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Relay Selection for Cooperative NOMA Systems Based on the DQN Algorithm 认领 引用
1
作者 Ying Lin Yongwei Xiong +2 位作者 Xingbo Gong Sifei Zhang Yinhang Tian 《Journal of Beijing Institute of Technology》 EI CAS 2025年第3期303-315,共13页
In this study,a solution based on deep Q network(DQN)is proposed to address the relay selection problem in cooperative non-orthogonal multiple access(NOMA)systems.DQN is particularly effective in addressing problems w... In this study,a solution based on deep Q network(DQN)is proposed to address the relay selection problem in cooperative non-orthogonal multiple access(NOMA)systems.DQN is particularly effective in addressing problems within dynamic and complex communication environ-ments.By formulating the relay selection problem as a Markov decision process(MDP),the DQN algorithm employs deep neural networks(DNNs)to learn and make decisions through real-time interactions with the communication environment,aiming to minimize the system’s outage proba-bility.During the learning process,the DQN algorithm progressively acquires channel state infor-mation(CSI)between two nodes,thereby minimizing the system’s outage probability until a sta-ble level is reached.Simulation results show that the proposed method effectively reduces the out-age probability by 82%compared to the two-way relay selection scheme(Two-Way)when the sig-nal-to-noise ratio(SNR)is 30 dB.This study demonstrates the applicability and advantages of the DQN algorithm in cooperative NOMA systems,providing a novel approach to addressing real-time relay selection challenges in dynamic communication environments. 展开更多
关键词 deep Q network(DQN) cooperative non-orthogonal multiple access(NOMA) relay selection outage probability
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Memory-Occupied Routing Algorithms for Quantum Relay Networks 认领 引用
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作者 Jiangyuan Yao Kaiwen Zou +4 位作者 Zheng Jiang Shuhua Weng Deshun Li Yahui Li Xingcan Cao 《Computers, Materials & Continua》 SCIE EI 2023年第6期5929-5946,共18页
Quantum transmission experiments have shown that the success-ful transmission rate of entangled quanta in optical fibers decreases expo-nentially.Although current quantum networks deploy quantum relays to establish lo... Quantum transmission experiments have shown that the success-ful transmission rate of entangled quanta in optical fibers decreases expo-nentially.Although current quantum networks deploy quantum relays to establish long-distance connections,the increase in transmission distance and entanglement switching costs still need to be considered when selecting the next hop.However,most of the existing quantum network models prefer to consider the parameters of the physical layer,which ignore the influence factors of the network layer.In this paper,we propose a meshy quantum network model based on quantum teleportation,which considers both net-work layer and physical layer parameters.The proposed model can reflect the realistic transmission characteristics and morphological characteristics of the quantum relay network.Then,we study the network throughput of different routing algorithms with the same given parameters when multiple source-destination pairs are interconnected simultaneously.To solve the chal-lenges of routing competition caused by the simultaneous transmission,we present greedy memory-occupied algorithm Q-GMOA and random memory-occupied algorithm Q-RMOA.The proposed meshy quantum network model and the memory-occupied routing algorithms can improve the utilization rate of resources and the transmission performance of the quantum network.And the evaluation results indicate that the proposed methods embrace a higher transmission rate than the previous methods with repeater occupation. 展开更多
关键词 Quantum relay network routing algorithm quantum memory
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A Niche-Based Evolutionary Tabu Search Algorithm for Optimal Coordination of Protection Relays in Power Networks 认领 引用
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作者 YUAN Rongxiang ZOU Xiufen XU Chunlin 《Wuhan University Journal of Natural Sciences》 CAS 2009年第3期215-222,共8页
In this paper, refusal of operation and the degree of constraint violation are considered as one part of the objective function for optimizing the protection relay setting coordination of over current relays in power ... In this paper, refusal of operation and the degree of constraint violation are considered as one part of the objective function for optimizing the protection relay setting coordination of over current relays in power systems; a new expression of objective function in this optimization problem is proposed. To combine the advantages of both Tabu search （TS） and evolutionary algorithms （EAs）, a new niche-based evolutionary Tabu search algorithm （named NETS） is presented to solve this optimization problem. Moreover, in two cases of power networks, comparisons between NETS and two published algorithms are given. Experimental results show the expression of the objective function for protection relay setting is feasible and reasonable, and the proposed algorithm NETS exhibits a good performance. 展开更多
关键词 evolutionary algorithm Tabu search power system protection relay coordination
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Optimization of Truss Structures Using Nature-Inspired Algorithms with Frequency and Stress Constraints 认领 引用 被引量：1
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作者 Sanjog Chhetri Sapkota Liborio Cavaleri +3 位作者 Ajaya Khatri Siddhi Pandey Satish Paudel Panagiotis G.Asteris 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第1期436-464,共29页
Optimization is the key to obtaining efficient utilization of resources in structural design.Due to the complex nature of truss systems,this study presents a method based on metaheuristic modelling that minimises stru... Optimization is the key to obtaining efficient utilization of resources in structural design.Due to the complex nature of truss systems,this study presents a method based on metaheuristic modelling that minimises structural weight under stress and frequency constraints.Two new algorithms,the Red Kite Optimization Algorithm(ROA)and Secretary Bird Optimization Algorithm(SBOA),are utilized on five benchmark trusses with 10,18,37,72,and 200-bar trusses.Both algorithms are evaluated against benchmarks in the literature.The results indicate that SBOA always reaches a lighter optimal.Designs with reducing structural weight ranging from 0.02%to 0.15%compared to ROA,and up to 6%–8%as compared to conventional algorithms.In addition,SBOA can achieve 15%–20%faster convergence speed and 10%–18%reduction in computational time with a smaller standard deviation over independent runs,which demonstrates its robustness and reliability.It is indicated that the adaptive exploration mechanism of SBOA,especially its Levy flight–based search strategy,can obviously improve optimization performance for low-and high-dimensional trusses.The research has implications in the context of promoting bio-inspired optimization techniques by demonstrating the viability of SBOA,a reliable model for large-scale structural design that provides significant enhancements in performance and convergence behavior. 展开更多
关键词 Optimization truss structures nature-inspired algorithms meta-heuristic algorithms red kite opti-mization algorithm secretary bird optimization algorithm
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An Iterative Detection/Decoding Algorithm of Correlated Sources for the LDPC-Based Relay Systems 认领 引用 被引量：1
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作者 Haiqiang Chen Hang Cao +3 位作者 Xiangcheng Li Youming Sun Haibin Wan Tuanfa Qin 《China Communications》 SCIE CSCD 2017年第9期190-198,共9页
An iterative detection/decoding algorithm of correlated sources for the LDPC-based relay systems is presented. The signal from the source-destination(S-D) link is formulated as a highly correlated counterpart from the... An iterative detection/decoding algorithm of correlated sources for the LDPC-based relay systems is presented. The signal from the source-destination(S-D) link is formulated as a highly correlated counterpart from the relay-destination(R-D) link. A special XOR vector is defined using the correlated hard decision information blocks from two decoders and the extrinsic information exchanged between the two decoders is derived by the log-likelihood ratio(LLR) associated with the XOR vector. Such the decoding scheme is different from the traditional turbo-like detection/decoding algorithm, where the extrinsic information is computed by the side information and the soft decoder outputs. Simulations show that the presented algorithm has a slightly better performance than the traditional turbo-like algorithm(Taking the(255,175) EG-LDPC code as an example, it achieves about 0.1 dB performance gains aroundBLER=10-4). Furthermore, the presented algorithm requires fewer computing operations per iteration and has faster convergence rate. For example, the average iteration of the presented algorithm is 33 at SNR=1.8 dB, which is about twice faster than that of the turbo-like algorithm, when decoding the(961,721) QC-LDPC code. Therefore, the presented decoding algorithm of correlated sources provides an alternative decoding solution for the LDPC-based relay systems. 展开更多
关键词 correlated sources iterative de-coding LDPC codes relay channel
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Joint Source and Relay Precoding/Beamforming Algorithm for OFDM Multi-user Cooperative Relay Systems 认领 引用 被引量：1
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作者 ZHOU Dong-yue HU Bin-jie 《Journal of Donghua University(English Edition)》 EI CAS 2014年第5期723-726,共4页
In order to reduce the feedback load of multi-user orthogonal frequency division multiplexing （ OFDM ） -based wireless systems, a practiral limited bits feedback precoding algorithm is proposed with direct source-de... In order to reduce the feedback load of multi-user orthogonal frequency division multiplexing （ OFDM ） -based wireless systems, a practiral limited bits feedback precoding algorithm is proposed with direct source-destination link based on amplify-and- forward cooperative relay network under frequency selective fading channels. Using joint minimum mean square error（MMSE） filter, the receiving decoding matrix is designed for each user in the paper. Source precoding （beamforming） matrix is optimized with convex function of weight mean square error （MSE）. Relay precoding matrix is obtained under MSE decomposition and convex optimization. The precoding matrix index is fed back for clustered subcarrier of OFDM with limited feedback. Then using interpolation algorithm, all precoding matrices are achieved at base station （BS） and relay nodes. Simulations indicate the effectiveness of the proposed limited feedback joint precoding and beam_formlng design. The proposed method can improve bit error rate （BER） performance and obtain better sum-rate performance in contrast to existing algorithms. It displays the BER performance is close to that of the unquantified precoding feedback method. 展开更多
关键词 relay multi-user precoding mean square error (MSE) feedback bits dual hop
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Greedy Algorithm Applied to Relay Selection for Cooperative Communication Systems in Amplify-and-Forward Mode 认领 引用 被引量：1
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作者 Cheng-Ying Yang Yi-Shan Lin Jyh-Horng Wen 《Journal of Electronic Science and Technology》 CAS 2014年第1期49-53,共5页
Using a relaying system to provide spatial diversity and improve the system performance is a tendency in the wireless cooperative communications. Amplify-and-forward （AF） mode with a low complexity is easy to be imp... Using a relaying system to provide spatial diversity and improve the system performance is a tendency in the wireless cooperative communications. Amplify-and-forward （AF） mode with a low complexity is easy to be implemented. Under the consideration of cooperative communication systems, the scenario includes one information source, M relay stations and N destinations. This work proposes a relay selection algorithm in the Raleigh fading channel. Based on the exhaustive search method, easily to realize, the optimal selection scheme can be found with a highly complicated calculation. In order to reduce the computational complexity, an approximate optimal solution with a greedy algorithm applied for the relay station selection is proposed. With different situations of the communication systems, the performance evaluation obtained by both the proposed algorithm and the exhaustive search algorithm are given for comparison. It shows the proposed algorithm could provide a solution approach to the optimal one. 展开更多
关键词 Amplify-and-forward mode cooperativecommunication exhaustive search greedy algorithm,relay selection.
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RELAY ALGORITHM BASED ON NETWORK CODING IN WIRELESS LOCAL NETWORK 认领 引用
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作者 Wang Qi Wang Qingshan Wang Dongxue 《Journal of Electronics(China)》 2013年第1期75-82,共8页
The network coding is a new technology in the field of information in 21st century. It could enhance the network throughput and save the energy consumption, and is mainly based on the single transmission rate. However... The network coding is a new technology in the field of information in 21st century. It could enhance the network throughput and save the energy consumption, and is mainly based on the single transmission rate. However, with the development of wireless network and equipment, wireless local network MAC protocols have already supported the multi-rate transmission. This paper investigates the optimal relay selection problem based on network coding. Firstly, the problem is formulated as an optimization problem. Moreover, a relay algorithm based on network coding is proposed and the transmission time gain of our algorithm over the traditional relay algorithm is analyzed. Lastly, we compare total transmission time and the energy consumption of our proposed algorithm, Network Coding with Relay Assistance (NCRA), Transmission Request (TR), and the Direct Transmission (DT) without relay algorithm by adopting IEEE 802.11b. The simulation results demonstrate that our algorithm that improves the coding opportunity by the cooperation of the relay nodes leads to the transmission time decrease of up to 17% over the traditional relay algorithms. 展开更多
关键词 Relay algorithm Wireless local network Multi-rate Network coding
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Short-Term Relay Quality Prediction Algorithm Based on Long and Short-Term Memory 认领 引用 被引量：3
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作者 XUE Wendong CHAI Yuan +2 位作者 LI Qigan HONG Yongqiang ZHENG Gaofeng 《Instrumentation》 2018年第4期46-54,共9页
The fraction defective of semi-finished products is predicted to optimize the process of relay production lines, by which production quality and productivity are increased, and the costs are decreased. The process par... The fraction defective of semi-finished products is predicted to optimize the process of relay production lines, by which production quality and productivity are increased, and the costs are decreased. The process parameters of relay production lines are studied based on the long-and-short-term memory network. Then, the Keras deep learning framework is utilized to build up a short-term relay quality prediction algorithm for the semi-finished product. A simulation model is used to study prediction algorithm. The simulation results show that the average prediction absolute error of the fraction is less than 5%. This work displays great application potential in the relay production lines. 展开更多
关键词 Relay Production Line Long and Short-Term Memory Network Keras Deep Learning Framework Quality Prediction
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A Novel Hybrid Sine Cosine-Flower Pollination Algorithm for Optimized Feature Selection 认领 引用
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作者 Sumbul Azeem Shazia Javed +3 位作者 Farheen Ibraheem Uzma Bashir Nazar Waheed Khursheed Aurangzeb 《Computers, Materials & Continua》 SCIE EI 2026年第5期1916-1930,共15页
Data serves as the foundation for training and testing machine learning and artificial intelligencemodels.The most fundamental part of data is its attributes or features.The feature set size changes from one dataset t... Data serves as the foundation for training and testing machine learning and artificial intelligencemodels.The most fundamental part of data is its attributes or features.The feature set size changes from one dataset to another.Only the relevant features contributemeaningfully to classificationaccuracy.The presence of irrelevant features reduces the system’s effectiveness.Classification performance often deteriorates on high-dimensional datasets due to the large search space.Thus,one of the significant obstacles affecting the performance of the learning process in the majority of machine learning and data mining techniques is the dimensionality of the datasets.Feature selection(FS)is an effective preprocessing step in classification tasks.The aim of applying FS is to exclude redundant and unrelated features while retaining the most informative ones to optimize classification capability and compress computational complexity.In this paper,a novel hybrid binary metaheuristic algorithm,termed hSC-FPA,is proposed by hybridizing the Flower Pollination Algorithm(FPA)and the Sine Cosine Algorithm(SCA).Hybridization controls the exploration capacity of SCA and the exploitation behavior of FPA to maintain a balanced search process.SCA guides the global search in the early iterations,while FPA’s local pollination refines promising solutions in later stages.A binary conversion mechanism using a threshold function is implemented to handle the discrete nature of the feature selection problem.The functionality of the proposed hSC-FPA is authenticated on fourteen standard datasets from the UCI repository using the K-Nearest Neighbors(K-NN)classifier.Experimental results are benchmarked against the standalone SCA and FPA algorithms.The hSC-FPA consistently achieves higher classification accuracy,selects a more compact feature subset,and demonstrates superior convergence behavior.These findings support the stability and outperformance of the hybrid feature selection method presented. 展开更多
关键词 Classification algorithms feature selection process flower pollination algorithm hybrid model metaheuristics multi-objective optimization search algorithm sine cosine algorithm
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Application of Evolutionary Algorithm for Optimal Directional Overcurrent Relay Coordination 认领 引用 被引量：1
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作者 N. M. Stenane K. A. Folly 《Journal of Computer and Communications》 2014年第9期103-111,共9页
In this paper, two Evolutionary Algorithms (EAs) i.e., an improved Genetic Algorithms (GAs) and Population Based Incremental Learning (PBIL) algorithm are applied for optimal coordination of directional overcurrent re... In this paper, two Evolutionary Algorithms (EAs) i.e., an improved Genetic Algorithms (GAs) and Population Based Incremental Learning (PBIL) algorithm are applied for optimal coordination of directional overcurrent relays in an interconnected power system network. The problem of coordinating directional overcurrent relays is formulated as an optimization problem that is solved via the improved GAs and PBIL. The simulation results obtained using the improved GAs are compared with those obtained using PBIL. The results show that the improved GA proposed in this paper performs better than PBIL. 展开更多
关键词 Evolutionary Algorithms GA Learning Rate Optimal Relay Coordination PBIL
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Spatial channel pairing-based maximum ratio combining algorithm for cooperative relay networks 认领 引用
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作者 胡锦松 束锋 +4 位作者 许正文 阙非 黄晓晖 刘婷婷 陆锦辉 《Journal of Southeast University(English Edition)》 EI CAS 2016年第2期146-150,共5页
To improve the reliable performance of information transmission in cooperative relay networks, the scheme of the max-rate spatial channel pairing （SCP） based on maximum ratio combining （MRC） is proposed. The schem... To improve the reliable performance of information transmission in cooperative relay networks, the scheme of the max-rate spatial channel pairing （SCP） based on maximum ratio combining （MRC） is proposed. The scheme includes three steps： channel phase cancellation, MRC, and SCP. Eventually, the solution of the scheme is modeled as convex optimization. The objective function of the optimization problem is to maximize the transmission rate and the optimization variable is the strategy of pairing between the uplink spatial sub-channels of each user and the corresponding downlink spatial ones. The theorem of the arrangement inequalities is adopted to obtain the approximate closed-form solution of the optimal pairing for this convex optimization. Simulation results demonstrate that compared to the existing distributed space-time block coding and coherent combined schemes without SCP, the proposed max-rate SCP plus MRC algorithm achieves appreciable improvements in symbol error rate in medium and high signal-to-noise ratio regimes. The achievable performance gain is due to the use of maxrate SCP. 展开更多
关键词 relay maximum ratio combining coherentcombining spatial channel pairing distributed space-timeblock coding
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MATLAB fitting for overcurrent relay and a new digital algorithm study 认领 引用
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作者 张小鸣 《Journal of Coal Science & Engineering(China)》 2005年第2期90-94,共5页
The overcurrent (OC) protection limit is set usually accorging to a OC protection setting table on digital integrated protection equipment in mine explode isolation high voltage (HV) vacuum switch. For digital integra... The overcurrent (OC) protection limit is set usually accorging to a OC protection setting table on digital integrated protection equipment in mine explode isolation high voltage (HV) vacuum switch. For digital integrated protection equipment, OC protection setting table must be converted to be a microcomputer algorithm. This paper first intro-duced a method of the fitting OC protection setting table to be OC relay inverse time characteristics equations using MATLAB least square fitting. On the basis of analyzing these fitting equations, a notion, “integral limit rate” was put forward initially and a OC in-verse time digital algorithm was developed. MATLAB simulation results and a digital signal processor (DSP) based digital integrated protection equipment running test indicate that this algorithm has less calculation amount, less taking up memory, high control accuracy, implements the no-grade setting of OC delay values, suits for all kinds of low-middle mi-crocomputer system implementation. 展开更多
关键词 overcurrent relay inverse time fit integral limit
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Propagation Alongside Crossover:An Evolutionary Algorithm for Continuous Optimization and Feature Selection 认领 引用
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作者 Najibeh Farzi-Veijouyeh Vahideh Sahargahi Neda Matin 《Journal of Bionic Engineering》 SCIE EI CSCD 2026年第2期1112-1175,共64页
Researchers continuously advance optimization algorithms,recognizing that no meta-heuristic can solve all problem types,as stated by the No Free Lunch theorem.This paper introduces the Propagation alongside Crossover(... Researchers continuously advance optimization algorithms,recognizing that no meta-heuristic can solve all problem types,as stated by the No Free Lunch theorem.This paper introduces the Propagation alongside Crossover(PAC)algorithm to address continuous optimization challenges.The primary goal of PAC is to structure the algorithmic phases in a manner that achieves a robust balance between exploration and exploitation through appropriately designed mechanisms at each stage.PAC simultaneously leverages the benefits of propagation,crossover,and mutation.Three independent operators are defined to generate new candidate solutions separately,and a novel selection strategy allows individuals produced by each operator,along with members of the current population,to independently enter the next generation.This design preserves population diversity,prevents all individuals from converging toward a single point,and enhances the algorithm’s ability to explore the solution space effectively.A key innovation of PAC is its three-mode propagation mechanism,which comprises local search,linear propagation toward the target point,and tear-drop shaped propagation toward the target point.Tear-drop propagation provides a precise and adaptive search around promising solutions,increasing diversity and preventing entrapment in local optima.The target point is typically set as the global optimum;however,when propagating the global optimum itself,a random point is used as the target to further enhance exploration and escape from local optima.The initial population is generated using chaotic mapping to ensure broad coverage of the search space.PAC was rigorously evaluated on 51 benchmark functions and three engineering problems,considering scalability,convergence,sensitivity,and computational efficiency.Comparative analyses with established optimization algorithms demonstrate PAC’s superior performance,as confirmed by Wilcoxon signed-rank and Friedman statistical tests.Furthermore,PAC was applied as a feature selection method on four diverse datasets,achieving substantial dimensionality reduction while outperforming comparative methods in classification accuracy.These results highlight PAC’s versatility,robustness,and practical effectiveness. 展开更多
关键词 Optimization algorithms Meta-heuristic algorithms Continuous optimization Propagation alongside crossover algorithm Intrusion detection
A Compound Relay Protection Operation Criterion Based on Kirchhoff’s Current Law and Abnormal Data Detecting Algorithm 认领 引用
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作者 Xuze Zhang Xiaoning Kang +2 位作者 Hao Wang Qiyue Huang Yali Ma 《Energy and Power Engineering》 2017年第4期88-94,共7页
A compound relay protection operation criterion is proposed based on Kirchhoff’s Current Law and abnormal data detecting algorithm. The abnormal data detecting algorithm are proposed after deep research on the abnorm... A compound relay protection operation criterion is proposed based on Kirchhoff’s Current Law and abnormal data detecting algorithm. The abnormal data detecting algorithm are proposed after deep research on the abnormal data properties. The current transformer status monitoring system and current phase angle detecting system is introduced. A simulation model containing different power sources and loads is established in Matlab. The simulation results show that this compound criterion can work quickly and reliably in all conditions. 展开更多
关键词 Relay Protection Abnormal Data Smart Substation
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Low-complexity APSK demodulation algorithm based on K-means clustering in LEO satellite communication systems 认领 引用
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作者 Guangfu Wu Xiangrui Meng +1 位作者 Changlin Chen Biqun Xiang 《Digital Communications and Networks》 SCIE EI CSCD 2026年第2期343-353,共11页
Amplitude Phase Shift Keying(APSK)is more suitable for the nonlinear channels of Low Earth Orbit(LEO)satellite communication systems compared to Quadrature Amplitude Modulation(QAM).To tackle challenges posed by Direc... Amplitude Phase Shift Keying(APSK)is more suitable for the nonlinear channels of Low Earth Orbit(LEO)satellite communication systems compared to Quadrature Amplitude Modulation(QAM).To tackle challenges posed by Direct Current(DC)interference and high demodulation complexity,we propose an APSK demodulation algorithm based on K-means clustering.Initially,static DC components are calculated and removed from the received APSK signals.Subsequently,the estimated APSK constellation points serve as initial centers for K-means clustering.These centers are refined through the K-means process and act as theoretical APSK constellation points for the Max-Log-MAP demodulation algorithm,effectively eliminating residual DC.We then introduce a low-complexity APSK demodulation algorithm that utilizes the symmetry of constellation points along with the Euclidean distance between DC-eliminated signals and these constellation points to minimize the set of constellation points.Simulation results indicate that for 32-APSK,our proposed demodulation submodule reduces computational complexity to approximately one-third that of the Max-Log-MAP algorithm while improving Bit Error Rate(BER)performance by about 0.23 dB.Furthermore,end-to-end simulation experiments conducted within LEO satellite communication systems demonstrate that our approach not only maintains this complexity advantage but also enhances BER performance by approximately 1.1 dB. 展开更多
关键词 DC elimination APSK demodulation LEO satellite communication K-means algorithm Max-Log-MAP algorithm
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A Quantum-Inspired Algorithm for Clustering and Intrusion Detection 认领 引用
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作者 Gang Xu Lefeng Wang +5 位作者 Yuwei Huang Yong Lu Xin Liu Weijie Tan Zongpeng Li Xiu-Bo Chen 《Computers, Materials & Continua》 SCIE EI 2026年第4期1180-1215,共36页
The Intrusion Detection System(IDS)is a security mechanism developed to observe network traffic and recognize suspicious or malicious activities.Clustering algorithms are often incorporated into IDS;however,convention... The Intrusion Detection System(IDS)is a security mechanism developed to observe network traffic and recognize suspicious or malicious activities.Clustering algorithms are often incorporated into IDS;however,conventional clustering-based methods face notable drawbacks,including poor scalability in handling high-dimensional datasets and a strong dependence of outcomes on initial conditions.To overcome the performance limitations of existing methods,this study proposes a novel quantum-inspired clustering algorithm that relies on a similarity coefficient-based quantum genetic algorithm(SC-QGA)and an improved quantum artificial bee colony algorithm hybrid K-means(IQABC-K).First,the SC-QGA algorithmis constructed based on quantum computing and integrates similarity coefficient theory to strengthen genetic diversity and feature extraction capabilities.For the subsequent clustering phase,the process based on the IQABC-K algorithm is enhanced with the core improvement of adaptive rotation gate and movement exploitation strategies to balance the exploration capabilities of global search and the exploitation capabilities of local search.Simultaneously,the acceleration of convergence toward the global optimum and a reduction in computational complexity are facilitated by means of the global optimum bootstrap strategy and a linear population reduction strategy.Through experimental evaluation with multiple algorithms and diverse performance metrics,the proposed algorithm confirms reliable accuracy on three datasets:KDD CUP99,NSL_KDD,and UNSW_NB15,achieving accuracy of 98.57%,98.81%,and 98.32%,respectively.These results affirm its potential as an effective solution for practical clustering applications. 展开更多
关键词 Intrusion detection clustering quantum artificial bee colony algorithm K-means quantum genetic algorithm
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A Metaheuristic Football Optimization Algorithm Integrated with Large Language Models for Automated Seismic Time-Series Modeling 认领 引用
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作者 Amal H.Alharbi Marwa M.Eid +2 位作者 Nima Khodadadi Ebrahim A.Mattar Sayed Elkenawy 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第5期947-987,共41页
Seismic time series forecasting remains challenging due to the nonlinearity,non-stationarity,and noise of earthquake data,and because deep learning models are sensitive to preprocessing and hyperparameter settings.Alt... Seismic time series forecasting remains challenging due to the nonlinearity,non-stationarity,and noise of earthquake data,and because deep learning models are sensitive to preprocessing and hyperparameter settings.Although recent studies have improved neural architectures and optimization techniques,preprocessing is often treated as a fixed or manually designed stage,with limited integration into model optimization.To address this,this paper proposes an integrated,data-driven modelling framework that combines guided preprocessing with systematic hyperparameter optimization for seismic prediction,specifically forecasting earthquake magnitude from seismic catalog time-series data,with experiments conducted on Canadian seismic records.The method uses a Large Language Model to guide data preparation and feature engineering,rather than fully automate them,and applies deep learning-based forecasting with the N-HITS architecture,optimized via metaheuristic-assisted feature selection and hyperparameter tuning.The Football Optimization Algorithm(FbOA),employed as a metaheuristic optimization strategy in this study,is evaluated and compared with several well-known optimizers under identical conditions.The results show significant performance gains,with FbOA achieving superior accuracy,robustness,and convergence compared to baseline and competing methods.Notably,error metrics are reduced(MSE 3.10×10-7,RMSE 5.57×103),with high performance indicators(r=0.982,R2=0.979,NSE=0.981,WI=0.985).These results highlight the value of integrating guided preprocessing with optimization and demonstrate a scalable framework for high-precision time-series prediction in geophysical and related domains. 展开更多
关键词 Seismic time-series forecasting large language models metaheuristic algorithms football optimization algorithm earthquake modeling
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Structured Random Cycle-Guided Algorithm (SRCA): An Adaptive Metaheuristic Combining Directionally-Guided and Stochastic Search Strategies 认领 引用
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作者 Giuseppe Marannano Antonino Cirello Tommaso Ingrassia 《Computers, Materials & Continua》 SCIE EI 2026年第6期1873-1898,共26页
In response to the growing need for adaptive optimization algorithms capable of handling complex,multimodal,and high-dimensional search spaces,this paper introduces the Structured Random Cycle-guided Algorithm(SRCA).S... In response to the growing need for adaptive optimization algorithms capable of handling complex,multimodal,and high-dimensional search spaces,this paper introduces the Structured Random Cycle-guided Algorithm(SRCA).SRCA is not presented as a fundamentally new optimization paradigm,but rather as an architectural synthesis and a unified adaptive framework for dynamic operator selection.Based on a cycle-structured architecture,directional and stochastic search behaviors are dynamically selected at the individual level.The algorithm orchestrates well-established structured movements with a diverse pool of stochastic exploration strategies,enabling a coherent and adaptive balance between exploration and exploitation throughout the optimization process.Unlike traditional metaheuristics that rely on fixed behavioral roles or static movement schemes,SRCA allows each individual to adapt its search strategy based on real-time population feedback,monitored through convergence and dispersion indicators.The performance of SRCA is quantitatively assessed under strictly identical experimental conditions on a comprehensive set of 23 benchmark functions,including multimodal and high-dimensional problems,as well as on six classical constrained engineering design problems.Numerical results demonstrate competitive convergence reliability and robustness across diverse optimization tasks,confirming the effectiveness of the proposed adaptive cycle-based framework. 展开更多
关键词 Metaheuristic algorithms optimization constrained optimization benchmark functions structured random cycle-guided algorithm
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Outage Analysis and Optimization in Decode Re-Encode and Forward Relay-Aided RIS 认领 引用
20
作者 Ali Asghar Haghighi 《China Communications》 SCIE EI CSCD 2026年第1期34-46,共13页
A terrestrial relay-aided reconfigurable intelligent surface(RIS)system with decode,re-encode and forward(DRF)relaying scheme is presented where the RIS effectively contributes to both sourceto-destination and relay-t... A terrestrial relay-aided reconfigurable intelligent surface(RIS)system with decode,re-encode and forward(DRF)relaying scheme is presented where the RIS effectively contributes to both sourceto-destination and relay-to-destination signaling.While in the conventional decode and forward(DF)relaying scheme,the source signal is merely duplicated in the relay and the time intervals are equally allocated to the source and relay nodes,this paper considers DRF relaying scheme where versatile time-sharing is adopted for the source and relay nodes which can be optimized based on the relative coordinates of the involved nodes.Two protocols namely unidirectional connection(UC)and bidirectional connection(BC)are proposed based on the source awareness from the relay’s successful reception.The outage probability(OP)performance for both protocols and both DF and DRF relaying schemes is analyzed and tight approximations are obtained.The numerical results show the out-performance of the DRF over the DF relaying scheme in the both UC and BC protocols.Equipped with the obtained system OP,the system throughput is defined and the optimum system throughput is obtained by optimizing the system rate and the timesharing between the source and the relay.Analytical results are corroborated in the numerical examples. 展开更多
关键词 DF relaying outage probability relay channel RIS throughput
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