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CSFW-SC: Cuckoo Search Fuzzy-Weighting Algorithm for Subspace Clustering Applying to High-Dimensional Clustering 被引量:1
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作者 WANG Jindong HE Jiajing +1 位作者 ZHANG Hengwei YU Zhiyong 《China Communications》 SCIE CSCD 2015年第S2期55-63,共9页
Aimed at the issue that traditional clustering methods are not appropriate to high-dimensional data, a cuckoo search fuzzy-weighting algorithm for subspace clustering is presented on the basis of the exited soft subsp... Aimed at the issue that traditional clustering methods are not appropriate to high-dimensional data, a cuckoo search fuzzy-weighting algorithm for subspace clustering is presented on the basis of the exited soft subspace clustering algorithm. In the proposed algorithm, a novel objective function is firstly designed by considering the fuzzy weighting within-cluster compactness and the between-cluster separation, and loosening the constraints of dimension weight matrix. Then gradual membership and improved Cuckoo search, a global search strategy, are introduced to optimize the objective function and search subspace clusters, giving novel learning rules for clustering. At last, the performance of the proposed algorithm on the clustering analysis of various low and high dimensional datasets is experimentally compared with that of several competitive subspace clustering algorithms. Experimental studies demonstrate that the proposed algorithm can obtain better performance than most of the existing soft subspace clustering algorithms. 展开更多
关键词 HIGH-DIMENSIONAL data CLUSTERING soft SUBSPACE cuckoo search FUZZY CLUSTERING
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Modified Cuckoo Search Algorithm to Solve Economic Power Dispatch Optimization Problems 被引量:16
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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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Structural reliability analysis using enhanced cuckoo search algorithm and artificial neural network 被引量:6
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作者 QIN Qiang FENG Yunwen LI Feng 《Journal of Systems Engineering and Electronics》 SCIE EI 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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Parameter estimation for chaotic systems using the cuckoo search algorithm with an orthogonal learning method 被引量:14
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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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DCS算法求解带软时间窗的送取货一体化VRP
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作者 周明龙 《淮北师范大学学报(自然科学版)》 CAS 2024年第2期56-62,共7页
为求解带软时间窗的送取货一体化车辆路径问题,提出一种离散布谷鸟(DCS)搜索算法。该算法在基本布谷鸟搜索算法基础之上,对莱维飞行获取新鸟巢和以一定概率抛弃鸟巢的迭代公式进行重新定义;同时设计客户序列和车辆序列双倍体鸟巢,并对... 为求解带软时间窗的送取货一体化车辆路径问题,提出一种离散布谷鸟(DCS)搜索算法。该算法在基本布谷鸟搜索算法基础之上,对莱维飞行获取新鸟巢和以一定概率抛弃鸟巢的迭代公式进行重新定义;同时设计客户序列和车辆序列双倍体鸟巢,并对客户序列采用交换、逆序、插入操作和对每辆车的访问路线采用2-Opt操作。通过5个算例的仿真实验和相关文献比较,结果表明所提DCS算法行之有效。 展开更多
关键词 车辆路径问题 同时送取货 软时间窗 布谷鸟搜索算法
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A hybrid cuckoo search algorithm with feasibility-based rule for constrained structural optimization 被引量:5
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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 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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Hybrid MPPT approach using Cuckoo Search and Grey Wolf Optimizer for PV systems under variant operating conditions 被引量:4
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作者 Jinan Abdulhasan Salim Baraa M.Albaker +1 位作者 Muwafaq Shyaa Alwan M.Hasanuzzaman 《Global Energy Interconnection》 EI CAS CSCD 2022年第6期627-644,共18页
Photovoltaic(PV)systems are adversely affected by partial shading and non-uniform conditions.Meanwhile,the addition of a bypass shunt diode to each PV module prevents hotspots.It also produces numerous peaks in the PV... Photovoltaic(PV)systems are adversely affected by partial shading and non-uniform conditions.Meanwhile,the addition of a bypass shunt diode to each PV module prevents hotspots.It also produces numerous peaks in the PV array’s power-voltage characteristics,thereby trapping conventional maximum power point tracking(MPPT)methods in local peaks.Swarm optimization approaches can be used to address this issue.However,these strategies have an unreasonably long convergence time.The Grey Wolf Optimizer(GWO)is a fast and more dependable optimization algorithm.This renders it a good option for MPPT of PV systems operating in varying partial shading.The conventional GWO method involves a long conversion time,large steady-state oscillations,and a high failure rate.This work attempts to address these issues by combining Cuckoo Search(CS)with the GWO algorithm to improve the MPPT performance.The results of this approach are compared with those of conventional MPPT according to GWO and MPPT methods based on perturb and observe(P&O).A comparative analysis reveals that under non-uniform operating conditions,the hybrid GWO CS(GWOCS)approach presented in this article outperforms the GWO and P&O approaches. 展开更多
关键词 cuckoo search GWO MPPT Hybrid MPPT PV system Luo DC-DC converter
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基于ICS算法的列车运动模型参数辨识
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作者 刘杨 尤思博 方洲宇 《电力机车与城轨车辆》 2024年第1期14-19,共6页
列车运动模型参数辨识对其运行控制至关重要,文章采用单质点列车模型,对运行列车进行受力分析,建立列车运动模型,并提出利用改进的布谷鸟搜索(ICS)算法对列车基本阻力参数进行辨识;基于真实的列车运行数据,对基本阻力参数辨识进行仿真分... 列车运动模型参数辨识对其运行控制至关重要,文章采用单质点列车模型,对运行列车进行受力分析,建立列车运动模型,并提出利用改进的布谷鸟搜索(ICS)算法对列车基本阻力参数进行辨识;基于真实的列车运行数据,对基本阻力参数辨识进行仿真分析,并基于TD3算法对参数辨识的有效性进行仿真验证。仿真结果表明,基本阻力参数辨识对列车运行控制十分必要,相对于经验参数,辨识参数下的列车基本阻力更为准确,且辨识参数下的牵引能耗有一定的降低。 展开更多
关键词 列车 参数辨识 基本阻力 改进的布谷鸟搜索(Ics)算法
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Control allocation for aircraft with input constraints based on improved cuckoo search algorithm 被引量:1
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作者 Yao LU Chao-yang DONG Qing WANG 《Defence Technology(防务技术)》 SCIE EI 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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Evaluation and intelligent deployment of coal and coalbed methane coupling coordinated exploitation based on Bayesian network and cuckoo search 被引量:2
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作者 Quanle Zou Zihan Chen +6 位作者 Zhiheng Cheng Yunpei Liang Wenjie Xu Peiran Wen Bichuan Zhang Han Liu Fanjie Kong 《International Journal of Mining Science and Technology》 SCIE EI CAS CSCD 2022年第6期1315-1328,共14页
Coal and coalbed methane(CBM)coordinated exploitation is a key technology for the safe exploitation of both resources.However,existing studies lack the quantification and evaluation of the degree of coordination betwe... Coal and coalbed methane(CBM)coordinated exploitation is a key technology for the safe exploitation of both resources.However,existing studies lack the quantification and evaluation of the degree of coordination between coal mining and coalbed methane extraction.In this study,the concept of coal and coalbed methane coupling coordinated exploitation was proposed,and the corresponding evaluation model was established using the Bayesian principle.On this basis,the objective function of coal and coalbed methane coordinated exploitation deployment was established,and the optimal deployment was determined through a cuckoo search.The results show that clarifying the coupling coordinated level of coal and coalbed methane resource exploitation in coal mines is conducive to adjusting the deployment plan in advance.The case study results show that the evaluation and intelligent deployment method proposed in this paper can effectively evaluate the coupling coordinated level of coal and coalbed methane resource exploitation and intelligently optimize the deployment of coal mine operations.The optimization results demonstrate that the safe and efficient exploitation of coal and CBM resources is promoted,and coal mining and coalbed methane extraction processes show greater cooperation.The observations and findings of this study provide a critical reference for coal mine resource exploitation in the future. 展开更多
关键词 Coal and coalbed methane Coupling coordinated exploitation Bayesian network cuckoo search Intelligent optimization
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A Novel Method for Identifying Recursive Systematic Convolutional Encoders Based on the Cuckoo Search Algorithm 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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Adaptive allocation strategy for cooperatively jamming netted radar system based on improved cuckoo search algorithm 被引量:1
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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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Application of a Parallel Adaptive Cuckoo Search Algorithm in the Rectangle Layout Problem 被引量:1
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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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A Method for Crude Oil Selection and Blending Optimization Based on Improved Cuckoo Search Algorithm 被引量:7
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作者 Yang Huihua Ma Wei +2 位作者 Zhang Xiaofeng Li Hu Tian Songbai 《China Petroleum Processing & Petrochemical Technology》 SCIE CAS 2014年第4期70-78,共9页
Refineries often need to find similar crude oil to replace the scarce crude oil for stabilizing the feedstock property. We introduced the method for calculation of crude blended properties firstly, and then created a ... Refineries often need to find similar crude oil to replace the scarce crude oil for stabilizing the feedstock property. We introduced the method for calculation of crude blended properties firstly, and then created a crude oil selection and blending optimization model based on the data of crude oil property. The model is a mixed-integer nonlinear programming(MINLP) with constraints, and the target is to maximize the similarity between the blended crude oil and the objective crude oil. Furthermore, the model takes into account the selection of crude oils and their blending ratios simultaneously, and transforms the problem of looking for similar crude oil into the crude oil selection and blending optimization problem. We applied the Improved Cuckoo Search(ICS) algorithm to solving the model. Through the simulations, ICS was compared with the genetic algorithm, the particle swarm optimization algorithm and the CPLEX solver. The results show that ICS has very good optimization efficiency. The blending solution can provide a reference for refineries to find the similar crude oil. And the method proposed can also give some references to selection and blending optimization of other materials. 展开更多
关键词 CRUDE OIL similarity CRUDE OIL SELECTION BLENDING OPTIMIZATION MIXED-INTEGER nonlinear programming cuckoosearch algorithm
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Enhanced Energy Efficient Multipath Routing Protocol for Wireless Sensor Communication Networks Using Cuckoo Search Algorithm 被引量:1
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作者 D. Antony Arul Raj P. Sumathi 《Wireless Sensor Network》 2014年第4期49-55,共7页
Energy efficient routing is one of the major thrust areas in Wireless Sensor Communication Networks (WSCNs) and it attracts most of the researchers by its valuable applications and various challenges. Wireless sensor ... Energy efficient routing is one of the major thrust areas in Wireless Sensor Communication Networks (WSCNs) and it attracts most of the researchers by its valuable applications and various challenges. Wireless sensor networks contain several nodes in its terrain region. Reducing the energy consumption over the WSCN has its significance since the nodes are battery powered. Various research methodologies were proposed by researchers in this area. One of the bio-inspired computing paradigms named Cuckoo search algorithm is used in this research work for finding the energy efficient path and routing is performed. Several performance metrics are taken into account for determining the performance of the proposed routing protocol such as throughput, packet delivery ratio, energy consumption and delay. Simulation is performed using NS2 and the results shows that the proposed routing protocol is better in terms of average throughput, and average energy consumption. 展开更多
关键词 WIRELESS Sensor Communication Networks cuckoo search Algorithm AODV AOMDV
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Research on the MPPT of Photovoltaic Power Generation Based on the CSA-INC Algorithm 被引量:1
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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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基于IMOCS-BP神经网络的锂离子电池SOH估计
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作者 王雪 游国栋 +1 位作者 房成信 张尚 《电源学报》 CSCD 北大核心 2024年第1期94-100,共7页
锂离子电池随着循环充放电次数的增长,其健康状态SOH(state-of-health)会随之发生一定程度的衰减。针对以上问题,设计了一种基于改进的多目标布谷鸟搜索IMOCS(improved multi-objective Cuckoo search)-BP神经网络的锂离子电池健康状态... 锂离子电池随着循环充放电次数的增长,其健康状态SOH(state-of-health)会随之发生一定程度的衰减。针对以上问题,设计了一种基于改进的多目标布谷鸟搜索IMOCS(improved multi-objective Cuckoo search)-BP神经网络的锂离子电池健康状态估计方法,在避免算法陷入局部最优的同时自适应改变布谷鸟搜索CS(Cuckoo search)算法更新概率和搜索步长,解决CS算法收敛速度慢和求解精度低的问题。以IMOCS算法和BP神经网络结合,对节点空间范围进行全局搜索,降低权值和阈值的初值对BP神经网络的影响,实现参数优化。通过Matlab仿真,验证了基于IMOCS-BP神经网络的SOH估计算法误差低、性能强,实现了锂电池SOH的精准预测。 展开更多
关键词 锂离子电池 健康状态 布谷鸟搜索算法 BP神经网络
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基于CNN-LSTM-CS工业管道腐蚀率预测模型 被引量:2
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作者 王宏 冯佳俊 +3 位作者 戴旗 施宇 梁宇航 张辉 《计算机系统应用》 2024年第5期103-109,共7页
针对传统工业管道腐蚀率预测模型存在特征提取依赖人工经验和泛化能力不足的问题,本文将卷积神经网络(convolutional neural network,CNN)和长短期记忆网络(long short-term memory,LSTM)相结合,提出了基于布谷鸟优化算法(cuckoo search... 针对传统工业管道腐蚀率预测模型存在特征提取依赖人工经验和泛化能力不足的问题,本文将卷积神经网络(convolutional neural network,CNN)和长短期记忆网络(long short-term memory,LSTM)相结合,提出了基于布谷鸟优化算法(cuckoo search,CS)的CNN-LSTM-CS网络模型,实现对工业管道腐蚀率预测.首先,对采集的管道腐蚀数据集进行归一化预处理;然后,利用CNN网络提取影响管道腐蚀率因素的深层次特征信息,并通过训练LSTM网络构建CNN-LSTM预测模型;最后,采用CS算法对预测模型进行参数优化,减少预测误差,实现腐蚀率的精准预测.实验结果表明,对比几种典型的腐蚀率预测方法,本文提出的方法具有更高的预测精度,为工业管道腐蚀率检测提供新的思路. 展开更多
关键词 管道腐蚀率 卷积神经网络 长短期记忆网络 布谷鸟优化算法
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Parameter Estimation of Mixed Weibull Distributions Using Cuckoo Search
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作者 池阔 王广彦 +1 位作者 康建设 吴坤 《Journal of Donghua University(English Edition)》 EI CAS 2016年第2期235-238,共4页
The lifetime data of products with multiple failure modes which are collected from life testing are often fitted by the mixed Weibull distributions. Since the mixed Weibull distributions contain no less than five para... The lifetime data of products with multiple failure modes which are collected from life testing are often fitted by the mixed Weibull distributions. Since the mixed Weibull distributions contain no less than five parameters,the parameter estimation is difficult and inaccurate. In order to enhance the accuracy,a new method of parameter estimation based on Cuckoo search( CS) is proposed. An optimization model for the mixed Weibull distribution is formulated by minimizing the residual sum of squares. The optimal parameters are searched via CS algorithm. In the case study,the lifetime data come from the life testing of diesel injectors and are fitted by the twocomponent Weibull mixture. Regarding the maximum absolute error and the accumulative absolute error between estimated and observed values as the accuracy index of parameter estimation,the results of four parameter estimation methods that the graphic estimation method,the nonlinear least square method,the optimization method based on particle swarm optimization( PSO) and the proposed method are compared. The result shows that the proposed method is more efficient and more accurate than the other three methods. 展开更多
关键词 RELIABILITY mixed Weibull distribution parameter estimation cuckoo search(cs)
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