Distributed Downlink Power Control by Message-Passing for Very Large-Scale Networks by Illsoo Sohn

“…Downlink power control is revisited by assuming very large-scale networks. In very large-scale networks, conventional centralized power control schemes quickly become impractical owing to the huge computational burden and limited backhaul capacity. …”
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Improved Ant Colony Algorithm for Network Flow Scheduling in SDN Data Center by ZHU Su-xia, LONG Yi-fei, SUN Guang-lu, LI Chun-feng

“…At present, in the software defined data center network, the flow scheduling strategy based on ant colony algorithm has the disadvantages of too slow convergence and search stagnation in path selection, which easily leads to the problems of excessively high data center network delay and low resource utilization.Therefore, this paper proposes an improved flow scheduling algorithm based on ant colony. …”
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Virtual Network Resource Allocation Algorithm Based on Load Balance in Carrier-SDN by Li Wang, Jihong Zhao, Hua Qu, Ya Guo

“…Resource allocation algorithm for virtual networks in carrier-SDN based on load balance was proposed.Firstly,multiple-layered model of carrier-SDN was constructed.Secondly,the binaryzation of particle swarm optimization algorithm with the characteristic of virtual network embedding（VNE）algorithm was realized.Finally,load balance was set as optimization object,then the solution of VNE problem was got.The simulation results demonstrate that the proposed algorithm has superior performance in terms of load balance,acceptance ratio and average compared with existing methods.…”
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Training of the feed-forward artificial neural networks using butterfly optimization algorithm by Şaban Gülcü, Büşra Irmak

“…Artificial Neural Network (ANN) learns from inputs and outputs. The values of the weights and biases in ANN are updated according to inputs and outputs. …”
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Delay-Dependent Dynamics of Switched Cohen-Grossberg Neural Networks with Mixed Delays by Peng Wang, Haijun Hu, Zheng Jun, Yanxiang Tan, Li Liu

“…This paper aims at studying the problem of the dynamics of switched Cohen-Grossberg neural networks with mixed delays by using Lyapunov functional method, average dwell time (ADT) method, and linear matrix inequalities (LMIs) technique. …”
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Connectivity-Sensed Routing Protocol for Vehicular Ad Hoc Networks: Analysis and Design by Changle Li, Mengmeng Wang, Lina Zhu

“…In this paper, we have studied the network connectivity using a stochastic analysis model and then we prove average intervehicle distance influences VANET connectivity greatly. …”
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Magnifier: A Multigrained Neural Network-Based Architecture for Burned Area Delineation by Daniele Rege Cambrin, Luca Colomba, Paolo Garza

“…The problem in their development in this context is the data scarcity and the lack of extensive benchmark datasets, limiting the capabilities of training large neural network models. …”
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Energy Efficiency Optimization for UAV-RIS-Assisted Wireless Powered Communication Networks by Xianhao Shen, Ling Gu, Jiazhi Yang, Shuangqin Shen

“…Furthermore, deep reinforcement learning (DRL) is introduced to effectively solve the formulated optimization problem. Simulation results demonstrate that the proposed optimized scheme outperforms benchmark schemes in terms of average throughput and energy efficiency. …”
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CIT-EmotionNet: convolution interactive transformer network for EEG emotion recognition by Wei Lu, Lingnan Xia, Tien Ping Tan, Hua Ma

“…Emotion recognition is a significant research problem in affective computing as it has a lot of potential areas of application. …”
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Optimal Determination of the Q/A Factor for Parabolic Concentrator Solar Collector Networks by Juan-Ramón Lizárraga-Morazán, Martín Picón-Núñez

“…This work presents a study of the Q/A factor in optimised designs of solar thermal networks of the Solar Heat for Industrial Processes (SHIP) type, which utilise Parabolic Trough Collector (PTC) technology for both winter and summer seasons. …”
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Cooperative Downloading in Mobile Ad Hoc Networks: A Cost-Energy Perspective by He Li, Yang Yang, Xuesong Qiu, Zhipeng Gao, Guizhen Ma

“…This work addresses the problem while distributing content to a group of mobile terminals (MTs) that cooperate during the download process by forming mobile ad hoc networks. …”
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Dynamic Prediction of Low Permeability Oilfield Development Based on BP Neural Network by CHEN Yujia, WANG Wei, REN Lijian, WANG Bing, WANG Runping, YANG Jun, FAN Jiawei, ZHU Yushuang

“…It is suitable for the problem of oilfield development with a large sample dataset, and provides a new perspective for understanding the development dynamics of low-permeability oilfields.…”
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Track line status detection system for subway based on lightweight convolutional network by LIN Jun, YUAN Hao, LIU Yue, KANG Gaoqiang, TONG Hao

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Pedestrian trajectory prediction model based on self-supervised spatiotemporal graph network by Shiji Yang, Xuezhong Xiao

“…Thus, a pedestrian trajectory prediction model based on a self - supervised spatiotemporal graph network is proposed. Firstly, in the process of spatiotemporal graph modeling, this model introduces hop interaction instead of node interaction to update node features, which greatly reduces the times of graph convolution operations, alleviates the problem of feature smoothing, and greatly improves the accuracy of prediction. …”
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Lightweight anomaly detection model for UAV networks based on memory-enhanced autoencoders by HU Tianzhu, SHEN Yulong, REN Baoquan, HE Ji, LIU Chengliang, LI Hongjun

“…In order to solve the problems of high energy consumption and high reliance on manual annotation data of traditional intelligent attack detection methods in UAV networks, a lightweight UAV network online anomaly detection model based on a double-layer memory-enhanced autoencoder integrated architecture was proposed. …”
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Community detection algorithm of hybrid node analysis and edge analysis in complex networks by Kun DENG, Qingfeng JIANG, Xingyan LIU

“…The community detection of hybrid node analysis and edge analysis in complex networks (CDHNE), a novel community detection algorithm, was proposed aiming at the problem that both edge community detection and node-based community detection algorithms had corresponding shortcomings in the process of detecting communities, which affected the quality of complex network community detection.The relatively stable characteristics of the edge in the networks were firstly used by the algorithm to construct a more accurate community structure through edge community detection at the early stage of algorithm execution.Then, after the formation of the edge communities, the flexible characteristics of the node were used to accurately detect the boundary of edge communities, so as to more accurately detect the community structure in the complex networks.In the computer-generated network experiments, when the community structure of the network gradually became fuzzy, the number of overlapping nodes and the number of communities to which the overlapping nodes belonged kept increasing.Compared to traditional algorithms, the accuracy of community detection and overlapping nodes detection were improved by an average of 10% and 15%, respectively, by the CDHNE algorithm.In the real network experiments, the tightness of the community structure detected by the CDHNE algorithm was better.Especially when facing large-scale networks with more than 100 000 nodes, the detection task was completed by the CDHNE algorithm with high quality, and the EQ value reached 0.412 1.The experimental results show that the CDHNE algorithm has advantages in operational stability and handling large-scale networks.…”
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Highway Traffic Flow Prediction Algorithm Based on Multiscale Transformation and Convolutional Networks by Yuzhu Luo, Jiarong Wang, Ming Wei

“…In order to solve the problem that the traditional long-term high-speed traffic forecasting algorithm is affected by the approximation ability of the function and easy to fall into the local mass value, we wrote a multivariate-based highway traffic forecasting algorithm scaling and convolutional networks. …”
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Diagnosis of abnormal sound in loudspeakers by integrated attention mechanism convolutional neural network by ZHOU Jinglei, WANG Xiaoming, LI Limin

“…In response to the problem of the non-linear, non-stationary nature of speaker abnormal sound, as well as their susceptibility to external noise interference, and the low recognition rates, a speaker abnormal sound classification method with variational mode decomposition (VMD) and 1D convolutional recurrent attention network (1DCNN-BiLSTM-Attention) was proposed. …”
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ClipQ: Clipping Optimization for the Post-Training Quantization of Convolutional Neural Network by Yiming Chen, Hui Zhang, Chen Zhang, Yi Liu

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Real-time traffic enhancement scheduling for train communication networks based on TSN by Deqiang He, Zeqian Chen, Daliang Sun, Zhenzhen Jin, Yanjun Chen, Rui Ma, Chen Liang

“…Experimental results show that compared with the traditional constraint model, the schedulability of the model with an adaptive switch queue selection mechanism increases by 33.0%, and the maximum end-to-end delay and network jitter decrease by 19.1% and 18.6% on average respectively. …”
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