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

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 *** this paper,an orthogonal learning cuckoo search algorithm is used to estimate the parameters of chaotic *** algorithm can combine the stochastic exploration of the cuckoo search and the exploitation capability of the orthogonal learning *** are conducted on the Lorenz system and the Chen *** proposed algorithm is used to estimate the parameters for these two *** 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

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cuckoo search algorithm Inspired by Artificial Bee Colony and Its Application

Cuckoo Search Algorithm Inspired by Artificial Bee Colony an...

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7th International Conference on Swarm Intelligence (ICSI)

作者： Gao, Yin Lei, Xiujuan Dai, Cai Shaanxi Normal Univ Xian Sch Comp Sci Xian 710119 Shaanxi Peoples R China

ISBN: (纸本)9783319410005;9783319409993

cuckoo search algorithm with advanced levy flight strategy, can greatly improve algorithm's searching ability and increase the diversity of population. But it also has some problems. We improve them in this paper. First, in order to address the randomness of levy flight fluctuating significantly in the later and its poor convergence performance, we combine artificial bee colony algorithm with cuckoo search algorithm since artificial bee colony algorithm considers the group learning and cognitive ability, individuals learn from each other in the iterative process, which improves the local search ability of the later, and can find the optimal solution more quickly. Second, we use mutation operation to create the worst nest's position so as to increase the diversity of the population. Then put forward the ABC-M-CS algorithm and use the thought of K-means to cluster UCI data. The experimental results on UCI data sets indicate that ABC-M-CS algorithm has the fastest convergence speed, highest accuracy and stability.

关键词： cuckoo search algorithm Artificial bee colony algorithm Mutation operation Clustering

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Multi-Swarm cuckoo search algorithm with Q-Learning Model

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COMPUTER JOURNAL 2021年第1期64卷 108-131页

作者： Li, Juan Xiao, Dan-dan Zhang, Ting Liu, Chun Li, Yuan-xiang Wang, Gai-ge Wuhan Technol & Business Univ Sch Artificial Intelligence Wuhan 430065 Peoples R China Wuchang Univ Technol Sch Artificial Intelligence Wuhan 430223 Peoples R China Jilin Univ Key Lab Symbol Computat & Knowledge Engn Minist Educ 2699 Qianjin St Changchun 130012 Jilin Peoples R China Wuhan Univ Sch Comp 299 Bayi St Wuhan 430072 Hubei Peoples R China Ocean Univ China Dept Comp Sci & Technol 238 Songling St Qingdao 266100 Shandong Peoples R China Northeast Normal Univ Inst Algorithm & Big Data Anal 5268 Renmin St Changchun 130117 Jilin Peoples R China

As a novel swarm intelligence optimization algorithm, cuckoo search (CS) has been successfully applied to solve diverse problems in the real world. Despite its efficiency and wide use, CS has some disadvantages, such as premature convergence, easy to fall into local optimum and poor balance between exploitation and exploration. In order to improve the optimization performance of the CS algorithm, a new CS extension with multi-swarms and Q-Learning namely MP-QL-CS is proposed. The step size strategy of the CS algorithm is that an individual fitness value is examined based on a one-step evolution effect of an individual instead of evaluating the step size from the multi-step evolution effect. In the MP-QL-CS algorithm, a step size control strategy is considered as action, which is used to examine the individual multi-stepping evolution effect and learn the individual optimal step size by calculating the Q function value. In this way, the MP-QL-CS algorithm can increase the adaptability of individual evolution, and a good balance between diversity and intensification can be achieved. Comparing the MP-QL-CS algorithm with various CS algorithms, variants of differential evolution (DE) and improved particle swarm optimization (PSO) algorithms, the results demonstrate that the MP-QL-CS algorithm is a competitive swarm algorithm.

关键词： cuckoo search algorithm Q-Learning multi-stepping evolution global optimization multi-swarms

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An efficient method for solving the optimal sitting and sizing problem of capacitor banks based on cuckoo search algorithm

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AIN SHAMS ENGINEERING JOURNAL 2018年第4期9卷 589-597页

作者： Devabalaji, K. R. Yuvaraj, T. Ravi, K. VIT Univ Sch Elect Engn Vellore 632014 Tamil Nadu India

In this paper, a new approach to determine the optimal location and sizing of capacitor is being analyzed and the objective function is formulated to minimize power losses and voltage profile of the system subjected to equality and inequality constraints. Voltage stability index (VSI) is implemented to pre-determine the optimal location of capacitor. The newly developed cuckoo search algorithm (CSA) is proposed to determine the optimal size of the capacitor. To check the feasibility of the proposed method, it is tested on IEEE 34-bus and 69-bus radial distribution system with different load factors. The simulated results demonstrate well the performance and effectiveness of the proposed method. (C) 2016 Ain Shams University.

关键词： cuckoo search algorithm Power loss minimization Voltage stability index Voltage profile index Distribution system

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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 *** 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 ***,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,*** a nonconvex optimization model for cooperatively jamming netted radar system is ***,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 *** 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

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A waveform decomposition technique based on wavelet function and differential cuckoo search algorithm

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SOFT COMPUTING 2021年第8期25卷 5909-5923页

作者： Wang, Mingwei Xiong, Shuai Chen, Maolin He, Peipei China Univ Geosci Inst Geol Survey Wuhan 430074 Peoples R China Natl Adm Surveying Mapping & Geoinformat Key Lab Natl Geog Census & Monitoring Wuhan 430079 Peoples R China Chongqing Jiaotong Univ Sch Civil Engn Chongqing 400074 Peoples R China North China Univ Water Resources & Elect Power Coll Surveying & Geoinformat Zhengzhou 450045 Peoples R China

Waveform decomposition is widely used for the separation of echoes from full-waveform LiDAR (FWL) signal, and some previous studies employed Gaussian function for laser pulse modeling and waveform decomposition. However, it was difficult to guarantee the waveform parameters on the neighbor of optimal solution, because of the limited amplitude range. In addition, waveform parameters were usually set by the amplitude and location of inflection points, which may enlarge the difference between decomposed and original waveforms. Hence, a novel waveform decomposition technique based on wavelet function and differential cuckoo search algorithm is proposed, where wavelet function has a high-order vanishing moment, cuckoo search algorithm has a strong optimization ability, and differential operator avoids trapping into the local optima. The proposed technique is tested on airborne FWL point cloud and compared with other corresponding approaches, experimental results demonstrate that the decomposed waveforms are obtained with a reasonable convergence rate and feature characterization, as the rRMSE is lower than 7% for all of waveforms, the whole process of waveform decomposition only takes 0.3s, and waveform parameters are used as the features to recognize different objects from point cloud.

关键词： Full-waveform LiDAR Waveform decomposition Wavelet function cuckoo search algorithm Differential operator

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Optimum design of steel frames using cuckoo search algorithm with Levy flights

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STRUCTURAL DESIGN OF TALL AND SPECIAL BUILDINGS 2013年第13期22卷 1023-1036页

作者： Kaveh, A. Bakhshpoori, T. Iran Univ Sci & Technol Sch Civil Engn Ctr Excellence Fundamental Studies Struct Engn Tehran 16 Iran

In the last two decades, many researchers have implemented various kinds of meta-heuristic algorithms in order to overcome the complex nature of the optimum design of structures. In this paper, the optimum design of two-dimensional steel frames for discrete variables based on the cuckoo search (CS) algorithm is developed. The CS is one of the recently developed population-based algorithms inspired by the behavior of some cuckoo species in combination with the Levy flight behavior of some birds and insects. The design algorithm is supposed to obtain minimum weight frame through suitable selection of sections from a standard set of steel sections such as the American Institute of Steel Construction (AISC) wide-flange (W) shapes. Strength constraints of AISC load and resistance factor design specification and displacement constraints are imposed on frames. In order to demonstrate the effectiveness and robustness of the CS, low-weight design and performance comparisons are made between the CS and other algorithms for some benchmark frames. Copyright (c) 2011 John Wiley & Sons, Ltd.

关键词： optimal design frame structures cuckoo search algorithm Levy flights steel structures meta-heuristic

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A multi-strategy hybrid cuckoo search algorithm with specular reflection based on a population linear decreasing strategy

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INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 2024年第12期15卷 5683-5723页

作者： Ouyang, Chengtian Liu, Xin Zhu, Donglin Zheng, Yangyang Zhou, Changjun Zou, Chengye Jiangxi Univ Sci & Technol Sch Informat Engn Ganzhou 341000 Peoples R China Zhejiang Normal Univ Sch Comp Sci & Technol Jinhua 321004 Peoples R China Yanshan Univ Coll Informat Sci & Engn Qinhuangdao 066004 Peoples R China

The cuckoo search algorithm (CS), an algorithm inspired by the nest-parasitic breeding behavior of cuckoos, has proved its own effectiveness as a problem-solving approach in many fields since it was proposed. Nevertheless, the cuckoo search algorithm still suffers from an imbalance between exploration and exploitation as well as a tendency to fall into local optimization. In this paper, we propose a new hybrid cuckoo search algorithm (LHCS) based on linear decreasing of populations, and in order to optimize the local search of the algorithm and make the algorithm converge quickly, we mix the solution updating strategy of the Grey Yours sincerely, wolf optimizer (GWO) and use the linear decreasing rule to adjust the calling ratio of the strategy in order to balance the global exploration and the local exploitation;Second, the addition of a specular reflection learning strategy enhances the algorithm's ability to jump out of local optima;Finally, the convergence ability of the algorithm on different intervals and the adaptive ability of population diversity are improved using a population linear decreasing strategy. The experimental results on 29 benchmark functions from the CEC2017 test set show that the LHCS algorithm has significant superiority and stability over other algorithms when the quality of all solutions is considered together. In order to further verify the performance of the proposed algorithm in this paper, we applied the algorithm to engineering problems, functional tests, and Wilcoxon test results show that the comprehensive performance of the LHCS algorithm outperforms the other 14 state-of-the-art algorithms. In several engineering optimization problems, the practicality and effectiveness of the LHCS algorithm are verified, and the design cost can be greatly reduced by applying it to real engineering problems.

关键词： cuckoo search algorithm Grey wolf optimizer Specular reflection learning Linearly decreasing populations CEC2017 Engineering optimization problems

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Characterization modeling of wake vortex circulation decay under reasonable worst case conditions with cuckoo search algorithm

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING 2024年第5期238卷 455-472页

作者： Oruc, Ridvan Baklacioglu, Tolga Sahin, Ozlem Agri Ibrahim Cecen Univ Civil Aviat Vocat Sch Agri Turkiye Eskisehir Tech Univ Fac Aeronaut & Astronaut 2 Eylul Kampusu Havacil & Uzay Bil Fak TR-26555 Eskisehir Turkiye Turkish Aerosp Ind TUSAS Aircraft Performance Dept TAI Ankara Turkiye

Wake vortex (WV) produced by a large aircraft has the potential to cause serious damage to smaller aircraft following it. In this context, characterization of WV circulation decay under the reasonable worst case (RWC) conditions allows the separation minima to be found safely. In this study, modeling of dimensionless decay curves, which were developed using three experimental LIDAR (Light Detection and Ranging) datasets in the RECAT-EU project and is a useful tool to characterize the wake vortex circulation decay under RWC conditions, was carried out using cuckoo search algorithm (CSA). The decay curves used in the modeling are the median (P50), 10th (P10), and 90th (P90) percentile decay curves of the RWC tracks, which constitute the top 2% longest lasting wakes. The fact that the correlation coefficient (R) values are very close to 1 for all datasets as a result of the error analysis shows that the prediction success of the CSA model is quite high.

关键词： Aircraft wake vortex turbulence cuckoo search algorithm optimization

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Health monitoring of steel structures using cuckoo search algorithm-based ANN

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STRUCTURES 2024年 61卷

作者： Thankachan, Prince Fida, A. Pillai, T. M. Madhavan Natl Inst Technol Calicut Dept Civil Engn Kozhikode 673601 Kerala India

The application of various computational methods in Structural Health Monitoring (SHM) of structures are gaining importance. One of the methodologies used is Artificial Neural Network (ANN). Though ANN can handle complex nonlinear functions that are intractable using traditional methods, the gradient descent nature of back propagation algorithms in ANN traps the solution in local minima, which prohibit it from finding the best solution. This can be resolved using various evolution algorithm combining with Artificial Neural Network, such as cuckoo search (CS) algorithm, Genetic algorithm (GA), Particle Swarm Optimisation (PSO) etc. This study presents a strategy SHM using a flexible combination of ANN and CS algorithm. This nature-inspired metaheuristic algorithm can train the parameters of ANN and can reduce the variation between the actual and predicted output. The strategy is applied on a steel truss bridge and a lattice offshore platform structure and its robustness is compared. Different damage scenarios were also considered. The study demonstrated the superiority of ANN-CS approach over ANN alone. Though ANN predicts the damage with the help of adequate vibrational data, ANN combined with cuckoo search algorithm shows good improvement in predicting the damage with lesser training data set.

关键词： Artificial Neural Network cuckoo search algorithm Health monitoring Steel structures Vibration-based damage detection

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