learning by Yichun Wang, Bo Zhang, Rongjie Wang, Jiang Desong, Yabo Cui, Zhouyang Sun, Hao Liu

“…Finally, through analysis of fault reconstruction cases in different operating conditions of the marine ranching power system, it is demonstrated that this proposed algorithm can provide optimal reconstruction strategies within as short as 70 ms while achieving objectives such as maximum load recovery, minimum switching times, and minimum network losses. …”
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Improving Secrecy Capacity in the Face of Eavesdropping in SWIPT CIoT Networks With Actor-Critic DRL by Nada Abdel Khalek, Walaa Hamouda

“…We formulate the challenging non-convex optimization problem to maximize secrecy capacity while ensuring spectrum sharing and energy constraints and model the CIoT agent’s decision-making as a model-free Markov decision process (MDP). …”
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Advanced machine learning techniques reveal multidimensional EEG abnormalities in children with ADHD: a framework for automatic diagnosis by Ying Mao, Ying Mao, Xuchen Qi, Xuchen Qi, Xuchen Qi, Lingyan He, Shan Wang, Zhaowei Wang, Fang Wang, Fang Wang

“…Then, four widely-employed machine learning algorithms (including random forest (RF), XGBoost, CatBoost, and LightGBM) were used for classification calculations, and the SHAP algorithm was then used to assess the importance of the contributing features to interpret the model’s decision process.ResultsThe results showed that the highest classification accuracy of 99.58% for pediatric ADHD detection was obtained with the CatBoost model based on the optimal feature subset of 206 features (PSD/FuzEn/MI = 53/5/148). …”
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Modified Diagnostic Criteria Tools for Familial Hypercholesterolemia without the Requirement for Clinical Genetic Testing: Rationale and Design of the MOOCS Adaptive Clinical Trial by Satyanarayana Upadhyayula

“…Various available FH diagnostic tools are grouped together in the FH diagnostic criteria tool universal algorithm. Background: The standard diagnostic criteria tools for FH require GT. …”
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YOLO-SMUG: An Efficient and Lightweight Infrared Object Detection Model for Unmanned Aerial Vehicles by Xinzhe Luo, Xiaogang Zhu

“…To tackle the high computational demands and accuracy limitations in UAV-based infrared object detection, this study proposes YOLO-SMUG, a lightweight detection algorithm optimized for small object identification. …”
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Control strategy of robotic manipulator based on multi-task reinforcement learning by Tao Wang, Ziming Ruan, Yuyan Wang, Chong Chen

“…To tackle this issue, instead of uniform parameter sharing, we propose an adjudicate reconfiguration network model, which we integrate into the Soft Actor-Critic (SAC) algorithm to address the optimization problems brought about by parameter sharing in multi-task reinforcement learning algorithms. …”
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A Hybrid Deep Learning Model for UAV Path Planning in Dynamic Environments by Junchi Zhang, Yanning Xian, Xun Zhu, Hongtao Deng

“…While its variants can converge to the optimal solution, they suffer from more memory and computation consumption. …”
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