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Optimization of the frequency offset increment of FDA-MIMO based on cuckoo search algorithm 认领 引用 被引量：1
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作者 WANG Bo ZHAO Yu +2 位作者 LI Yonglin YANG Rennong XUE Junjie 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2026年第1期157-170,共14页
Frequency diverse array multiple-input multiple-output(FDA-MIMO)radar has gained considerable research attention due to its ability to effectively counter active repeater deception jamming in complex electromagnetic e... Frequency diverse array multiple-input multiple-output(FDA-MIMO)radar has gained considerable research attention due to its ability to effectively counter active repeater deception jamming in complex electromagnetic environments.The effectiveness of interference suppression by FDA-MIMO is limited by the inherent range-angle coupling issue in the FDA beampattern.Existing literature primarily focuses on control methods for FDA-MIMO radar beam direction under the assumption of static beampatterns,with insufficient exploration of techniques for managing nonstationary beam directions.To address this gap,this paper initially introduces the FDA-MIMO signal model and the calculation formula for the FDA-MIMO array output using the minimum variance distortionless response(MVDR)beamformer.Building on this,the problem of determining the optimal frequency offset for the FDA is rephrased as a convex optimization problem,which is then resolved using the cuckoo search(CS)algorithm.Simulations confirm the effectiveness of the proposed approach,showing that the frequency offsets obtained through the CS algorithm can create a dot-shaped beam direction at the target location while effectively suppressing interference signals within the mainlobe. 展开更多
关键词 frequency diverse array multiple-input multiple-output(FDA-MIMO) convex optimization cuckoo search algorithm beampattern
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Improved Cuckoo Search Algorithm for Engineering Optimization Problems 认领 引用
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作者 Shao-Qiang Ye Azlan Mohd Zain Yusliza Yusoff 《Computers, Materials & Continua》 SCIE EI 2026年第4期1607-1631,共25页
Engineering optimization problems are often characterized by high dimensionality,constraints,and complex,multimodal landscapes.Traditional deterministic methods frequently struggle under such conditions,prompting incr... Engineering optimization problems are often characterized by high dimensionality,constraints,and complex,multimodal landscapes.Traditional deterministic methods frequently struggle under such conditions,prompting increased interest in swarm intelligence algorithms.Among these,the Cuckoo Search(CS)algorithm stands out for its promising global search capabilities.However,it often suffers from premature convergence when tackling complex problems.To address this limitation,this paper proposes a Grouped Dynamic Adaptive CS(GDACS)algorithm.Theenhancements incorporated intoGDACS can be summarized into two key aspects.Firstly,a chaotic map is employed to generate initial solutions,leveraging the inherent randomness of chaotic sequences to ensure a more uniform distribution across the search space and enhance population diversity from the outset.Secondly,Cauchy and Levy strategies replace the standard CS population update.This strategy involves evaluating the fitness of candidate solutions to dynamically group the population based on performance.Different step-size adaptation strategies are then applied to distinct groups,enabling an adaptive search mechanism that balances exploration and exploitation.Experiments were conducted on six benchmark functions and four constrained engineering design problems,and the results indicate that the proposed GDACS achieves good search efficiency and produces more accurate optimization results compared with other state-of-the-art algorithms. 展开更多
关键词 Cuckoo search algorithm chaotic transformation population division adaptive update strategy Cauchy distribution
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Optimal load frequency control system for two-area connected via AC/DC link using cuckoo search algorithm 认领 引用
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作者 Gaber EL-SAADY Alexey MIKHAYLOV +2 位作者 Nora BARANYAI Mahrous AHMED Mahmoud HEMEIDA 《虚拟现实与智能硬件（中英文）》 EI CSCD 2025年第3期299-316,共18页
Background Interconnection of different power systems has a major effect on system stability.This study aims to design an optimal load frequency control(LFC)system based on a proportional-integral(PI)controller for a ... Background Interconnection of different power systems has a major effect on system stability.This study aims to design an optimal load frequency control(LFC)system based on a proportional-integral(PI)controller for a two-area power system.Methods Two areas were connected through an AC tie line in parallel with a DC link to stabilize the frequency of oscillations in both areas.The PI parameters were tuned using the cuckoo search algorithm(CSA)to minimize the integral absolute error(IAE).A state matrix was provided,and the stability of the system was verified by calculating the eigenvalues.The frequency response was investigated for load variation,changes in the generator rate constraint,the turbine time constant,and the governor time constant.Results The CSA was compared with particle swarm optimization algorithm(PSO)under identical conditions.The system was modeled based on a state-space mathematical representation and simulated using MATLAB.The results demonstrated the effectiveness of the proposed controller based on both algorithms and,it is clear that CSA is superior to PSO.Conclusion The CSA algorithm smoothens the system response,reduces ripples,decreases overshooting and settling time,and improves the overall system performance under different disturbances. 展开更多
关键词 Load frequency control Cuckoo search algorithm PI controllers State space modeling
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Deep Learning Mixed Hyper-Parameter Optimization Based on Improved Cuckoo Search Algorithm 认领 引用
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作者 TONG Yu CHEN Rong HU Biling 《Wuhan University Journal of Natural Sciences》 CAS CSCD 2025年第2期195-204,共10页
Deep learning algorithm is an effective data mining method and has been used in many fields to solve practical problems.However,the deep learning algorithms often contain some hyper-parameters which may be continuous,... Deep learning algorithm is an effective data mining method and has been used in many fields to solve practical problems.However,the deep learning algorithms often contain some hyper-parameters which may be continuous,integer,or mixed,and are often given based on experience but largely affect the effectiveness of activity recognition.In order to adapt to different hyper-parameter optimization problems,our improved Cuckoo Search(CS)algorithm is proposed to optimize the mixed hyper-parameters in deep learning algorithm.The algorithm optimizes the hyper-parameters in the deep learning model robustly,and intelligently selects the combination of integer type and continuous hyper-parameters that make the model optimal.Then,the mixed hyper-parameter in Convolutional Neural Network(CNN),Long-Short-Term Memory(LSTM)and CNN-LSTM are optimized based on the methodology on the smart home activity recognition datasets.Results show that the methodology can improve the performance of the deep learning model and whether we are experienced or not,we can get a better deep learning model using our method. 展开更多
关键词 improved Cuckoo Search algorithm mixed hyper-parameter optimization deep learning
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Structural reliability analysis using enhanced cuckoo search algorithm and artificial neural network 认领 引用 被引量：7
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作者 QIN Qiang FENG Yunwen LI Feng 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2018年第6期1317-1326,共10页
The present study proposed an enhanced cuckoo search(ECS) algorithm combined with artificial neural network(ANN) as the surrogate model to solve structural reliability problems. In order to enhance the accuracy and co... The present study proposed an enhanced cuckoo search(ECS) algorithm combined with artificial neural network(ANN) as the surrogate model to solve structural reliability problems. In order to enhance the accuracy and convergence rate of the original cuckoo search(CS) algorithm, the main parameters namely, abandon probability of worst nests paand search step sizeα0 are dynamically adjusted via nonlinear control equations. In addition, a global-best guided equation incorporating the information of global best nest is introduced to the ECS to enhance its exploitation. Then, the proposed ECS is linked to the well-trained ANN model for structural reliability analysis. The computational capability of the proposed algorithm is validated using five typical structural reliability problems and an engineering application. The comparison results show the efficiency and accuracy of the proposed algorithm. 展开更多
关键词 structural reliability enhanced cuckoo search(ECS) artificial neural network(ANN) cuckoo search(CS) algorithm
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Modified Cuckoo Search Algorithm to Solve Economic Power Dispatch Optimization Problems 认领 引用 被引量：18
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作者 Jian Zhao Shixin Liu +2 位作者 Mengchu Zhou Xiwang Guo Liang Qi 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2018年第4期794-806,共13页
A modified cuckoo search(CS) algorithm is proposed to solve economic dispatch(ED) problems that have nonconvex, non-continuous or non-linear solution spaces considering valve-point effects, prohibited operating zones,... A modified cuckoo search(CS) algorithm is proposed to solve economic dispatch(ED) problems that have nonconvex, non-continuous or non-linear solution spaces considering valve-point effects, prohibited operating zones, transmission losses and ramp rate limits. Comparing with the traditional cuckoo search algorithm, we propose a self-adaptive step size and some neighbor-study strategies to enhance search performance.Moreover, an improved lambda iteration strategy is used to generate new solutions. To show the superiority of the proposed algorithm over several classic algorithms, four systems with different benchmarks are tested. The results show its efficiency to solve economic dispatch problems, especially for large-scale systems. 展开更多
关键词 Cuckoo search(CS) economic dispatch(ED) prohibited operating zones ramp rate limits valve-point effects
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Adaptive allocation strategy for cooperatively jamming netted radar system based on improved cuckoo search algorithm 认领 引用 被引量：9
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作者 De-jiang Lu Xing Wang +1 位作者 Xiao-tian Wu You Chen 《Defence Technology（防务技术）》 SCIE EI CAS CSCD 2023年第6期285-297,共13页
The jamming resource allocation problem of the aircraft formation cooperatively jamming netted radar system is investigated.An adaptive allocation strategy based on dynamic adaptive discrete cuckoo search algorithm(DA... The jamming resource allocation problem of the aircraft formation cooperatively jamming netted radar system is investigated.An adaptive allocation strategy based on dynamic adaptive discrete cuckoo search algorithm(DADCS)is proposed,whose core is to adjust allocation scheme of limited jamming resource of aircraft formation in real time to maintain the best jamming effectiveness against netted radar system.Firstly,considering the information fusion rules and different working modes of the netted radar system,a two-factor jamming effectiveness evaluation function is constructed,detection probability and aiming probability are adopted to characterize jamming effectiveness against netted radar system in searching and tracking mode,respectively.Then a nonconvex optimization model for cooperatively jamming netted radar system is established.Finally,a dynamic adaptive discrete cuckoo search algorithm(DADCS)is constructed by improving path update strategies and introducing a global learning mechanism,and a three-step solution method is proposed subsequently.Simulation results are provided to demonstrate the advantages of the proposed optimization strategy and the effectiveness of the improved algorithm. 展开更多
关键词 Cuckoo search algorithm Netted radar system Radar countermeasures Resource allocation Information fusion
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A hybrid cuckoo search algorithm with feasibility-based rule for constrained structural optimization 认领 引用 被引量：6
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作者 龙文 张文专 +1 位作者 黄亚飞 陈义雄 《Journal of Central South University》 SCIE EI CAS 2014年第8期3197-3204,共8页
Constrained optimization problems are very important as they are encountered in many science and engineering applications.As a novel evolutionary computation technique,cuckoo search(CS) algorithm has attracted much at... Constrained optimization problems are very important as they are encountered in many science and engineering applications.As a novel evolutionary computation technique,cuckoo search(CS) algorithm has attracted much attention and wide applications,owing to its easy implementation and quick convergence.A hybrid cuckoo pattern search algorithm(HCPS) with feasibility-based rule is proposed for solving constrained numerical and engineering design optimization problems.This algorithm can combine the stochastic exploration of the cuckoo search algorithm and the exploitation capability of the pattern search method.Simulation and comparisons based on several well-known benchmark test functions and structural design optimization problems demonstrate the effectiveness,efficiency and robustness of the proposed HCPS algorithm. 展开更多
关键词 constrained optimization problem cuckoo search algorithm pattem search feasibility-based rule engineeringoptimization
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Wind speed forecasting based on wavelet decomposition and wavelet neural networks optimized by the Cuckoo search algorithm 认领 引用 被引量：8
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作者 ZHANG Ye YANG Shiping +2 位作者 GUO Zhenhai GUO Yanling ZHAO Jing 《Atmospheric and Oceanic Science Letters》 CSCD 2019年第2期107-115,共9页
Wind speed forecasting is of great importance for wind farm management and plays an important role in grid integration. Wind speed is volatile in nature and therefore it is difficult to predict with a single model. In... Wind speed forecasting is of great importance for wind farm management and plays an important role in grid integration. Wind speed is volatile in nature and therefore it is difficult to predict with a single model. In this study, three hybrid multi-step wind speed forecasting models are developed and compared — with each other and with earlier proposed wind speed forecasting models. The three models are based on wavelet decomposition(WD), the Cuckoo search(CS) optimization algorithm, and a wavelet neural network(WNN). They are referred to as CS-WD-ANN(artificial neural network), CS-WNN, and CS-WD-WNN, respectively. Wind speed data from two wind farms located in Shandong, eastern China, are used in this study. The simulation result indicates that CS-WD-WNN outperforms the other two models, with minimum statistical errors. Comparison with earlier models shows that CS-WD-WNN still performs best, with the smallest statistical errors. The employment of the CS optimization algorithm in the models shows improvement compared with the earlier models. 展开更多
关键词 Wind speed forecast wavelet decomposition neural network Cuckoo search algorithm
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Parameter estimation for chaotic systems using the cuckoo search algorithm with an orthogonal learning method 认领 引用 被引量：17
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作者 李向涛 殷明浩 《Chinese Physics B》 SCIE EI CAS CSCD 2012年第5期113-118,共6页
We study the parameter estimation of a nonlinear chaotic system,which can be essentially formulated as a multidimensional optimization problem.In this paper,an orthogonal learning cuckoo search algorithm is used to es... We study the parameter estimation of a nonlinear chaotic system,which can be essentially formulated as a multidimensional optimization problem.In this paper,an orthogonal learning cuckoo search algorithm is used to estimate the parameters of chaotic systems.This algorithm can combine the stochastic exploration of the cuckoo search and the exploitation capability of the orthogonal learning strategy.Experiments are conducted on the Lorenz system and the Chen system.The proposed algorithm is used to estimate the parameters for these two systems.Simulation results and comparisons demonstrate that the proposed algorithm is better or at least comparable to the particle swarm optimization and the genetic algorithm when considering the quality of the solutions obtained. 展开更多
关键词 cuckoo search algorithm chaotic system parameter estimation orthogonal learning
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Application of a Parallel Adaptive Cuckoo Search Algorithm in the Rectangle Layout Problem 认领 引用 被引量：3
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作者 Weimin Zheng Mingchao Si +2 位作者 Xiao Sui Shuchuan Chu Jengshyang Pan 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第6期2173-2196,共24页
The meta-heuristic algorithm is a global probabilistic search algorithm for the iterative solution.It has good performance in global optimization fields such as maximization.In this paper,a new adaptive parameter stra... The meta-heuristic algorithm is a global probabilistic search algorithm for the iterative solution.It has good performance in global optimization fields such as maximization.In this paper,a new adaptive parameter strategy and a parallel communication strategy are proposed to further improve the Cuckoo Search(CS)algorithm.This strategy greatly improves the convergence speed and accuracy of the algorithm and strengthens the algorithm’s ability to jump out of the local optimal.This paper compares the optimization performance of Parallel Adaptive Cuckoo Search(PACS)with CS,Parallel Cuckoo Search(PCS),Particle Swarm Optimization(PSO),Sine Cosine Algorithm(SCA),Grey Wolf Optimizer(GWO),Whale Optimization Algorithm(WOA),Differential Evolution(DE)and Artificial Bee Colony(ABC)algorithms by using the CEC-2013 test function.The results show that PACS algorithmoutperforms other algorithms in 20 of 28 test functions.Due to the superior performance of PACS algorithm,this paper uses it to solve the problem of the rectangular layout.Experimental results show that this scheme has a significant effect,and the material utilization rate is improved from89.5%to 97.8%after optimization. 展开更多
关键词 Rectangular layout cuckoo search algorithm parallel communication strategy adaptive parameter
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High Order Stable Infinite Impulse Response Filter Design Using Cuckoo Search Algorithm 认领 引用 被引量：2
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作者 N.Agrawal A.Kumar +1 位作者 V.Bajaj G.K.Singh 《International Journal of Automation and computing》 CSCD 2017年第5期589-602,共14页
In this paper, an efficient technique for optimal design of digital infinite impulse response （IIR） filter with minimum passband error （ep）, minimum stopband error （es）, high stopband attenuation （As）, and als... In this paper, an efficient technique for optimal design of digital infinite impulse response （IIR） filter with minimum passband error （ep）, minimum stopband error （es）, high stopband attenuation （As）, and also free from limit cycle effect is proposed using cuckoo search （CS） algorithm. In the proposed method, error function, which is multi-model and non-differentiable in the heuristic surface, is constructed as the mean squared difference between the designed and desired response in frequency domain, and is optimized using CS algorithm. Computational efficiency of the proposed technique for exploration in search space is examined, and during exploration, stability of filter is maintained by considering lattice representation of the denominator polynomials, which requires less computational complexity as well as it improves the exploration ability in search space for designing higher filter taps. A comparative study of the proposed method with other algorithms is made, and the obtained results show that 90% reduction in errors is achieved using the proposed method. However, computational complexity in term of CPU time is increased as compared to other existing algorithms. 展开更多
关键词 Cuckoo search algorithm infinite impulse response （IIR） means square error （MSE） evolutionary algorithm stability.
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Control allocation for aircraft with input constraints based on improved cuckoo search algorithm 认领 引用 被引量：1
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作者 Yao LU Chao-yang DONG Qing WANG 《Defence Technology（防务技术）》 SCIE CAS CSCD 2017年第1期1-5,共5页
The control allocation problem of aircraft whose control inputs contain integer constraints is investigated. The control allocation problem is described as an integer programming problem and solved by the cuckoo searc... The control allocation problem of aircraft whose control inputs contain integer constraints is investigated. The control allocation problem is described as an integer programming problem and solved by the cuckoo search algorithm. In order to enhance the search capability of the cuckoo search algorithm, the adaptive detection probability and amplification factor are designed. Finally, the control allocation method based on the proposed improved cuckoo search algorithm is applied to the tracking control problem of the innovative control effector aircraft. The comparative simulation results demonstrate the superiority and effectiveness of the proposed improved cuckoo search algorithm in control allocation of aircraft. 展开更多
关键词 Control allocation Optimization Cuckoo search algorithm Innovative control effector aircraft Tracking
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Research on the MPPT of Photovoltaic Power Generation Based on the CSA-INC Algorithm 认领 引用 被引量：2
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作者 Tao Hou Shan Wang 《Energy Engineering》 EI 2023年第1期87-106,共20页
The existing Maximum Power Point Tracking(MPPT)method has low tracking efficiency and poor stability.It is easy to fall into the Local Maximum Power Point(LMPP)in Partial Shading Condition(PSC),resulting in the degrad... The existing Maximum Power Point Tracking(MPPT)method has low tracking efficiency and poor stability.It is easy to fall into the Local Maximum Power Point(LMPP)in Partial Shading Condition(PSC),resulting in the degradation of output power quality and efficiency.It was found that various bio-inspired MPPT based optimization algorithms employ different mechanisms,and their performance in tracking the Global Maximum Power Point(GMPP)varies.Thus,a Cuckoo search algorithm(CSA)combined with the Incremental conductance Algorithm(INC)is proposed(CSA-INC)is put forward for the MPPT method of photovoltaic power generation.The method can improve the tracking speed by more than 52%compared with the traditional Cuckoo Search Algorithm(CSA),and the results of the study using this algorithm are compared with the popular Particle Swarm Optimization(PSO)and the Gravitational Search Algorithm(GSA).CSA-INC has an average tracking efficiency of 99.99%and an average tracking time of 0.19 s when tracking the GMPP,which improves PV power generation’s efficiency and power quality. 展开更多
关键词 Partial shading condition sudden light intensity cuckoo search algorithm maximum power point tracking Incremental conductance Algorithm
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Cuckoo search algorithm-based optimal deployment method of heterogeneous multistatic radar for barrier coverage 认领 引用 被引量：1
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作者 LI Haipeng FENG Dazheng 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2023年第5期1101-1115,共15页
This paper proposes an optimal deployment method of heterogeneous multistatic radars to construct arc barrier coverage with location restrictions.This method analyzes and proves the properties of different deployment ... This paper proposes an optimal deployment method of heterogeneous multistatic radars to construct arc barrier coverage with location restrictions.This method analyzes and proves the properties of different deployment patterns in the optimal deployment sequence.Based on these properties and considering location restrictions,it introduces an optimization model of arc barrier coverage and aims to minimize the total deployment cost of heterogeneous multistatic radars.To overcome the non-convexity of the model and the non-analytical nature of the objective function,an algorithm combining integer line programming and the cuckoo search algorithm(CSA)is proposed.The proposed algorithm can determine the number of receivers and transmitters in each optimal deployment squence to minimize the total placement cost.Simulations are conducted in different conditions to verify the effectiveness of the proposed method. 展开更多
关键词 heterogeneous multistatic radar(HMR) arc barrier coverage minimum deployment cost optimal deployment sequence cuckoo search algorithm(CSA)
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A Cuckoo Search Detector Generation-based Negative Selection Algorithm 认领 引用
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作者 Ayodele Lasisi Ali M.Aseere 《Computer Systems Science & Engineering》 SCIE EI 2021年第8期183-195,共13页
The negative selection algorithm(NSA)is an adaptive technique inspired by how the biological immune system discriminates the self from nonself.It asserts itself as one of the most important algorithms of the artificia... The negative selection algorithm(NSA)is an adaptive technique inspired by how the biological immune system discriminates the self from nonself.It asserts itself as one of the most important algorithms of the artificial immune system.A key element of the NSA is its great dependency on the random detectors in monitoring for any abnormalities.However,these detectors have limited performance.Redundant detectors are generated,leading to difficulties for detectors to effectively occupy the non-self space.To alleviate this problem,we propose the nature-inspired metaheuristic cuckoo search(CS),a stochastic global search algorithm,which improves the random generation of detectors in the NSA.Inbuilt characteristics such as mutation,crossover,and selection operators make the CS attain global convergence.With the use of Lévy flight and a distance measure,efficient detectors are produced.Experimental results show that integrating CS into the negative selection algorithm elevated the detection performance of the NSA,with an average increase of 3.52%detection rate on the tested datasets.The proposed method shows superiority over other models,and detection rates of 98%and 99.29%on Fisher’s IRIS and Breast Cancer datasets,respectively.Thus,the generation of highest detection rates and lowest false alarm rates can be achieved. 展开更多
关键词 Negative selection algorithm detector generation cuckoo search optimization
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基于改进CS-GWO算法的多无人机三维路径规划 认领 引用
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作者 宋宇 赵桐 《长春工业大学学报》 CAS 2026年第2期147-152,共6页
随着无人机技术的迅速发展,多无人机协同任务在各个领域中引起了广泛关注。然而,在复杂环境下,实现多无人机协同避障并成功完成任务,但仍面临突出挑战。为了解决这一问题,提出一种基于结合布谷鸟搜索(CS)算法和灰狼优化(GWO)算法的多无... 随着无人机技术的迅速发展,多无人机协同任务在各个领域中引起了广泛关注。然而,在复杂环境下,实现多无人机协同避障并成功完成任务,但仍面临突出挑战。为了解决这一问题,提出一种基于结合布谷鸟搜索(CS)算法和灰狼优化(GWO)算法的多无人机协同避障路径规划方法。该方法利用GWO的全局搜索能力和CS的随机性,综合考虑了路径长度、飞行高度和路径平滑性等多个关键因素,设计了一个新的适应度函数,进而通过改进算法实现高效路径规划。根据仿真结果可以得出,所提出的方法有效地达成了多无人机协同避障并完成任务的目标,为多无人机系统的应用提供了新的研究思路和解决方案。 展开更多
关键词 无人机路径规划 三维避障 布谷鸟搜索算法 灰狼优化算法
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An Improved Cuckoo Search Algorithm for Multi-Objective Optimization 认领 引用 被引量：2
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作者 TIAN Mingzheng HOU Kuolin +1 位作者 WANG Zhaowei WAN Zhongping 《Wuhan University Journal of Natural Sciences》 CAS CSCD 2017年第4期289-294,共6页
The recently proposed Cuckoo search algorithm is an evolutionary algorithm based on probability. It surpasses other algorithms in solving the multi-modal discontinuous and nonlinear problems. Searches made by it are v... The recently proposed Cuckoo search algorithm is an evolutionary algorithm based on probability. It surpasses other algorithms in solving the multi-modal discontinuous and nonlinear problems. Searches made by it are very efficient because it adopts Levy flight to carry out random walks. This paper proposes an improved version of cuckoo search for multi-objective problems（IMOCS）. Combined with nondominated sorting, crowding distance and Levy flights, elitism strategy is applied to improve the algorithm. Then numerical studies are conducted to compare the algorithm with DEMO and NSGA-II against some benchmark test functions. Result shows that our improved cuckoo search algorithm convergences rapidly and performs efficienly. 展开更多
关键词 multi-objective optimization evolutionary algorithm Cuckoo search Levy flight
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TDOA Passive Location Based on Cuckoo Search Algorithm 认领 引用 被引量：10
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作者 JIANG Yilin LIU Mengnan +1 位作者 CHEN Tao GAO Lipeng 《Journal of Shanghai Jiaotong university(Science)》 EI 2018年第3期368-375,共8页
This paper formulates a new framework to estimate the target position by adopting cuckoo search(CS)positioning algorithm. Addressing the nonlinear optimization problem is a crucial spot in the location system of time ... This paper formulates a new framework to estimate the target position by adopting cuckoo search(CS)positioning algorithm. Addressing the nonlinear optimization problem is a crucial spot in the location system of time difference of arrival(TDOA). With the application of the Levy flight mechanism, the preferential selection mechanism and the elimination mechanism, the proposed approach prevents positioning results from falling into local optimum. These intelligent mechanisms are useful to ensure the population diversity and improve the convergence speed. Simulation results demonstrate that the cuckoo localization algorithm has higher locating precision and better performance than the conventional methods. Compared with particle swarm optimization(PSO) algorithm and Newton iteration algorithm, the proposed method can obtain the Cram′er-Rao lower bound(CRLB) and quickly achieve the global optimal solutions. 展开更多
关键词 time difference of arrival(TDOA) passive location cuckoo search(CS) algorithm station layout
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A Novel Method for Identifying Recursive Systematic Convolutional Encoders Based on the Cuckoo Search Algorithm 认领 引用 被引量：1
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作者 Shunan Han Peng Liu Guang Huang 《China Communications》 SCIE CSCD 2022年第12期64-72,共9页
The existing methods for identifying recursive systematic convolutional encoders with high robustness require to test all the candidate generator matrixes in the search space exhaustively.With the increase of the code... The existing methods for identifying recursive systematic convolutional encoders with high robustness require to test all the candidate generator matrixes in the search space exhaustively.With the increase of the codeword length and constraint length,the search space expands exponentially,and thus it limits the application of these methods in practice.To overcome the limitation,a novel identification method,which gets rid of exhaustive test,is proposed based on the cuckoo search algorithm by using soft-decision data.Firstly,by using soft-decision data,the probability that a parity check equation holds is derived.Thus,solving the parity check equations is converted to maximize the joint probability that parity check equations hold.Secondly,based on the standard cuckoo search algorithm,the established cost function is optimized.According to the final solution of the optimization problem,the generator matrix of recursive systematic convolutional code is estimated.Compared with the existing methods,our proposed method does not need to search for the generator matrix exhaustively and has high robustness.Additionally,it does not require the prior knowledge of the constraint length and is applicable in any modulation type. 展开更多
关键词 RSC code blind identification softdecision cuckoo search algorithm
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