Research on Optimization of Railway Obstacle Detection Model Based on Neural Architecture Search by YAO Weiwei, LYU Yu, ZHANG Huiyuan, XIONG Minjun, DONG Wenbo, LI Chen

“…Furthermore, a comparison of expected performance scores across different models leads to the selection of the optimal option as the ultimate solution. Experimental results demonstrated that this method achieved an average accuracy of 0.711 and an average inference time of 6.12 ms per frame, significantly outperforming baseline models with equivalent computational loads.…”
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Edge-first-based cooperative caching strategy in information centric networking by Jiang ZHI, Jun LI, Hai-bo WU, Yong-mao REN

“…In order to optimize the replica placement in information centric networking,an edge-first-based cooperative caching strategy (ECCS) was proposed.According to the strategy,cache decision was made during the interest forwarding stage.The decision result and statistic information would been forwarded to upstream routers step by step.Utilizing the information,upstream nodes could update their cache information table immediately to achieve cooperative caching.The experimental results indicate ECCS can achieve salient performance gain in terms of server load reduction ratio,average hop reduction ratio,average cache hit ratio,compared with current strategies.…”
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Optimization of Water Distribution Based on Head loss Analysis Using EPANET Software by Desy Fitria Wulandari, Agus Subekti, Agung Tjahjo Nugroho

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A Cluster-Based Consensus Algorithm in a Wireless Sensor Network by Yanwei Li, Zhenyu Zhou, Takuro Sato

“…In this paper, we propose an average connectivity degree cluster (ACDC) scheme gossip algorithm to improve the convergence speed and the accuracy of the consensus, when a common decision is needed for a certain phenomenon in a distributed network. …”
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Federated deep reinforcement learning-based urban traffic signal optimal control by Mi Li, Xiaolong Pan, Chuhui Liu, Zirui Li

“…By reasonably designing the state, action and reward functions and determining the optimal values of several key parameters in the federated collaboration mechanism, the RL model could ensure high learning efficiency and fast convergence in the face of the gradual increase of road network size and the exponential increase of state and action space with the number of intersections. …”
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Dynamic pricing optimization for high-speed railway based on passenger flow assignment. by Jiren Cao, Lei Nie, Lu Tong, Zhenhuan He, Zhangjiaxuan Liu

“…Taking differentiated passenger demand and supply trains as the research object, the space-time service network based on train timetable was constructed. …”
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Active Learning Query Strategies for Linear Regression Based on Efficient Global Optimization by Tianxin Zong, Na Li, Zhigang Zhang

“…This study validated the efficiency and robustness of EGO-ALR approaches using 19 datasets from various domains and three distinct linear regression models (Ridge regression, Lasso, and Elastic network).…”
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Two-branch Shape Complement Network for Feature Missing Splicing Mode by SUNJin, MAHaotian, LEIZhenting, LIANGLi

“…Firstly , a basic point cloud generation network is built based on the codec , and then the decoder structure is optimized according to the framework of generation confrontation network. …”
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Deep Q-Networks for Minimizing Total Tardiness on a Single Machine by Kuan Wei Huang, Bertrand M. T. Lin

“…The advent of Deep Q-Networks (DQNs) within the reinforcement learning paradigm could be a viable approach to transcending these limitations, offering a robust and adaptive approach. …”
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The Shrinking of Beijing and the Rising of Xiong’an: Optimize Population Migration in terms of Transport Service by Hongzhi Lin

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Image Quality Predictor with Highly Efficient Fully Convolutional Neural Network by Cao Yu-Dong, Liao Xin-Lin, Liu Hai-Yan

“…A highly efficient deep fully convolutional neural network (DFCN) for image quality assessment (IQA) is designed in this paper. …”
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Optimized ultrathin hybrid sound absorption metasurfaces with preserved hydrostatic pressure-resistant by Jiaming Feng, Qingxuan Liang, Xin Yan, Dichen Li

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Resource Allocation for Two-Way Relay Network Based on Cognitive Radio by Shuang Liang, Shouyi Yang, Wanming Hao

“…The resource allocation issue for sensing-based spectrum opportunistic access and sensing-based spectrum sharing access in two-way relay cognitive network with imperfect spectrum sensing was discussed.Different from the traditional resource allocation methods for two-way relay network,new algorithm jointly considering sensing time and transmission power in secondary system.Under the condition of the sensing time and the transmission power,the maximal throughput of the secondary system can be obtained.To protect the primary user effectively from interference,the average interference power constraint in each hop was considered.The total transmission power constraint of the secondary system is also considered.The proposed algorithms can acquire the optimal sensing time and power allocation under imperfect spectrum sensing for the sensing-based spectrum opportunistic access and sensing-based spectrum sharing access.Finally,the performance of the two schemes was compared and the effectiveness of the proposed algorithm was verified.…”
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Resource Allocation for Two-Way Relay Network Based on Cognitive Radio by Shuang Liang, Shouyi Yang, Wanming Hao

“…The resource allocation issue for sensing-based spectrum opportunistic access and sensing-based spectrum sharing access in two-way relay cognitive network with imperfect spectrum sensing was discussed.Different from the traditional resource allocation methods for two-way relay network,new algorithm jointly considering sensing time and transmission power in secondary system.Under the condition of the sensing time and the transmission power,the maximal throughput of the secondary system can be obtained.To protect the primary user effectively from interference,the average interference power constraint in each hop was considered.The total transmission power constraint of the secondary system is also considered.The proposed algorithms can acquire the optimal sensing time and power allocation under imperfect spectrum sensing for the sensing-based spectrum opportunistic access and sensing-based spectrum sharing access.Finally,the performance of the two schemes was compared and the effectiveness of the proposed algorithm was verified.…”
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Global Feature Focusing and Information Enhancement Network for Occluded Pedestrian Detection by ZHENG Kaikui, JI Kangyou, LI Jun, LI Qiming

“…CBAM adjusts the importance of each channel and spatial location in the feature maps through operations like global average pooling, maxpooling, and small fully connected neural networks in both channel and spatial attention dimensions. …”
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Trust-Based Distributed Resource Allocation in Edge-Enabled IIoT Networks by Amit Samanta, Tri Gia Nguyen

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Application of WCA-RBF Neural Network in Fault Diagnosis of Analog Circuits by Zhiwei Jin

“…The test results show that this model converges after 40 times of training, with an error value of 10−3 and an average value of the mean squared error of 0.45. Comparing the fault diagnosis rates of the original model, genetic algorithm optimized radial basis function neural network model, and wolf colony algorithm optimized radial basis function neural network model, the last model has the best fault diagnosis rate, reaching 95.52%. …”
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Dynamic heterogeneous network representation learning method based on Hawkes process by CHEN Lei, DENG Kun, LIU Xingyan

“…Firstly, the vector representation of nodes was obtained by utilizing the relational rotation encoding method and attention mechanism, where the attention coefficients of adjacent nodes were learned. Secondly, the optimal weighted combination of different meta-paths was learned to better captures the structural and semantic information of the network. …”
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A Scalable Multi-Target Tracking Algorithm for Wireless Sensor Networks by Songhwai Oh

“…The algorithm is based on a rigorous probabilistic model and an approximation scheme for the optimal Bayesian filter. In particular, an extensive simulation study shows that there is no performance loss up to an average localization error of 0.7 times the separation between sensors and the algorithm tolerates up to 50% lost-to-total packet ratio and 90% delayed-to-total packet ratio. …”
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Model Selection Approach for Distributed Fault Detection in Wireless Sensor Networks by Mrinal Nandi, Anup Dewanji, Bimal Roy, Santanu Sarkar

“…This second type of detection probability is new in sensor network literature. We develop schemes under the model selection procedure and multiple model selection procedure and use the concept of Bayesian model averaging to identify a set of likely fault sensors and obtain an average predictive error.…”
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