Solving Action Semantic Conflict in Physically Heterogeneous Multi-Agent Reinforcement Learning with Generalized Action-Prediction Optimization by Xiaoyang Yu, Youfang Lin, Shuo Wang, Sheng Han

“…Conversely, completely independent agent parameters significantly escalate computational costs and training complexity. To address these challenges, we introduce an adaptive MARL algorithm named Generalized Action-Prediction Optimization (GAPO). …”
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Numerical Modeling on the Damage Behavior of Concrete Subjected to Abrasive Waterjet Cutting by Xueqin Hu, Chao Chen, Gang Wang, Jenisha Singh

“…In this study, a numerical framework based on a coupled Smoothed Particle Hydrodynamics (SPH)–Finite Element Method (FEM) algorithm incorporating the Riedel–Hiermaier–Thoma (RHT) constitutive model is proposed to investigate the damage mechanism of concrete subjected to abrasive waterjet. …”
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Multi-objective optimization of EMS facilities using multi-source data: A case study in Dangtu, China by Jinze Li, Xiao Wang, Qiyan Zhang, Peng Tang

“…A multi-objective evolutionary algorithm calculates Pareto optimal solutions for site selection, allowing for a balanced consideration of conflicting EMS siting objectives. …”
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A Distributed Economic Power Dispatch Strategy Considering State of Charge for Microgrids by Kaicheng Lu, Shufeng Dong, Yonghua Song

“…Every node estimates the average SoC of all battery energy storage systems(BESSs) in a microgrid and determines the power of the local BESS and microturbine (MT) autonomously to achieve SoC balancing and economic dispatch with component constraints and power balance constraints by peer-to-peer communication with its neighbors. To improve the effectiveness of power distribution, an improved average consensus algorithm(IACA) based on particle swarm optimization (PSO) is proposed to adjust the weight matrix of communication networks, which reduces the number of iterations to estimate the average SoC. …”
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An Optimal Sizing Methodology for a Wind/PV Hybrid Energy Production System for Agricultural Irrigation in Skikda, Algeria by Nadhir Abderrahmane, Allaoua Brahmia, Adlen Kerboua, Ridha Kelaiaia

“…The optimization algorithm used was tailored to the formulated problem, ensuring reliable and applicable results. …”
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Detection Method for Bolts with Mission Pins on Transmission Lines Based on DBSCAN-FPN by Zhenbing ZHAO, Shuai ZHANG, Wei JIANG, Peng WU

“…Then, the FPN model is improved: based on the prior knowledge of bolts, the convolutional network is used to achieve bottom-up feature extraction, the bilinear interpolation method is used to transfer the high-level semantic information of the features to each level from top to bottom, the convolution filtering method is used to laterally strengthen the information fusion of high-level semantic features and high-resolution features, and a more optimized feature expression of bolts with missing pins is obtained. …”
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E-Commerce Logistics Software Package Tracking and Route Planning and Optimization System of Embedded Technology Based on the Intelligent Era by Dan Zhang, Zhiyang Jia

“…To sum up, this algorithm could effectively optimize the distribution route of logistics packages and improve the efficiency of package transportation.…”
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Optimal sleep time controller based on traffic prediction and residual energy in duty-cycled wireless sensor networks by Haibo Luo, Minghua He, Zhiqiang Ruan, Xiaxia Zeng

“…In duty-cycled wireless sensor networks, energy efficiency and packet latency are two most important metrics in the design of medium access control and routing algorithms. …”
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Enhancing Security for Resource-Constrained Smart Cities IoT Applications: Optimizing Cryptographic Techniques with Effective Field Multipliers by Atef Ibrahim, Fayez Gebali

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Machine learning model for classifying high school students’ academic performance in mathematics amidst the COVID-19 context by Gisella Luisa Elena Maquen-Niño, Moisés Alvin Miguel_Flores, Leysi Yarely Aurich_Mio, Ivan Adrianzén Olano, Percy Edwin De la Cruz Vélez de Villa, Diana Mercedes Castro Cárdenas

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Unboxing Tree ensembles for interpretability: A hierarchical visualization tool and a multivariate optimal re-built tree by Giulia Di Teodoro, Marta Monaci, Laura Palagi

“…The interpretability of models has become a crucial issue in Machine Learning because of algorithmic decisions' growing impact on real-world applications. …”
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A Comprehensive Review of Thermal Management Methods and Ideal System Design for Improved Electric Vehicle Battery Pack Performance and Safety by M. Murugan, P. V. Elumalai, KCK Vijayakumar, M. Babu, K. Suresh Kumar, M. Ganesh, Liu Kuang, S. Prabhakar

“…From this aspect, the problem of this research focused on the description of a detailed insight into the efficiencies of TMSs inside an EV, pointing to the impacts of various cooling mechanisms, mostly liquid cooling, air cooling, and phase‐change materials. …”
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Multi-criteria vehicle routing problem for a real-life parcel locker-based delivery by Radosław Idzikowski, Jarosław Rudy, Michał Jaroszczuk

“…Results confirm that both Tabu Search and Genetic Algorithm significantly improve the solution provided by the greedy algorithm, with Genetic Algorithm being the most effective on average. …”
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GAT-ADNet: Leveraging Graph Attention Network for Optimal Power Flow in Active Distribution Network With High Renewables by Dinesh Kumar Mahto, Mahipal Bukya, Rajesh Kumar, Akhilesh Mathur, Vikash Kumar Saini

“…The high penetration of renewables into the active distribution network (ADN) brings voltage deviation and difficulties to the optimal power flow (OPF) problem. The optimal operation of the distribution grid aims to efficiently manage the flow of electricity from sources to end-users, ensuring a resilient and sustainable grid. …”
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A hybrid model based on learning automata and cuckoo search for optimizing test item selection in computerized adaptive testing by Chanjuan Jin, Weiming Pan

“…Compared with the traditional CAT methods, our approach gives better ability estimates and selects test items that are most appropriate for each student. The findings of the study show that the efficiency, accuracy and fairness of the tests have improved through experimentation.…”
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Optimizing High-Speed Railroad Timetable with Passenger and Station Service Demands: A Case Study in the Wuhan-Guangzhou Corridor by Jin Wang, Leishan Zhou, Yixiang Yue, Jinjin Tang, Zixi Bai

“…The results show that the proposed model and algorithm can quickly reduce the defined cost function by 38.2% and improve the average travel speed by 10.7 km/h, which indicates that our proposed model and algorithm can effectively improve the quality of a constructed train timetable and the travel efficiency for passengers.…”
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Distribution Generation Network Arrangement by Capacitor Placement and Sizing in Renewable Energy Sources with Uncertainties Based on Self-adaption Kho-Kho Optimizer by Lu Xingxing

“…Post-optimization results indicated a reduction in power loss costs from 4.11 × 10^5 to 1.05 × 10^5 units, representing a 25.54% decrease. …”
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Optimizing microgrid performance a multi-objective strategy for integrated energy management with hybrid sources and demand response by Mohsen Moosavi, Javad Olamaei, Hossein Mohmmadnezhad Shourkaei

“…When compared to leading optimization algorithms, the proposed approach showed better performance. …”
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Research on the optimal scheduling of a multi-storage combined integrated energy system based on an energy supply grading strategy by Na Zhang, Feng You, Bingqian Hu, Jingyu Li, Guangchen Liu

“…Next, considering the system operational cost and carbon emission cost as the optimization goal, a comprehensive energy optimization scheduling model of multi-storage combined hierarchical energy supply is constructed. …”
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Improvement of Network Traffic Prediction in Beyond 5G Network using Sparse Decomposition and BiLSTM Neural Network by Rihab Abdullah Jaber Al Hamadani, Mahdi Mosleh, Ali Hashim Abbas Al-Sallami, Rasool Sadeghi

“…Next, sparse feature extraction is performed using Discrete Wavelet Transform (DWT), and a sparse matrix is constructed. A Genetic Algorithm (GA) is used to optimize the sparse matrix, which effectively selects the most significant features for prediction. …”
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