Spatial Layout Optimization in Urban Renewal Based on Improved NSGAII Algorithm by Xuan Han, Baishu Xia

“…A multi-objective optimization method based on the improved non-dominated sorting genetic algorithm II was proposed to address the problem of spatial layout optimization in urban renewal. …”
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Research on the Algorithm for Composite Lining of Deep Buried Water Conveyance Tunnel by Fei Li, Ningdong Chang, Jianhui Wang, Tao Feng, Chunling Li

“…This case study was analysed by using the simplified algorithm and verified by finite element method with ABAQUS. …”
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CGDINet: A Deep Learning-Based Salient Object Detection Algorithm by Chengyu Hu, Jianxin Guo, Hanfei Xie, Qing Zhu, Baoxi Yuan, Yujie Gao, Xiangyang Ma, Jialu Chen, Juan Tian

“…However, traditional SOD algorithms often face issues such as rough object boundaries, incomplete extraction of global image features, and insufficient attention to key areas. …”
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Improved and efficient EM channel estimation algorithm for MIMO-OFDM systems by XU Peng1, WANG Jin-kuan1, QI Feng2

“…For multiple-input multiple-output with orthogonal frequency division multiplexing（MIMO-OFDM） systems,the error floor（EF） phenomenon at high signal noise rate（SNR） was induced by the expectation maximum（EM） channel estimation algorithm.In addition,the data transmission efficiency was declined obviously with the increasing number of transmit antennas.According to these problems,an improved and efficient EM channel estimation algorithm was pro-posed.Firstly,an accurate and equivalent signal model was introduced to derive a modified EM algorithm,which im-proved the estimation performance at high SNR.Next,to enhance the data transmission efficiency and further the esti-mate performance of the proposed algorithm,phase orthogonal pilots sequences and joint estimation were carried out over multiple OFDM symbols respectively.Simulation results show that the proposed algorithm has better estimation performance and higher data transmission efficiency.…”
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Distance estimating algorithm based on gradient neighbors in wireless sensor networks by ZHENG Ming-cai1, 3, ZHANG Da-fang1, 2

“…A modified distance-estimating algorithm DV-GNN was presented to improve the precision of indirect dis- tance measuring in wireless sensor networks, theoretical basis was analyzed, and implementing process was given. …”
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Research on floating object classification algorithm based on convolutional neural network by Jikai Yang, Zihan Li, Ziyan Gu, Wei Li

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Unsupervised learning trajectory anomaly detection algorithm based on deep representation by Zhongqiu Wang, Guan Yuan, Haoran Pei, Yanmei Zhang, Xiao Liu

“…Third, these fused feature sequences are grouped into different clusters using a unsupervised clustering algorithm, and then segments which quite differ from others are detected as anomalies. …”
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Dynamic Weighted Symbiotic Organisms Search Algorithm for Global Optimization Problems by Pengjun Zhao, Sanyang Liu

“…The symbiotic organisms search (SOS) algorithm is a current effective meta-heuristic algorithm, which is been applied to solve various types of optimization problems. …”
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Research on Weld Identification and Defect Localization Based on an Improved Watershed Algorithm by Lingjiang Guo, Yong Yan, Junjie Cui, Zhongsi Xu

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Handover trigger time selection algorithm in heterogeneous wireless networks environment by Ji-lei YAN, Jian-dong LI, Lin-jing ZHAO

“…The handover trigger time selection problem for mobile user in the heterogeneous networks environment was discussed.Firstly,theoretical analysis of the handover trigger time selection was presented and the constraint which the optimal handover trigger time should satisfy was obtained.Then,an algorithm was proposed to predict the optimal handover trigger time based on the estimation of handover delay and the prediction of received signal strength.Simulation results show that this algorithm can effectively reduce the packet loss ratio and the probability of handover failure.…”
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A Novel Proprietary Internet Video Traffic Dataset Generation Algorithm by Tianhua Chen, Elans Grabs, Aleksandrs Ipatovs, Maria-Dolores Cano

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Optimization in Construction Management Using Adaptive Opposition Slime Mould Algorithm by Pham Vu Hong Son, Luu Ngoc Quynh Khoi

“…The purpose of this research study is to solve a four-objective optimization problem in the construction industry using a hybrid model that combines the slime mould algorithm (SMA) with opposition-based learning. This hybrid model is known as the adaptive opposition slime mould algorithm (AOSMA). …”
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An Improved Algorithm of Wireless Sensor Networks Routing Protocol Based on LEACH by Jinshen Weng, Huabiao Qin, Zongguo Zhang

“…One of the most popular research focuses of wireless sensor network is postponing the life cycle of sensor network as well as reducing energy consumption.An efficient clustering routing algorithm based on LEACH（low energy adaptive clustering hierarch）was presented，which is the representative of hierarchy based protocol in wireless sensor network.The residual energy，average energy and maximum energy are considered in this algorithm while electing the cluster header.It can also limit the number of members of each cluster.At the same time，it can produce the first cluster header among the cluster heads which will use the multi-hop mode to balance the load of network.The simulation results show that this improved algorithm can reduce the energy consumption，extend the network life cycle and ensure the load balance of the system.…”
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FDR coding and decoding algorithm for reliable transmission in underwater acoustic network by Lijuan WANG, Xiujuan DU, Chong LI

“…By analyzing the shortcomings of RLT coding and decoding algorithm,a filtering dimension reduction (FDR) algorithm was proposed,which eliminated the waiting time of the traditional decoding algorithm and achieves fast decoding.In addition,XOR operation between encoded packages effectively increased the number of one-degree encoded packages,and improved decoding probability while reducing transmission delay.An optimized degree distribution function for FDR decoding algorithm was proposed,which increased the proportion of two-degree,three-degree and four-degree encoded packages,further increased the probability of one-degree packet,so that speeded up the decoding progress.Simulation results with NS3 show that the decoding success probability of FDR algorithms higher than RLT algorithm.…”
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Overview of research on fiber nonlinear equalization algorithm based on artificial intelligence by Yajie LI, Yongli ZHAO, Shoudong LIU, Jie ZHANG

“…The necessity and importance of nonlinear equalization algorithm in optical transmission systems were outlined.The principle of classical nonlinear equalization algorithm was described,and the shortcomings and limitations of classical algorithms were presented.Combined with the status in recent years,four kinds of nonlinear equalization algorithms based on artificial intelligence were introduced in detail.These algorithms include artificial neural networks,support vector machine,unsupervised clustering and deep neural network.All the nonlinear equalization algorithms mentioned were compared in terms of performance,complexity,instantaneity and application flexibility.Finally,the future development trend of nonlinear equalization algorithm based on artificial intelligence was analyzed.…”
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Research on label propagation algorithm based on modularity maximization in the social network by Jing CHEN, Yun WAN

“…A kind of community detection method based on the combination of modularity and community structure attributes was proposed.Firstly,updating the whole network after communities merging every time could result in the high time complexity,therefore,introducing propagation distance parameter and “merger going after label propagation” was utilized to reduce time complexity.Secondly,CDMM-LPA algorithm was proposed by combing label propagation with community structure.Finally,empirical analysis on data networks verified the validity of the approaches.The experimental results show that the CDMM-LPA algorithm has a high modularity value and a more stable community structure while reducing the time complexity.…”
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Adaptive gradient algorithm for hybrid precoding in mmWave MIMO system by Yu ZHANG, Zhi ZHANG, Xiaodai DONG

“…To reduce the complexity of existing hybrid precoding algorithms based on alternating minimization (AltMin) and online learning via gradient descent with momentum in mmWave MIMO systems, aiming at the single-user scenario, the problem of designing the hybrid precoder was reconsidered and an equivalent single hidden layer neural network was proposed.Under the new architecture, the elements of the digital and analog precoder were equivalent to the connecting weights of a single hidden layer neural network, and their optimal solution could be obtained via the weights training method.Inspired by the back propagation (BP) algorithm in feed forward neural networks, an adaptive gradient (AG)-based BP algorithm for hybrid precoding was proposed.Furthermore, the proposed algorithm was extended to the multi-user scenario.The numerical results show that the proposed algorithm achieves approximately the same spectral efficiency as the fully-digital precoding in both the single-user and multi-user scenarios, while has lower complexity than the existing AltMin-based hybrid precoding algorithms and online learning hybrid precoding based on gradient descent with momentum.…”
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A Relevant Customer Identification Algorithm Based on the Internet Financial Platform by Guo Yangyudongnanxin

“…In order to improve the intelligent search capabilities of Internet financial customers, this paper proposes a search algorithm for Internet financial data. The proposed algorithm calculates the customers corresponding to the two selected financial platforms based on the candidate customer set selected from the seed dataset and combined with the restored social relationship. …”
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On-board Multi-User Detection Algorithm Based on Conditional Neural Process by Yilun LIU, Liang JIN, Jiali LI, Lidong ZHU

“…With the characteristics of all-terrain, all-weather and seamless coverage, satellite communications have become a potentially important part of 6G.An important prerequisite for achieving satellite intelligence is that the satellite have on-board processing capabilities.Multi-user detection (MUD) is a classic method of suppressing multiple access interference (MAI) in wireless communication, such as MMSE, Gaussian processregression (GPR) and other algorithms.Due to the inverse matrix required in the detection process, the algorithm complexity is usually cubic, and it is diff cult to directly apply to satellite platforms because of its limited processing capabilities.The conditional neural process combined the characteristics of the low complexity of the neural network and the data-eff cient of the Gaussian process.The neural network was used to parameterized the Gaussian process to avoided the inversion of the matrix, thereby reduced the computational complexity.The application of conditional neural process in MUD was studied.The simulation results showed that, while reduced complexity, conditional neural process also greatly improved the performance of bit error rate (BER).…”
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Data aggregation scheduling algorithm based on twice maximum independent set by Jian XU, Geng YANG, Zheng-yu CHEN, Hai-yong WANG, Zhen YANG

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