Recovery and Resource Allocation Strategies to Maximize Mobile Network Survivability by Using Game Theories and Optimization Techniques by Pei-Yu Chen, Frank Yeong-Sung Lin

“…In addition, the Average DOD would be used to evaluate the damage degree of the network. …”
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Joint user association and power control scheme based on energy consumption and QoE in heterogeneous network by Shiyu JI, Liangrui TANG, Shuxian LI, Shimo DU

“…Based on multi-objective optimization,a joint user association and power control scheme was proposed in heterogeneous network environment,aiming to reduce the system energy consumption and improve user quality of experience.The scheme took the system energy consumption minimum and the average user quality of experience maximum as objective functions and translated the joint user association and power control to multi-objective problem.Then,the differential evolution optimization algorithm and TOPSIS algorithm was used to solve the multi-objective problem.Simulation results show that the scheme can efficiently reduce the system energy consumption and improve the user quality of experience.…”
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Optimization of Bandwidth Allocation and UAV Placement in Active RIS-Assisted UAV Communication Networks with Wireless Backhaul by Thi-Thuy-Minh Tran, Binh-Minh Vu, Oh-Soon Shin

“…Moreover, a comprehensive alternating optimization framework is proposed to implement an iterative solution for the sub-problems. Simulation results demonstrate that the proposed algorithm achieves approximately 59% improvement in the average sum rate, substantially enhancing overall network reliability compared to existing benchmark schemes.…”
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Q-LME: Q-learning-based local mutual exclusion algorithm for flying ad hoc networks by Sindhuja S, Mary Anita Rajam V

“…This paper addresses the LME problem for FANETs through Q-learning-based Local Mutual Exclusion (Q-LME). …”
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Deep Reinforcement Learning-Based Joint Routing and Capacity Optimization in an Aerial and Terrestrial Hybrid Wireless Network by Zhe Wang, Hongxiang Li, Eric J. Knoblock, Rafael D. Apaza

“…In this ATHN, AVs and BSs collaboratively form a multi-hop ad-hoc network with the objective of minimizing the average end-to-end (E2E) packet transmission delay. …”
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Charging Scheduling Method for Wireless Rechargeable Sensor Networks Based on Energy Consumption Rate Prediction for Nodes by Songjiang Huang, Chao Sha, Xinyi Zhu, Jingwen Wang, Ruchuan Wang

“…With the development of the IoT, Wireless Rechargeable Sensor Networks (WRSNs) derive more and more application scenarios with diverse performance requirements. …”
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Resilient Transportation Network Design under Uncertain Link Capacity Using a Trilevel Optimization Model by Mohammad Rahdar, Lizhi Wang, Jing Dong, Guiping Hu

“…The upper-level takes the system perspective to expand the existing transportation network to enhance resiliency. We also propose a formulation for the network flow problem to significantly reduce the number of variables and constraints. …”
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A Multiobjective Evolutionary Algorithm for Energy-Efficient Cooperative Spectrum Sensing in Cognitive Radio Sensor Network by Weirong Liu, Gaorong Qin, Shuo Li, Jian He, Xiaoyong Zhang

“…Cognitive radio has emerged as a promising solution to address the problems posed by coming spectrum scarcity for the inherently resource-constrained sensor networks. …”
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NMPC-Based Performance Evaluation of Active Balancing Networks of Li-ion Batteries for Overnight EV Charging by Muhammad Azmat Ullah, Afaq Ahmed, Ali Arshad Uppal, Qadeer Ahmed

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Integral-Based Memory Event-Triggered Controller Design for Uncertain Neural Networks with Control Input Missing by Ping Wang, Zhen Wang, Haiyang Xu

“…In this paper, the controller design problem for uncertain neural networks (NNs) with control input missing is addressed under an event-triggered (ET) scheme. …”
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Improving IoRT Networks: Cross-Tier Resource Allocation for Multi-Antenna UAV Relays in SAGIN by Zahra Khodadadi, Foroogh S. Tabataba, Mohammad Sadegh Fazel, Mehdi Naderi Soorki, Halim Yanikomeroglu

“…By jointly adopting proposed size-constrained PSO-K-means clustering, Simulated Annealing (SA) method, and Successive Convex Approximation (SCA) method, a two-stage scheme is devised to solve the proposed NP-hard and non-convex problem. Our simulation results indicate that an average performance improvement of 44% is achieved by our proposed scheme compared to the case where only clustering is performed. …”
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Accelerating flood warnings by 10 hours: the power of river network topology in AI-enhanced flood forecasting by Hongjun Wang, Jiyuan Chen, Yinqiang Zheng, Xuan Song

“…Our analysis reveals that the tree-like configuration of river networks leads to over-squashing in GNNs, a problem caused by high resistance distances between nodes. …”
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Employing Siamese Networks as Quantitative Biomarker for Assessing the Effect of Dolphin-Assisted Therapy on Pediatric Cerebral Palsy by Jesús Jaime Moreno Escobar, Oswaldo Morales Matamoros, Erika Yolanda Aguilar del Villar, Hugo Quintana Espinosa, Liliana Chanona Hernández

“…The methodology involves training a Siamese network, a type of neural network designed to compare similarities between inputs, using data collected from SCP patients undergoing DAT sessions. …”
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Research on rechargeable agricultural wireless sensor network based on ZigBee immune routing repair algorithm by Ruipeng Tang, Yinhe Wu, Jun Tan, Binghong Guan, Narendra Kumar Aridas, Mohamad Sofian Abu Talip

“…Abstract WSN (wireless sensor network) plays a very important role in the agricultural environment monitoring. …”
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Interference Mitigation in mmWave Heterogeneous Cloud-Radio Access Network: For Better Performance and User Connectivity by Najwan M. Swadi, Firas A. Sabir, Hamed S. Al-Raweshidy

“…In other hand, the adaptive solution of RRH-BBU k-means clustering sub problem depend on actual load and number of active RRHs in the network to find the number of k RRH-BBU clusters, which manage resource consumption. …”
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RL-Net: a rapid and lightweight network for detecting tiny vehicle targets in remote sensing images by Yaoyao Du, Li Chen, Xingxing Hao

“…The integration of Unmanned Aerial Vehicles (UAVs) with object detection technology offers a promising solution to this problem. However, existing detection networks often exhibit limitations such as missed detections and inadequate real-time performance, particularly for small vehicle targets in remote sensing images, and fail to meet the efficiency requirements of edge computing devices. …”
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Medical Image Classification Algorithm Based on Weight Initialization-Sliding Window Fusion Convolutional Neural Network by Feng-Ping An

“…A new network weight initialization method is proposed, which alleviates the problem that existing deep learning model initialization is limited by the type of the nonlinear unit adopted and increases the potential of the neural network to handle different visual tasks. …”
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Physarum-inspired multi-parameter adaptive routing protocol for coal mine hybrid wireless mesh networks by Guangzhi Han, Haifeng Jiang, Liansheng Lu, Shanshan Ma, Shuo Xiao

“…The experimental results show that the route path selected by Physarum-inspired multi-parameter adaptive routing protocol is better than those selected by the other four protocols in the performance of average end-to-end delay and delivery ratio. The balance of energy consumption and network load is achieved and the network lifetime is effectively prolonged when using Physarum-inspired multi-parameter adaptive routing protocol.…”
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Stochastic and Percolating Models of Blocking Computer Networks Dynamics during Distribution of Epidemics of Evolutionary Computer Viruses by S. A. Lesko, A. S. Alyoshkin, V. V. Filatov

“…On one hand, this model is based on the use of percolation theory methods, which makes it possible to determine such structural-information characteristics of networks as the dependence of the percolation threshold on the average number of connections per one node (network density). …”
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An ESG-ConvNeXt network for steel surface defect classification based on hybrid attention mechanism by Ning Zhang, Ziyang Liu, Enxu Zhang, Yuanqi Chen, Jie Yue

“…Finally, in the downsampling stage, we incorporate a PReLU activation function to mitigate the problem of neuron death during downsampling. We conducted extensive experiments using the NEU-CLS-64 steel surface defect dataset, and the results demonstrate that our model outperforms other methods in terms of detection performance, achieving an average recognition accuracy of 97.5%. …”
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