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Adaptive allocation strategy for cooperatively jamming netted radar system based on improved cuckoo search algorithm

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Defence Technology（防务技术） 2023年第6期24卷 285-297页

作者： De-jiang Lu Xing Wang Xiao-tian Wu You Chen Aviation Engineering School Air Force Engineering UniversityXi'an710038China

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.

关键词： cuckoo search algorithm Netted radar system Radar countermeasures Resource allocation Information fusion

A Novel Method for Identifying Recursive Systematic Convolutional Encoders Based on the cuckoo search algorithm

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China Communications 2022年第12期19卷 64-72页

作者： Shunan Han Peng Liu Guang Huang Aviation University of Air Force Changchun 130000China

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.

关键词： RSC code blind identification softdecision cuckoo search algorithm

High Order Stable Infinite Impulse Response Filter Design Using cuckoo search algorithm

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International Journal of Automation and computing 2017年第5期14卷 589-602页

作者： N.Agrawal A.Kumar V.Bajaj G.K.Singh Department of Electronics and Communication Engineering the Pandit Dwarka Prasad MishraIndian Institute of Information TechnologyDesign and ManufacturingDurnna 482005India School of Electrical Engineering and Computer Science Gwangju Institute of Science and TechnologyKorea Department of Electrical Engineering Indian Institute of TechnologyRoorkee 247667India

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.

关键词： cuckoo search algorithm infinite impulse response （IIR） means square error （MSE） evolutionary algorithm stability.

Parameter estimation for chaotic systems using the cuckoo search algorithm with an orthogonal learning method

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Chinese Physics B 2012年第5期21卷 113-118页

作者：李向涛殷明浩 College of Computer Science Northeast Normal University

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.

关键词： cuckoo search algorithm chaotic system parameter estimation orthogonal learning

Control allocation for aircraft with input constraints based on improved cuckoo search algorithm

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Defence Technology（防务技术） 2017年第1期13卷 1-5页

作者： Yao LU Chao-yang DONG Qing WANG School of Aeronautic Science and Engineering BUAABeijing 100191China School of Automation Science and Electrical Engineering BUAABeijing 100191China

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.

关键词： Control allocation Optimization cuckoo search algorithm Innovative control effector aircraft Tracking

A Novel cuckoo search algorithm and Its Application

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Open Journal of Applied Sciences 2021年第9期11卷 1071-1081页

作者： Ping Liu Shengjiang Zhang Nanchang Vocational University Nanchang China

In this paper, the principle of cuckoo algorithm is introduced, and the traditional cuckoo algorithm is improved to establish a mathematical model of multi-objective optimization scheduling. Based on the improved algorithm, the model is optimized to a certain extent. Through analysis, it is proved that the improved algorithm has higher computational accuracy and can effectively improve the global convergence.

关键词： cuckoo search algorithm Feature Selection Infrared Spectrum Global Convergence

An EPC Forecasting Method for Stock Index Based on Integrating Empirical Mode Decomposition, SVM and cuckoo search algorithm

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Journal of Systems Science and Information 2014年第6期2卷 481-504页

作者： Xiangfei LI Zaisheng ZHANG Chao HUANG School of Accountancy Tianjin Polytechnic University Tianjin University School of Management Shanghai University of Finance and Economics College of Management and Economics

In order to improve the forecasting accuracy, a hybrid error-correction approach by integrating support vector machine(SVM), empirical mode decomposition(EMD) and the improved cuckoo search algorithm(ICS) was introduced in this study. By using two indexes as examples, the empirical study shows our proposed approach by means of synchronously predict the prediction error which used to correct the preliminary predicted values has better prediction precision than other five competing approaches, furthermore, the improved strategies for cuckoo search algorithm has better performance than other three evolutionary algorithms in parameters selection.

关键词： error-correction stock index forecasting empirical mode decomposition SVM cuckoo search algorithm

Renal Pathology Images Segmentation Based on Improved cuckoo search with Diffusion Mechanism and Adaptive Beta-Hill Climbing

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Journal of Bionic Engineering 2023年第5期20卷 2240-2275页

作者： Jiaochen Chen Zhennao Cai Huiling Chen Xiaowei Chen José Escorcia-Gutierrez Romany F.Mansour Mahmoud Ragab College of Computer Science and Artificial Intelligence Wenzhou UniversityWenzhou325035China Department of Rheumatology and Immunology The First Affiliated Hospital of Wenzhou Medical UniversityWenzhou325000China Department of Computational Science and Electronics Universidad de la CostaCUC080002BarranquillaColombia Department of Mathematics Faculty of ScienceNew Valley University72511El-KhargaEgypt Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mathematics Faculty of ScienceAl-Azhar UniversityNaser CityCairo11884Egypt

Lupus Nephritis(LN)is a significant risk factor for morbidity and mortality in systemic lupus erythematosus,and nephropathology is still the gold standard for diagnosing LN.To assist pathologists in evaluating histopathological images of LN,a 2D Rényi entropy multi-threshold image segmentation method is proposed in this research to apply to LN images.This method is based on an improved cuckoo search(CS)algorithm that introduces a Diffusion Mechanism(DM)and an Adaptiveβ-Hill Climbing(AβHC)strategy called the DMCS algorithm.The DMCS algorithm is tested on 30 benchmark functions of the IEEE CEC2017 dataset.In addition,the DMCS-based multi-threshold image segmentation method is also used to segment renal pathological images.Experimental results show that adding these two strategies improves the DMCS algorithm's ability to find the optimal solution.According to the three image quality evaluation metrics:PSNR,FSIM,and SSIM,the proposed image segmentation method performs well in image segmentation experiments.Our research shows that the DMCS algorithm is a helpful image segmentation method for renal pathological images.

关键词： Multi-threshold image segmentation 2D Rényi entropy Renal pathology cuckoo search algorithm Swarm intelligence algorithms Bionic algorithm

cuckoo search algorithm with Interactive learning for Economic Dispatch

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Cuckoo Search Algorithm with Interactive learning for Econom...