A Hybrid Ant Colony Optimization Algorithm for Multi-Compartment Vehicle Routing Problem by Ning Guo, Bin Qian, Rong Hu, Huai P. Jin, Feng H. Xiang

“…Ant colony optimization algorithm (ACO) has been recognized as an efficient method to solve the VRP and its variants. …”
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An Enhanced Differential Evolution Algorithm with Fast Evaluating Strategies for TWT-NFSP with SSTs and RTs by Rong Hu, Xing Wu, Bin Qian, Jian L. Mao, Huai P. Jin

“…This paper proposes an enhanced differential evolution algorithm with several fast evaluating strategies, namely, DE_FES, to minimize the total weighted tardiness objective (TWT) for the NFSP with SSTs and RTs. …”
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Apriori algorithm based prediction of students’ mental health risks in the context of artificial intelligence by You Fu, Fang Ren, Jiantao Lin

“…The model’s weight coefficients were optimized using the Quantum Particle Swarm Optimization (QPSO) algorithm. The model’s performance was evaluated using data from a mental health survey conducted among college students at a Chinese university.ResultsThe proposed Prophet-LSTM model demonstrated superior performance in predicting student mental health risks compared to other machine learning algorithms. …”
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The Memory Efficiency in a Receptionist Robot's Face Recognition System Using LBPH Algorithm by Endang Darmawan Yudi, Yesi Novaria Kunang, Ahmad Zarkasi

“…This research aims to develop a memory-efficient face recognition system for a receptionist robot using the Local Binary Patterns Histogram (LBPH) algorithm. Given the computational limitations of the Raspberry Pi, the system utilizes optimization techniques including grayscale conversion, noise reduction, and contrast adjustment to enhance processing efficiency. …”
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Constrained Multiobjective Equilibrium Optimizer Algorithm for Solving Combined Economic Emission Dispatch Problem by M. A. El-Shorbagy, A. A. Mousa

“…This research implements a recent evolutionary-based algorithm of equilibrium optimizer to resolve the constrained combined economic emission dispatch problem. …”
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The Methodological Algorithm of Forming Multimedia Foreign Language Communicative Competence of Secondary School Students by Akmaral Rakhman, Dana Shayakhmetova, Zhanar Kulekenova, Elmira Gerfanova, Aliya Ayazbayeva

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A New Subband Adaptive Filtering Algorithm for Sparse System Identification with Impulsive Noise by Young-Seok Choi

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Nonlinear Blind Source Separation Algorithm Using Glowworm Swarm Optimization with Baffle Effect by Pubo Huang, Yu Wei

“…According to the characteristics of glowworm swarm optimization（GSO）algorithm, to overcome the disadvantages of premature convergence, a new method called “baffle effect”was proposed. …”
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An Iterative Algorithm for the Generalized Reflexive Solution of the Matrix Equations AXB=E, CXD=F by Deqin Chen, Feng Yin, Guang-Xin Huang

“…An iterative algorithm is constructed to solve the linear matrix equation pair AXB=E, CXD=F over generalized reflexive matrix X. …”
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A reconstruction algorithm of service path for mobile Ad Hoc network based on SDN by Fang DONG, Ou LI, Youquan MO

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Retracted: A FJSSP Method Based on Dynamic Multi-Objective Squirrel Search Algorithm by International Journal of Antennas and Propagation

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An Audit Risk Model Based on Improved BP Neural Network Data Mining Algorithm by Wenjia Niu, Lihua Zhao, Peiyao Jia, Jiankun Chu

“…For auditors, it is a great challenge to use data mining algorithms, machine learning, artificial intelligence, and other emerging technologies to identify high-quality audit data from the vast amount of data of audited enterprises. …”
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Network selection algorithm in heterogeneous wireless networks to minimize the maximum residual service time by Bai DU, Hong-yan LI, Yan LONG

“…Due to the problem of how to select the most suitable access network for users at any time anywhere in heterogeneous wireless networks(HWN),a distributed algorithm to minimize the difference of residual service time between different access networks was proposed.The algorithm use the Lyapunov optimization to model the network and guarantee the stability of the network.Simulation results show that the proposed algorithm can decrease the rejection ratio and achieve a shorter queue length in access networks.…”
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EFFICIENT MALICIOUS NODE DETECTION IN WIRELESS SENSOR NETWORKS USING RABIN-KARP ALGORITHM by T Devapriya, V Ganesan, S Velmurugan

Subjects: “…malicious node detection, wireless sensor networks, rabin-karp algorithm, data integrity, energy efficiency…”
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Classification of Non-Seismic Tsunami Early Warning Level Using Decision Tree Algorithm by Elmo Juanara, Chi Yung Lam

“…Subsequently, a decision tree algorithm was employed to classify the warning levels. …”
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Energy-Efficient Clustering and Localization Technique Using Genetic Algorithm in Wireless Sensor Networks by Junfeng Chen, Samson Hansen Sackey, Joseph Henry Anajemba, Xuewu Zhang, Yurun He

“…Finally, the simulations are carried out to assess the performance of the proposed algorithm. Experimental results show that the proposed algorithm approximates the unknown node location and provides minimum localization error.…”
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Iterative algorithm on single-channel blind separation and decoding of co-frequency modulated signals by LIAO Can-hui, TU Shi-long, WAN Jian

“…An algorithm was proposed to exploit the codes in iterative single-channel blind separation and decoding of two co-frequency modulated signals with long-constraint channel codes.The output log-likelihood ratio（LLR） values of the decoder were used as a prior LLR fed back to the separator to improve the separation performance.Special emphases were laid on soft input soft output blind separation,maximum a posteriori（MAP） decoding and LLR interaction between separator and decoder.Simulation results show that the proposed algorithm can make a significant improvement in per-formance over the algorithms without iterations.For BPSK signals with（2,1,6） convolutional codes and random inter-leaving,a gain of about 2dB in signal-noise ratio can be obtained after two iterations.…”
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Research on Spatial Prediction of Precipitation in Guangdong Province Based on Gaussian Process Regression Algorithm by ZENG Xiongzhi, YU Chao

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TAGAN: an academic paper adversarial recommendation algorithm incorporating fine-grained semantic features by Jinyang SUN, Baisong LIU, Hao REN, Jiangbo QIAN

“…Academic paper recommendation aims to provide users with personalized paper resources.Collaborative filtering methods face the problems of highly sparse data and lack of negative samples.Considering the above challenges, an academic paper recommendation algorithm TAGAN（title and abstract GAN）which incorporated fine-grained semantic features was presented.Firstly, based on titles and abstracts provide abundant semantic features, convolutional neural networks (CNN) was used to extract the global features of the titles, a two-layer long and short-term memory network (LSTM) was built to model abstract words separately.At the same time, the attention mechanism was proposed to associate the title and the abstract semantically.Then, the semantic features of the paper were integrated into the recommendation framework based on generative adversarial network (GAN).The generative model will fit the user’s interest preferences and can effectively replace the negative sampling process.Finally,through the experimental comparison on the public dataset, TAGAN is better than the baseline models in all indicators, which verifies the effectiveness of TAGAN.…”
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Traffic Prediction of Space-Integrated-Ground Information Network Based on Improved LSTM Algorithm by Chengsheng PAN, Yufu WANG, Li YANG

“…The space-integrated-ground information network is easy to interrupt and the traffi c fl uctuation is not stable due to the problems of high traffi c burst and topological time-varying, which makes the traffi c prediction diffi cult much higher than the ground.In order to solve this problem, an improved LSTM algorithm was put forward.Firstly, the traffi c autocorrelation was judged by analyzd the infl uence of the lag variable of traffi c sequence on the predicted value; Secondly, the noise and breakpoint of the training set were eliminated by replacing the interruption with the predicted value; Finally, Dropout algorithm was used to reduce the impact of noise and neural network over fi tting, and accurately predict the traffi c data of the integrated intelligent network.The simulation results showed that in OPNET simulation environment, compared with other algorithms, the accuracy of this algorithm was improved by 59.21%, and the training speed of the algorithm was improved by 11.11%, which could provide eff ective data support for the overall scheduling of the integrated intelligent network.…”
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