Economic Dispatch Analysis of Risk Prevention and Control Based on Game Theory Equilibrium by Qixiang WANG, Zhentao HAN, Yi LIANG

“…In order to solve these problems, this paper first proposes an economic dispatch mathematical model for risk prevention and control of the power system considering green power generation and consumption and then puts forward a game theory equilibrium solution algorithm based on the optimal response method. …”
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Collision-Free Path Planning for Multiple Drones Based on Safe Reinforcement Learning by Hong Chen, Dan Huang, Chenggang Wang, Lu Ding, Lei Song, Hongtao Liu

“…Additionally, in the testing phase, the proposed method realized a 43% improvement in the task success rate relative to the MADDPG.…”
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SIDDA: SInkhorn Dynamic Domain Adaptation for image classification with equivariant neural networks by Sneh Pandya, Purvik Patel, Brian D Nord, Mike Walmsley, Aleksandra Ćiprijanović

“…SIDDA is compatible with a variety of NN architectures, and it works particularly well in improving classification accuracy and model calibration when paired with symmetry-aware equivariant NNs (ENNs). …”
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EVOLUTION OF THE AGRICULTURAL LABOUR MARKET IN THE EUROPEAN UNION BETWEEN 2011-2020 by Cristina Vasilica ICOCIU, Ana-Maria IFRIM, Cătălin Ionuț SILVESTRU, Marius-Mihai MICU

“…The basic hypothesis is that, over time, agriculture has been the premise for the economic development of the world's states, the agricultural transition being quite well correlated with general growth processes. By improving their competitiveness and strengthening their agricultural production capacities, the countries of the world can recover from any crisis, especially after a health crisis. …”
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Proposing a New Method for Customer Segmentation Based on Their Level of Loyalty and Defining Appropriate Strategies for Each Segment by Samira KHodabandehlou, Ali Akbar Niknafs

“…The evaluation of customer loyalty have a significant impact on improving business processes. Ordinary methods of customer loyalty evaluation have been designed based on three components including; recency of transactions (R), the frequency of transactions (F) and the monetary value of transactions (M). …”
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Designing transit routes based on vehicle routing behavior determined through location-based services data by Yuhan Tang, Abdullah Alhadlaq, Alben Rome Bagabaldo, Marta C. Gonzalez

“…To design transit improvements, we first apply k-means clustering based on Euclidean distances to group underserved road segments, and then refine these groups using a shortest-path-based clustering algorithm. …”
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Enhancing Secure Energy Efficiency of SWIPT IoT Network Considering IRS and Artificial-Noise: A Deep Learning Approach by Kimchheang Chhea, Jung-Ryun Lee

“…To solve this problem, we propose a deep neural network (DNN) algorithm that utilizes a loss function derived from Lagrange duality function. …”
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A novel framework to intercept GPS-denied, bomb-carrying, non-military, kamikaze drones: Towards protecting critical infrastructures by Athanasios N. Skraparlis, Klimis S. Ntalianis, Nicolas Tsapatsoulis

“…Both defensive drones are equipped with a net-gun and an innovative algorithm, which, among others, estimates the locations of interception, using a real-world trajectory model. …”
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3D Human Motion Capture Method Based on Computer Vision by A. D. Obukhov, D. L. Dedov, E. O. Surkova, I. L. Korobova

“…Based on the skeletal points obtained from the neural network, a three-dimensional reconstruction of the human body model was carried out using various triangulation algorithms.Results. …”
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A Multi-Index Fusion Adaptive Cavitation Feature Extraction for Hydraulic Turbine Cavitation Detection by Yi Wang, Feng Li, Mengge Lv, Tianzhen Wang, Xiaohang Wang

“…The number of decomposition layers in the multi-index fusion variational mode decomposition (VMD) algorithm is adaptively determined by fusing multiple indicators related to cavitation characteristics, thus retaining more cavitation information and improving the quality of cavitation feature extraction. …”
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Fatigue-Aware Sub-Second Combinatorial Auctions for Dynamic Cycle Allocation in Human–Robot Collaborative Assembly by Claudio Urrea

“…Results: In 1000 RoboDK episodes, the framework increases active cycles·min⁻¹ by 20%, improves robot utilization by +10.2 percentage points, reduces per cycle fatigue by 4%, and raises the collision-free rate to 99.85% versus a static baseline (<i>p</i> < 0.001). …”
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Dynamic characteristics of a semi-active fractional-order inerter-based suspension with acceleration-velocity switch control by Yong Wang, Jiachen Li, Mingzhu Ji, Xiwen Qiao, Yang Wang

“…According to the mechanical characteristic of the inerter, the acceleration-velocity switch (AVS) control strategy is proposed to adjust the inertance of the SA-FO inerter. The dynamic model of the SA-FOIB suspension with AVS control is established, its dynamic response under road harmonic excitation is obtained using the averaging method, the dynamic performance under road harmonic and random excitations is analyzed and evaluated by the vehicle body acceleration, suspension dynamic deflection and wheel dynamic load, the optimized structural parameters are obtained using the genetic algorithm optimization method. …”
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Deep Learning-Based Data-Assisted Channel Estimation and Detection by Hamidreza Hashempoor, Wan Choi

“…We introduce a novel structure empowered by deep learning models, accompanied by a thorough training methodology, for enhancing channel estimation and data detection in multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. …”
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Research on the policy inconsistency, network motifs and low carbon effects for municipal solid waste management by Bo Lv, Tianxu Cui, Daiheng Li, Weiyue Yao

“…This study combines the policy consistency formula, a four-node network motif evolution algorithm, and the Exponential Random Graph Model (ERGM), analyzing MSWM green network motifs with carbon emission data. …”
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Innovative two-stage thermal control of DC-DC converter for hybrid PV-battery system by Rasool M. Imran, Kadhim Hamzah Chalok, Siraj A. M. Nasrallah

“…Most PV systems utilize various maximum power point tracking (MPPT) algorithms to inject the maximum available power into the utility. …”
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HASSDE-NAS: Heuristic–Adaptive Spectral–Spatial Neural Architecture Search with Dynamic Cell Evolution for Hyperspectral Water Body Identification by Feng Chen, Baishun Su, Zongpu Jia

“…A heuristic cell search algorithm optimizes the network architecture through architecture stability, feature diversity, and gradient sensitivity analysis, which improves search efficiency and model robustness. …”
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Accurate identification of locally aneuploid cells by incorporating cytogenetic information in single cell data analysis by Ziyi Li, Ruoxing Li, Irene Ganan-Gomez, Hussein A. Abbas, Guillermo Garcia-Manero, Wei Sun

“…PartCNVH further improves partCNV by integrating a hidden Markov model for feature selection. …”
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Review of sEMG for Exoskeleton Robots: Motion Intention Recognition Techniques and Applications by Xu Zhang, Yonggang Qu, Gang Zhang, Zhiqiang Wang, Changbing Chen, Xin Xu

“…A model with stronger generalization ability is obtained after training, thereby improving the accuracy of human movement intention recognition based on sEMG technology, which provides important support for the realization of human–machine fusion-embodied intelligence of exoskeleton robots.…”
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Task Offloading with LLM-Enhanced Multi-Agent Reinforcement Learning in UAV-Assisted Edge Computing by Feifan Zhu, Fei Huang, Yantao Yu, Guojin Liu, Tiancong Huang

“…This framework integrates the QTRAN algorithm with a large language model (LLM) for efficient region decomposition and employs graph convolutional networks (GCNs) combined with self-attention mechanisms to adeptly manage inter-subregion relationships. …”
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Towards few-shot learning with triplet metric learning and Kullback-Leibler optimization by Yukun Liu, Xiaojing Wei, Daming Shi, Dan Xiang, Junliu Zhong, Hai Su

“…In training, the deep learning and expectation-maximization algorithm are used to optimize models. Intensive experiments have been conducted on three popular benchmark datasets, and the experimental results show that this method significantly improves the classification ability of few-shot learning tasks and obtains the most advanced performance.…”
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