Relevant bibliographies by topics / Cuckoo Search (CS) Algorithm

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Cuckoo Search (CS) Algorithm'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Cuckoo Search (CS) Algorithm"

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Elkhechafi, Mariam, Hanaa Hachimi, and Youssfi Elkettani. "A new hybrid cuckoo search and firefly optimization." Monte Carlo Methods and Applications 24, no. 1 (2018): 71–77. http://dx.doi.org/10.1515/mcma-2018-0003.

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Abstract In this paper, we present a new hybrid algorithm which is a combination of a hybrid Cuckoo search algorithm and Firefly optimization. We focus in this research on a hybrid method combining two heuristic optimization techniques, Cuckoo Search (CS) and Firefly Algorithm (FA) for the global optimization. Denoted as CS-FA. The hybrid CS-FA technique incorporates concepts from CS and FA and creates individuals in a new generation not only by random walk as found in CS but also by mechanisms of FA. To analyze the benefits of hybridization, we have comparatively evaluated the classical Cucko
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Li, Juan, Dan-dan Xiao, Hong Lei, Ting Zhang, and Tian Tian. "Using Cuckoo Search Algorithm with Q-Learning and Genetic Operation to Solve the Problem of Logistics Distribution Center Location." Mathematics 8, no. 2 (2020): 149. http://dx.doi.org/10.3390/math8020149.

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Cuckoo search (CS) algorithm is a novel swarm intelligence optimization algorithm, which is successfully applied to solve some optimization problems. However, it has some disadvantages, as it is easily trapped in local optimal solutions. Therefore, in this work, a new CS extension with Q-Learning step size and genetic operator, namely dynamic step size cuckoo search algorithm (DMQL-CS), is proposed. Step size control strategy is considered as action in DMQL-CS algorithm, which is used to examine the individual multi-step evolution effect and learn the individual optimal step size by calculatin
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Xue, Yi Ge, and Hui Wen Deng. "The Cuckoo Search Algorithm Based on Dynamic Grouping to Adjust Flight Scale." Applied Mechanics and Materials 543-547 (March 2014): 1822–26. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.1822.

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The cuckoo search (CS) algorithm is a very efficient swarm optimization algorithm. Based on CS, a cuckoo search algorithm based on dynamic grouping to adjust flight scale (DGCS) is proposed: All cuckoos are divided into three groups according to the fitness of the individual and the average fitness of the population, then different flight scale is adopted dynamically for each group. Simulation experiments show that the DGCS can quickly converge to the global optimum solution, and has better optimization performance.
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楊恙, 楊恙, Xukun Zuo Yang Yang, Maosheng Fu Xukun Zuo, Shuhao Yu Maosheng Fu, and Chaochuan Jia Shuhao Yu. "Adaptive Cuckoo Search Algorithm Based on Dynamic Adjustment Mechanism." 電腦學刊 32, no. 5 (2021): 171–83. http://dx.doi.org/10.53106/199115992021103205014.

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Cuckoo Search (CS) algorithm, a simple and effective global optimization algorithm, has been widely used to deal with practical optimization problems. So as to improvethe standard cuckoo search algorithm, such as slow convergence and easy convergence to local optimal value, an Adaptive Cuckoo Search algorithm on the basis of Dynamic Adjustment Mechanism (ACSDAM) has been proposed. Based on exponential function and logarithmic function, the dynamic adjustment is made for updating step size and discovering probability. During the optimization process, updating step size and discovering probabili
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Alkhateeb, Faisal, and Bilal H. Abed-alguni. "A Hybrid Cuckoo Search and Simulated Annealing Algorithm." Journal of Intelligent Systems 28, no. 4 (2019): 683–98. http://dx.doi.org/10.1515/jisys-2017-0268.

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Abstract Simulated annealing (SA) proved its success as a single-state optimization search algorithm for both discrete and continuous problems. On the contrary, cuckoo search (CS) is one of the well-known population-based search algorithms that could be used for optimizing some problems with continuous domains. This paper provides a hybrid algorithm using the CS and SA algorithms. The main goal behind our hybridization is to improve the solutions generated by CS using SA to explore the search space in an efficient manner. More precisely, we introduce four variations of the proposed hybrid algo
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Bentouati, Bachir, Saliha Chettih, Rabah Djekidel, and Ragab Abdel-Aziz El-Sehiemy. "An Efficient Chaotic Cuckoo Search Framework for Solving Non-Convex Optimal Power Flow Problem." International Journal of Engineering Research in Africa 33 (November 2017): 84–99. http://dx.doi.org/10.4028/www.scientific.net/jera.33.84.

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The optimal power flow (OPF) problem is a very complicated task in power systems. OPF problem has a set of equality and inequality constraints. This paper looks at a chaotic cuckoo search (CCS) algorithm for solving non-convex OPF problem. The proposed CCS is a bio-inspired optimization calculation that is inspired by the behaviour of cuckoos people in nature. The chaotic guide is a variation of qualities combined with CS. A sinusoidal chaotic is integrated with CS algorithm and tested on standard IEEE 30-bus test system to the point of improving its global speed of convergence and enhancing i
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Liao, Qixiang, Shudao Zhou, Hanqing Shi, and Weilai Shi. "Parameter Estimation of Nonlinear Systems by Dynamic Cuckoo Search." Neural Computation 29, no. 4 (2017): 1103–23. http://dx.doi.org/10.1162/neco_a_00946.

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In order to address with the problem of the traditional or improved cuckoo search (CS) algorithm, we propose a dynamic adaptive cuckoo search with crossover operator (DACS-CO) algorithm. Normally, the parameters of the CS algorithm are kept constant or adapted by empirical equation that may result in decreasing the efficiency of the algorithm. In order to solve the problem, a feedback control scheme of algorithm parameters is adopted in cuckoo search; Rechenberg’s 1/5 criterion, combined with a learning strategy, is used to evaluate the evolution process. In addition, there are no information
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Huang, Changlong, Ling Pei, and Qi Ouyang. "Research on the Cuckoo Algorithm for Flexible Workshop Scheduling Problems." Frontiers in Computing and Intelligent Systems 3, no. 1 (2023): 177–81. http://dx.doi.org/10.54097/fcis.v3i1.6365.

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As a typical combinatorial optimization problem, the essence of the solution to the scheduling problem is to formulate a reasonable scheduling scheme to arrange and allocate production resources, thereby obtaining the optimal scheduling result. The Cuckoo Search Algorithm (CS), a revolutionary meta-heuristic, is based on the cuckoo's breeding behavior and combines Lévy flight and random walk strategies to more efficiently attain the search goal. CS algorithm has been extensively employed in a variety of intricate combinatorial optimization issues, with its few parameters, precise resolution, r
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Mohanty, Preeti Pragyan, and Subrat Kumar Nayak. "A Modified Cuckoo Search Algorithm for Data Clustering." International Journal of Applied Metaheuristic Computing 13, no. 1 (2022): 1–32. http://dx.doi.org/10.4018/ijamc.2022010101.

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Clustering of data is one of the necessary data mining techniques, where similar objects are grouped in the same cluster. In recent years, many nature-inspired based clustering techniques have been proposed, which have led to some encouraging results. This paper proposes a Modified Cuckoo Search (MoCS) algorithm. In this proposed work, an attempt has been made to balance the exploration of the Cuckoo Search (CS) algorithm and to increase the potential of the exploration to avoid premature convergence. This algorithm is tested using fifteen benchmark test functions and is proved as an efficient
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Mohamad, Azizah, Azlan Mohd Zain, Nor Erne Nazira Bazin, and Amirmudin Udin. "Cuckoo Search Algorithm for Optimization Problems - A Literature Review." Applied Mechanics and Materials 421 (September 2013): 502–6. http://dx.doi.org/10.4028/www.scientific.net/amm.421.502.

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Cuckoo Search (CS) is an optimization algorithm developed by Yang and Deb in 2009. This paper describes an overview of CS which is inspired by the life of a bird family, called Cuckoo as well as overview of CS applications in various categories for solving optimization problems. Special lifestyle of Cuckoo and their characteristics in egg laying and breeding has been the basic motivation for this optimization algorithm. The categories that reviewed are Engineering, Pattern Recognition, Software Testing & Data Generation, Networking, Job Scheduling and Data Fusion and Wireless Sensor Networ
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Dissertations / Theses on the topic "Cuckoo Search (CS) Algorithm"

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Lidberg, Simon. "Evolving Cuckoo Search : From single-objective to multi-objective." Thesis, Högskolan i Skövde, Institutionen för teknik och samhälle, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-5309.

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This thesis aims to produce a novel multi-objective algorithm that is based on Cuckoo Search by Dr. Xin-She Yang. Cuckoo Search is a promising nature-inspired meta-heuristic optimization algorithm, which currently is only able to solve single-objective optimization problems. After an introduction, a number of theoretical points are presented as a basis for the decision of which algorithms to hybridize Cuckoo Search with. These are then reviewed in detail and verified against current benchmark algorithms to evaluate their efficiency. To test the proposed algorithm in a new setting, a real-world
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Lakshminarayanan, Srinivasan. "Nature Inspired Discrete Integer Cuckoo Search Algorithm for Optimal Planned Generator Maintenance Scheduling." University of Toledo / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1438101954.

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Lyu, Sih-Sian, and 呂思賢. "Improved Dynamic Adaptation Cuckoo Search Algorithm." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/08482734801983283086.

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碩士<br>義守大學<br>資訊管理學系<br>102<br>This study for Cuckoo Search (CS) and Lévy flight mechanisms were discussed. In order to further improve the efficiency of Cuckoo Search, use it as a framework for improved to enhance search capabilities. Therefore, this study refers to a lot of literature, presented the Improved Dynamic Adaptation Cuckoo Search Algorithm (IDACS). In order to validate the presented IDACS search capabilities, two experiments were discussed. First, the function experiment. Second, for the UCI database of real experimental data did Artificial Neural Network training. Finally the res
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Katta, J. "Optimization of conical antenna array synthesis using modified cuckoo search algorithm." Thesis, 2014. http://ethesis.nitrkl.ac.in/6220/1/E-20.pdf.

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This thesis presents a modelling of conical antenna array (CAA) and synthesizing this array for a radiation pattern using modified cuckoo algorithm (MCS). Conventional arrays are also taken up as a preliminary study and optimisation of basic geometrics like linear and circular antenna arrays. The modelling carried out by tuning the antenna array parameters like amplitude excitation, complex amplitude excitation and angular distance. Analysis on the conventional and conformal geometries are carried out aiming for a desired pattern. Analysed simulation results gives the insight that, modelled co
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NUGRAHA, DIMAS AJI, and DIMAS AJI NUGRAHA. "A Novel MPPT Method Based on Cuckoo Search Algorithm and Golden Section Search Algorithm for Partially Shaded PV System." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/4hr2yd.

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碩士<br>國立臺灣科技大學<br>電機工程系<br>107<br>Partial shading is a common and difficult problem to be solved in a photovoltaic (PV) system. Numerous efforts have been introduced to mitigate this problem. Some commonly used approaches are deploying some meta-heuristic (MH) algorithm to track the multiple peak P - V curve of partially shaded PV system. Cuckoo Search (CS) is a new optimization algorithm based on MH approach. It has been used to solve optimization problems in many applications including Maximum Power Point Tracking (MPPT) problem. CS algorithm performs well in tracking the Global Maximum Powe
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Saraswathi, M. B. L. "Optimal Path Planning of Mobile Robot using Hybrid Cuckoo Search-Bat Algorithm." Thesis, 2018. http://ethesis.nitrkl.ac.in/9913/1/2018_MT_216ID1329_MSaraswathi_Optimal.pdf.

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The mobile robot path planning depends on sensing the data, map building and planning the path according to the prescribed environment. Many researchers have followed different techniques to get the optimal path. In the Earlier days, mathematical model has been developed to get the optimal path but the result obtained was very poor. After that, so many Soft computing techniques have been developed, but the major drawback is that they consumes more time to find the optimal path. These algorithms sometimes fall under local optima during execution. In this thesis a mobile robot path planning is o
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CáceresVera, Lucio José Fernando, and 高子睿. "Design and Optimization of a Permanent Magnet Traction Motor Using Cuckoo Search Algorithm." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/u28p54.

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碩士<br>國立成功大學<br>系統及船舶機電工程學系<br>105<br>This thesis presents a new method to design and optimize a Fractional Slot Concentrated Winding Interior Permanent Magnet Synchronous Motor (FSCWIPMSM) for wide Constant Power Speed Range (CPSR). The designed electric traction motor for a particular EV application (Scooter), was optimized and built with the purpose of achieving wide CPSR, low torque ripple and high efficiency. A brief study of the influence of slot-pole combination on Fractional Slot Concentrated Winding (FSCW) motors were conducted in order to reduce the torque ripple of the motor at high
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Chou, Tzu-Shuang, and 周子雙. "Shape and Sizing Optimization of Truss Structure with Frequency Constraints Using Cuckoo Search Algorithm." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/bmzawm.

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碩士<br>國立交通大學<br>土木工程系所<br>107<br>Taiwan has many earthquake because it situates in Circum-Pacific Seismic Belt. Many engineering structures are subjected to dynamic excitation, which may lead to undesirable vibrations. The multiple natural frequency bounds in truss optimization problems can improve dynamic behaviour of structures. However, natural frequencies and constraints of the foregoing optimization problems are highly nonlinear, nonconvex and greatly sensitive to shape changes and member sizes of truss structures. Vibration modes and corresponding obtained frequencies may switch during t
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Gninkeu, Tchapda Ghislain Yanick. "Application of improved particle swarm optimization in economic dispatch of power systems." Diss., 2018. http://hdl.handle.net/10500/24428.

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Economic dispatch is an important optimization challenge in power systems. It helps to find the optimal output power of a number of generating units that satisfy the system load demand at the cheapest cost, considering equality and inequality constraints. Many nature inspired algorithms have been broadly applied to tackle it such as particle swarm optimization. In this dissertation, two improved particle swarm optimization techniques are proposed to solve economic dispatch problems. The first is a hybrid technique with Bat algorithm. Particle swarm optimization as the main optimizer integrates
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Books on the topic "Cuckoo Search (CS) Algorithm"

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Yang, Xin-She, ed. Cuckoo Search and Firefly Algorithm. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-02141-6.

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Dey, Nilanjan, ed. Applications of Cuckoo Search Algorithm and its Variants. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-5163-5.

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Yang, Xin-She. Cuckoo Search and Firefly Algorithm: Theory and Applications. Springer International Publishing AG, 2016.

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Yang, Xin-She. Cuckoo Search and Firefly Algorithm: Theory and Applications. Springer, 2013.

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Dey, Nilanjan. Applications of Cuckoo Search Algorithm and Its Variants. Springer Singapore Pte. Limited, 2021.

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Dey, Nilanjan. Applications of Cuckoo Search Algorithm and its Variants. Springer, 2020.

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Dey, Nilanjan. Applications of Cuckoo Search Algorithm and its Variants. Springer, 2020.

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Yang, Xin-She. Cuckoo Search and Firefly Algorithm: Theory and Applications. Springer London, Limited, 2013.

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Shehab, Mohammad. Artificial Intelligence in Diffusion MRI: Enhanced Cuckoo Search Algorithm with Metaheuristic Components for Extracting the Maxima of the Orientation ... Springer, 2019.

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Shehab, Mohammad. Artificial Intelligence in Diffusion MRI: Enhanced Cuckoo Search Algorithm with Metaheuristic Components for Extracting the Maxima of the Orientation ... Springer, 2020.

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Book chapters on the topic "Cuckoo Search (CS) Algorithm"

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Cuevas, Erik, and Alma Rodríguez. "Cuckoo Search (CS) Algorithm." In Metaheuristic Computation with MATLAB®. Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781003006312-8.

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Tiachacht, S., S. Khatir, M. Slimani, A. Behtani, C. Le Thanh, and M. Abdel Wahab. "Model Updating of Frame Structure Using Equilibrium Optimizer (EO) and Cuckoo Search (CS) Algorithms." In Lecture Notes in Civil Engineering. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0945-9_2.

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Shehab, Mohammad. "Cuckoo Search Algorithm." In Artificial Intelligence in Diffusion MRI. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36083-2_3.

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Kaveh, Ali, and Taha Bakhshpoori. "Cuckoo Search Algorithm." In Metaheuristics: Outlines, MATLAB Codes and Examples. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04067-3_7.

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Yang, Xin-She, and Adam Slowik. "Cuckoo Search Algorithm." In Swarm Intelligence Algorithms. CRC Press, 2020. http://dx.doi.org/10.1201/9780429422614-9.

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Zolghadr-Asli, Babak. "Cuckoo Search Algorithm." In Computational Intelligence-based Optimization Algorithms. CRC Press, 2023. http://dx.doi.org/10.1201/9781003424765-13.

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Wang, Shi, Shuangyu Song, Yang Yu, Zhe Xu, Hanaki Yachi, and Shangce Gao. "Multiple Chaotic Cuckoo Search Algorithm." In Lecture Notes in Computer Science. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61824-1_58.

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Sahoo, Mitali Madhusmita, Rasmita Dash, Rajashree Dash, and Rasmita Rautray. "Cuckoo Search Algorithm: A Review." In Lecture Notes in Electrical Engineering. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1420-3_124.

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Fister, Iztok, Xin-She Yang, Janez Brest, and Iztok Fister. "On the Randomized Firefly Algorithm." In Cuckoo Search and Firefly Algorithm. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02141-6_2.

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Varshney, Megha, Pravesh Kumar, and Tarun Kumar Sharma. "CS-Jaya: Hybridization of Cuckoo and Jaya Algorithm." In Soft Computing: Theories and Applications. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9858-4_73.

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Conference papers on the topic "Cuckoo Search (CS) Algorithm"

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Bargali, Anushka, and Sandeep Kumar Sunori. "Optimization of Biosensor Parameters using Cuckoo Search Algorithm." In 2025 7th International Conference on Inventive Material Science and Applications (ICIMA). IEEE, 2025. https://doi.org/10.1109/icima64861.2025.11073996.

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Jain, Shilpa, Sandeep Kumar Sunori, Amit Mittal, and Pradeep Juneja. "Cuckoo Search Algorithm Based Intrusion Detection System of Cybersecurity." In 2025 6th International Conference on Mobile Computing and Sustainable Informatics (ICMCSI). IEEE, 2025. https://doi.org/10.1109/icmcsi64620.2025.10883367.

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Wei, Jiamin, YangQuan Chen, Yongguang Yu, and Yuquan Chen. "Improving Cuckoo Search Algorithm With Mittag-Leffler Distribution." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-97709.

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Abstract Cuckoo search (CS), as one of the recent nature-inspired metaheuristic algorithms, has proved to be an efficient approach due to the combination of Lévy flights, local search capabilities and guaranteed global convergence. CS uses Lévy flights in global random walk to explore the search space. The Lévy step is taken from the Lévy distribution which is a heavy-tailed probability distribution. In this case, a fraction of large steps are generated, which plays an important role in enhancing search capability of CS. Besides, although many foragers and wandering animals have been shown to
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Yongxiang, He, and Guo Hongwu. "Electric Atuator Modeling Based on Modified Cuckoo Search(CS) Algorithm." In 2019 Chinese Automation Congress (CAC). IEEE, 2019. http://dx.doi.org/10.1109/cac48633.2019.8996372.

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Mohamad, A., A. Mohd Zain, S. Sharif, N. Mohd Yusof, F. Najarian, and R. Abdul Jalil. "Optimization of cylindricity in deep hole drilling using Cuckoo search algorithm (CS)." In PROCEEDINGS OF GREEN DESIGN AND MANUFACTURE 2020. AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0044686.

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MAHMOOD, Ahmad Muinuddin. "Refinement of tuned mass damper parameters on machine support structure using dynamic cuckoo search algorithm." In Civil and Environmental Engineering for Resilient, Smart and Sustainable Solutions. Materials Research Forum LLC, 2025. https://doi.org/10.21741/9781644903414-26.

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Abstract. A classical Tuned Mass Damper (TMD) consists of a mass, spring, and viscous damper, typically optimized in the frequency domain to minimize the steady-state displacement amplitude of a primary structure under harmonic force excitation with varying frequency. This study proposes the use of a dynamic Cuckoo Search (CS) algorithm, a nature-inspired optimization method, to enhance the accuracy of TMD parameters when external factors, such as excitation frequency or structural properties, change. The research aims to optimize key TMD parameters (mass ratio, damping ratio, and frequency ra
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Zefan, Cai, and Yang Xiaodong. "Cuckoo search algorithm with deep search." In 2017 3rd IEEE International Conference on Computer and Communications (ICCC). IEEE, 2017. http://dx.doi.org/10.1109/compcomm.2017.8322934.

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Ge, Gengyu, Kun Shen, Maoqiang Yang, and Xuyu Peng. "Powell-based Cuckoo Search Algorithm." In 2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD). IEEE, 2018. http://dx.doi.org/10.1109/fskd.2018.8687161.

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Zheng, Runyu. "An Improved Cuckoo Search Algorithm." In 2021 7th International Conference on Systems and Informatics (ICSAI). IEEE, 2021. http://dx.doi.org/10.1109/icsai53574.2021.9664073.

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Peng, Hu, Changshou Deng, Hui Wang, Wenjun Wang, Xinyu Zhou, and Zhijian Wu. "Gaussian bare-bones cuckoo search algorithm." In GECCO '18: Genetic and Evolutionary Computation Conference. ACM, 2018. http://dx.doi.org/10.1145/3205651.3205666.

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