MOANA: Multi-objective ant nesting algorithm for optimization problems by Noor A. Rashed, Yossra H. Ali, Tarik A. Rashid, Seyedali Mirjalili

“…This paper presents the Multi-Objective Ant Nesting Algorithm (MOANA), a novel extension of the Ant Nesting Algorithm (ANA), specifically designed to address multi-objective optimization problems (MOPs). …”
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Joint resource allocation algorithm for clustering cognitive Internet of things by Xin LIU

“…Cognitive Internet of things (CIoT) can improve spectrum utilization effectively through spectrum sensing and sharing,but spectrum sensing may generate overhead.Clustering CIoT was proposed to decrease sensing overhead,whose transmission rate could be improved through joint resource allocation.The network model and frame structure of the CIoT were proposed firstly,and the average transmission rate and interference power of the CIoT were deduced.Then,an optimization model was built to maximize the transmission rate through jointly optimizing the sensing time,sensing cluster head and transmission power,and a joint optimization algorithm was given to solve the optimization problem.Finally,the node clustering and cluster head selection algorithm of the CIoT was presented.The simulations show that the maximal transmission rate through joint resource allocation can be achieved and the transmission performance compared with the traditional schemes can be improved by the proposed scheme.…”
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Multi-view graph neural network for fraud detection algorithm by Zhuo CHEN, Miao ZHU, Junwei DU

“…Aiming at the problem that in the field of fraud detection, imbalance labels and lack of necessary connections between fraud nodes, resulting in fraud detection tasks not conforming to the hypothesis of homogeneity of graph neural networks, multi-view graph neural network for fraud detection (MGFD) algorithm was proposed.First, A structure-independent encoder was used to encode the attributes of nodes in the network to learn the difference between the fraud node and the normal node.The hierarchical attention mechanism was designed to integrate the multi-view information in the network, and made full use of the interaction information between different perspectives in the network to model the nodes on the basis of learning differences.Then, based on the data imbalance ratio sampled subgraph, the sample was constructed according to the connection characteristics of fraud nodes for classification, which solved the problem of imbalance sample labels.Finally, the prediction label was used to identify whether a node is fraudulent.Experiments on real-world datasets have shown that the MGFD algorithm outperforms the comparison method in the field of graph-based fraud detection.…”
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Design of DBA algorithm in EPON upstream channel in support of SLA by WANG Dong, QIU Kun, WANG Li-cun

“…Based on the SLA （service level agreement） in access network, the inherent deficiencies of two classical DBA algorithms: IPACT and Cyclic DBA in EPON to support multi-user types were analyzed. …”
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Bearing Defect Classification Algorithm Based on Autoencoder Neural Network by Manhuai Lu, Yuanxiang Mou

“…Comparative experiments show that the neural network can effectively complete feature selection and substantially improve classification accuracy while avoiding the laborious algorithm of the conventional method.…”
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Chaotic Puma Optimizer Algorithm for controlling wheeled mobile robots by Mohamed Kmich, Nawal El Ghouate, Ahmed Bencharqui, Hicham Karmouni, Mhamed Sayyouri, S.S. Askar, Mohamed Abouhawwash

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WLAN indoor positioning algorithm based on skewness-kurtosis testing by Zhen-long SONG, Gang-yi JIANG, Chao HUANG, Mei YU, Jia-le ZHANG

“…Focused on the issues that large positioning errors produced by the inconsistency of received signal strength (RSS)sample population distributions under indoor wireless local area network (WLAN),an indoor positioning algorithm based on skewness-kurtosis testing was proposed.By using the testing method of skewness and kurtosis,whether the RSS samples come from the normal population or not was checked.The distribution functions of the samples accepting null hypothesis were approximated with normal distribution,and the probability density functions of the samples refusing null hypothesis were estimated by kernel function.Experimental results show that the proposed algorithm leads to a 15 percent improvement over the previous methods.Moreover,the proposed algorithm can significantly reduce the workload of the off-line phase at the same positioning accuracy.…”
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Key distribution and recovery algorithm based on Shamir's secret sharing by Hui-gui RONG, Jin-xia MO, Bing-guo CHANG, Guang SUN, Fei LONG

“…The case of secret sharing problem was discussed based on Shamir's secret sharing scheme and reconstructs the secret by introducing a linear combination of shadows—Lagrange factor. Then, the improved algorithm of key distribu-tion and recovery was proposed and extended to a multi-secret sharing scheme. …”
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An Enhanced -Means Clustering Algorithm for Pattern Discovery in Healthcare Data by Ramzi A. Haraty, Mohamad Dimishkieh, Mehedi Masud

“…Mainly, we study k -means clustering algorithms on large datasets and present an enhancement to k -means clustering, which requires k or a lesser number of passes to a dataset. …”
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Improved Epidemic algorithm based on trust mechanism in opportunistic networks by Guang-hua ZHANG, Shao-bo PANG, Yao-hong YANG, Zhen-guo CHEN

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Research on simple query algorithm during mobile terminal disconnection by Ru-bing LIANG, Qiong LIU

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Reconstruction algorithm for block compressed sensing based on variation model by Jian CHEN, xiong SUKai, zhi YANGXiu, kui ZHENGMing, qun LINLi

“…The algorithms for block compressed sensing based on total variation and mixed variation (abbreviated as BCS-TV and BCS-MV) models were proposed to improve the performance of current reconstruction algorithms for the block-based compressed sensing. …”
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Determination of the FIFO-stack size for the algorithm of the image region growing by V. Yu. Tsviatkou

“…The aim of the work is to derive an expression that allows determining the size of the FIFO-stack for storing the coordinates of adjacent pixels depending on the image size for the segmentation algorithm based on region growing. The FIFO stack, organized on the principle of a ring multi-bit shift register, is considered. …”
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Learning attribute network algorithm based on high-order similarity by Shaoqing WU, Yihong DONG, Xiong WANG, Yan CAO, Yu XIN

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A Virtual Network Mapping Algorithm Based on Approaching Principle by Sheng Huang, Chuanchuan Wu, Xiaofei Yang, Hui Wang, Wei Zhang

“…On the basis of two stages virtual network mapping algorithm, pointing at the defects of the blind node mapping of existing greedy strategy, a virtual network mapping algorithm based on approaching principle was proposed. …”
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An Improved 3D Localization Algorithm for the Wireless Sensor Network by Yan Xu, Yi Zhuang, Jing-jing Gu

“…Aiming at the existing problems of the current 3D localization algorithms, an improved 3D localization algorithm based on Degree of Coplanarity (3D-IDCP) is proposed. …”
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Path Planning of Manipulators with the Improved RRT Algorithm in Complex Environment by Zhou Qinyuan, Zhang Lei, Deng Yueping, Zhang Chen, Lu Rirong, Hu Xianzhe

“…Aiming at the problems of the standard rapidly exploring random tree (RRT) algorithm in a complex environment, such as blind expansion, falling into local search, easy planning failure, low sampling success rate, and long paths, an adaptive goal-oriented strategy combined with an alternative strategy for regional sampling and an improved RRT algorithm of the greedy pruning strategy was proposed. …”
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Low-complexity ATPM-VSIMM algorithm with adaptive model parameters by Hao ZENG, Wangqiang MU, Yang JIANG, Shunping YANG

“…Aiming at the problem that for maneuvering target tracking, the accuracy of tracking degraded in interacting multiple model algorithms due to the fixed model sets and the fixed transition probability matrix, a low-complexity ATPM-VSIMM algorithm was proposed, which could update the model parameters adaptively.The maneuvering situation of the target was judged according to the innovation changes of the system, and the state noise of the model sets was adjusted to realize the adaptive update of the model sets.Then, the more accurate transition probability matrix was computed through the change of the model posterior probability and the inter-model switching relationship.Therefore, the matching degree between the system motion model and the target motion trajectory was improved.Finally, the high filtering accuracy and the fast response speed of the tracking system were guaranteed.The effectiveness of the proposed algorithm was verified through three aspects that are the initial value of the model posterior probability, the initial value of the transition probability matrix, and the state noise.Simulation results demonstrate that the filtering accuracy of the ATPM-VSIMM algorithm is improved about 8% compared with the existing algorithms.…”
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Time-optimal Trajectory Planning of Robot based on Breed Algorithm by Yu Rui, Wang Chengjun, Guo Yongcun, Zhang Yuping

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A Trust Value-Based Spectrum Allocation Algorithm in CWSNs by Qing-Qi Pei, Zi Li, Li-Chuan Ma

“…This algorithm uses “the last diminisher” algorithm, which appears in fair division models. …”
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