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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User grouping and power allocation algorithm for UAV-aided NOMA network by Guoquan LI, Jinzhao LIN, Yongjun XU, Zhengwen HUANG, Ting LIU

“…To improve the transmission flexibility of emergency communication scenarios,a joint user grouping and power allocation algorithm was proposed for UAV-aided non-orthogonal multiple access (NOMA) system.A sum-rate maximization resource allocation algorithm was formulated under the constraints of the maximum transmit power and the user grouping.To solve the non-convex problem,a graph-based user grouping algorithm was proposed to minimize the relative distance between the UAV and users.Based on the grouping result,the power allocation sub-problem was transformed into a convex one by using the auxiliary-variable approach.Simulation results demonstrate that the proposed algorithm has better performance in terms of sum rates.…”
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Voltage Profile Analysis in Smart Grids Using Online Estimation Algorithm by P. Raghavendra, Ramakrishna S. S. Nuvvula, Polamarasetty P. Kumar, Dattatraya N. Gaonkar, A. Sathoshakumar, Baseem Khan

“…This paper presents a real-time sensor-based online voltage profile estimation technique and coordinated Volt/VAR control in smart grids with distributed generator interconnection. An algorithm is developed for voltage profile estimation using real-time sensor remote terminal unit (RTU) which takes into account topological characteristics, such as radial structure and high R/X ratio, of the smart distribution grid with DG systems. …”
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A Temperature Field Based Routing Algorithm in Content-Centric Networking by Zonghai Liu, Peng Wang, Xiaohui Zhang, Feicai Jin

“…Aiming at the characteristics of CCN, a temperature field based routing（TFBR）algorithm was proposed. This scheme introduced the conception of temperature fields in physics into CCN and applied a finite element method（FEM）, which is one of numerical analysis techniques, to assign a temperature value to each node of CCN in a distributed way. …”
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Distributed energy efficient unequal clustering algorithm for wireless sensor networks by SHANG Feng-jun1, Mehran Abolhasan2, Tadeusz Wysocki3

“…A distributed energy-efficient unequal clustering （DEEUC） algorithm was proposed for wireless sensor net-works by research current routing algorithms. …”
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Using Improved XGBoost Algorithm to Obtain Modified Atmospheric Refractive Index by Yanbo Mai, Zheng Sheng, Hanqing Shi, Qixiang Liao

“…Besides, the improved XGBoost algorithm has the strongest learning and generalization capability to calculate missing values of atmospheric refractive index among the three algorithms. …”
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Algorithmic Generation of Parameterized Geometric Models of the Aortic Valve and Left Ventricle by Nikita Pil, Alex G. Kuchumov

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Comparisons of performances of structural variants detection algorithms in solitary or combination strategy. by De-Min Duan, Chinyi Cheng, Yu-Shu Huang, An-Ko Chung, Pin-Xuan Chen, Yu-An Chen, Jacob Shujui Hsu, Pei-Lung Chen

“…Interestingly, expanding the number of algorithms from three to five in the combination did not enhance performance, highlighting the efficiency of a well-chosen ensemble over a larger algorithmic pool.…”
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Video inter-frame tampering detection algorithm fusing multiple features by Hui XIAO, Bin WENG, Tianqiang HUANG, Han PU, Zehui HUANG

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A Two-Level Metaheuristic Algorithm for the Job-Shop Scheduling Problem by Pisut Pongchairerks

“…This paper proposes a novel two-level metaheuristic algorithm, consisting of an upper-level algorithm and a lower-level algorithm, for the job-shop scheduling problem (JSP). …”
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Combined AGADESN with DBSCAN Algorithm for Cluster Target Motion Intention Recognition by Xirui Xue, Shucai Huang, Daozhi Wei

“…In order to solve these problems, a joint algorithm of deep echo state network optimized by adaptive genetic algorithm (AGADESN) and DBSCAN clustering algorithm is proposed in this paper. …”
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Effects of Pooling Samples on the Performance of Classification Algorithms: A Comparative Study by Kanthida Kusonmano, Michael Netzer, Christian Baumgartner, Matthias Dehmer, Klaus R. Liedl, Armin Graber

“…RF mainly outperforms other investigated algorithms, while accuracy levels are comparable among all the remaining ones. …”
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