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

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 *** the increase of the codeword length and constraint length,the search space expands exponentially,and thus it limits the application of these methods in *** 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 ***,by using soft-decision data,the probability that a parity check equation holds is ***,solving the parity check equations is converted to maximize the joint probability that parity check equations ***,based on the standard cuckoo search algorithm,the established cost function is *** to the final solution of the optimization problem,the generator matrix of recursive systematic convolutional code is *** with the existing methods,our proposed method does not need to search for the generator matrix exhaustively and has high ***,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

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Parameter Control Based cuckoo search algorithm for Numerical Optimization

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NEURAL PROCESSING LETTERS 2022年第4期54卷 3173-3200页

作者： Cheng, Jiatang Xiong, Yan Guilin Univ Technol Coll Mech & Control Engn Guilin 541006 Peoples R China

cuckoo search (CS) algorithm is an efficient search technique for addressing numerical optimization problems. However, for the basic CS, the step size and mutation factor are sensitive to the optimization problems being solved. In view of this consideration, a new version namely the parameter control based CS (PCCS) algorithm is presented to strengthen the search accuracy and robustness. In this variant, the step size and mutation factor are dynamically updated according to the elite information stored in the historical archives at each generation, so as to realize the reasonable setting of these control parameters. For performance evaluation, numerical experiments are conducted on 25 benchmark functions from two different test suites. Moreover, the application in neural network optimization is also considered to further investigate the effectiveness. Experimental results indicate that the proposed PCCS algorithm is a promising and competitive method in terms of solution quality and convergence rate.

关键词： cuckoo search algorithm Parameter control Historical archive Numerical optimization

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Application of cuckoo search algorithm to estimate peak particle velocity in mine blasting

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ENGINEERING WITH COMPUTERS 2017年第2期33卷 181-189页

作者： Fouladgar, Nazanin Hasanipanah, Mahdi Amnieh, Hassan Bakhshandeh Islamic Azad Univ Isfahan Khorasgan Branch Young Researchers & Elite Club Esfahan Iran Islamic Azad Univ Qom Branch Young Researchers & Elite Club Qom Iran Univ Tehran Sch Min Coll Engn Tehran 111554563 Iran

Ground vibration is one of the most undesirable effects of blasting operation in surface mines. Therefore, it seems that the prediction of ground vibrations with a high degree of accuracy is necessary to reduce environmental effects. This article proposes a novel swarm intelligence algorithm based on cuckoo search (NSICS) to create a precise equation for predicting the ground vibration produced by blasting operations in Miduk copper mine, Iran. To evaluate the proposed NSICS model, several empirical equations were also utilized. In this regard, 85 blasting events were considered, and the values of two effective parameters on the ground vibration, namely, maximum charge used per delay and distance between blast face and monitoring station, were measured. In addition, the values of peck particle velocity (PPV), as a vibration descriptor, were recorded in each blasting. Two performance indices, i.e., root mean square error and coefficient of multiple correlation (R-2), were used to determine the performance capacity of the proposed models. Comparing the values predicted by the models demonstrated that the proposed equation by NSICS is more reliable than empirical equations in predicting the PPV.

关键词： Blasting operation Ground vibration cuckoo search algorithm NSICS

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Optimal design of fractional delay FIR filter using cuckoo search algorithm

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INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS 2018年第12期46卷 2364-2379页

作者： Kumar, Manjeet Bennett Univ Dept Elect & Commun Engn Greater Noida 201310 Uttar Pradesh India

The conventional gradient-based optimization methods are not sufficient to optimize nonlinear, multimodal, and nonuniform objective functions of fractional delay FIR (FD-FIR) filters, and the objective function cannot converge to the global minimum solution. So a population-based meta-heuristic optimization algorithm called as cuckoo search algorithm (CSA) has been implemented in the design of optimal FD-FIR filter. cuckoo search algorithm is based on lifestyle and unique parasitic behavior in egg laying and breeding of some cuckoo species along with Levy flight behavior of some birds and fruit flies. To attain a balance between exploration and exploitation in the search space, different set of control parameters is tested by simulation. Extensive simulations were performed to ensure how CSA exploits in the design of optimal FD-FIR filter. A quantitative assessment of the proposed CSA-based method is accomplished using several performance metric such as magnitude error, convergence rate, and optimal solution. The simulation results reveal the advantages of the proposed FD filter using CSA compared with the FD filter designed using evolutionary algorithm like genetic algorithm and conventional FD filter design methods such as Lagrange, discrete Hartley transform, discrete Fourier transform, discrete cosine transform, and radial basis function methods.

关键词： cuckoo search algorithm FD-FIR filter genetic algorithm Levy flight meta-heuristics

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Modeling of environmental effect factor and exergetic sustainability index with cuckoo search algorithm for a business jet

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AIRCRAFT ENGINEERING AND AEROSPACE TECHNOLOGY 2022年第7期94卷 1157-1169页

作者： Oruc, Ridvan Baklacioglu, Tolga Turan, Onder Aydin, Hakan Kastamonu Univ Sch Civil Aviat Dept Airframe & Powerplant Maintenance Kastamonu Turkey Eskisehir Tech Univ Fac Aeronaut & Astronaut Dept Airframe & Powerplant Maintenance Eskisehir Turkey Tusas Engine Ind Inc Eskisehir Turkey

Purpose The purpose of this paper is to create models that predict exergetic sustainability index (ESI) and environmental effect factor (EEF) values with high accuracy according to various engine parameters. Design/methodology/approach In this study, models were created to estimate ESI and EEF sustainability parameters in various flight phases for a business jet with a turboprop engine using the cuckoo search algorithm (CSA) method. The database used for modeling includes the various engine parameters (torque, engine airflow, gas generator speed, fuel mass flow, power and air-fuel ratio) obtained by running a business aircraft engine more than once at different settings and the actual ESI and EEF values obtained depending on these parameters. In addition, sensitivity analysis was performed to measure the effect of engine parameters on the models. Finally, the effect of the CSA number of nest (n) parameter on the model accuracy was investigated. Findings It has been observed that the models predict ESI and EEF values with high accuracy. As a result of the sensitivity analysis, it was seen that the air-fuel ratio had a greater effect on the output parameters. Practical implications These models are thought to assist in the exergetic environment analysis used to find the greatest losses for turboprop business jets and identify their causes and further improve system performance. Thus, they will be a useful tool to minimize the negative impact of business jet on environmental sustainability. Originality/value To the best of the authors' knowledge, this study stands out in the literature because it is the first exergo-metaheuristic approach developed with CSA for business aircraft engine;moreover, the data set used consists of real values.

关键词： Sustainability Aircraft Turboprop cuckoo search algorithm Environmental effect

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An efficient adaptive thresholding function optimized by a cuckoo search algorithm for a despeckling filter of medical ultrasound images

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JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING 2020年第11期14卷 15429-15454页

作者： WangNo, Nitit Chiewchanwattana, Sirapat Sunat, Khamron Khon Kaen Univ Fac Sci Dept Comp Sci Khon Kaen 40002 Thailand

In this research paper, we propose an efficient adaptive thresholding function optimized by a cuckoo search algorithm for despeckling filters to avoid boundaries created by more than a few current despeckling filters. The speckle noise contamination caused at some points in ultrasound picture acquisition systems compromises the level of its visuality, which presents a diagnostic challenge for medical doctors. Therefore, to enhance the visual quality, despeckling filters are normally employed in the processing of such pictures. However, several disadvantages have developed within current despeckling filters, which have discouraged the utilization of modern despeckling filters for minimizing impacts from speckle noise. The proposed despeckling filter was developed through a combination of an adaptive thresholding function and a cuckoo search algorithm. Specifically, the aforementioned cuckoo search algorithm optimizes the coefficients of the thresholding function. Additionally, the proposed approach it can be used in a no-reference as well as in a full-reference image quality assessment which the assessment of PSNR, SSIM, MSE and MAE values was used to evaluate the proposed despeckling filter, as well as others, in medical ultrasound images. The findings from the research show that the visual outcome acquired by the proposed filter is inferior to those of filters with a despeckling effect. In addition, the numerical results revealed that the proposed despeckling filter was effective in creating ultrasound imageries for clinical use.

关键词： Thresholding function Despeckling Ultrasound image cuckoo search algorithm

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Estimation of Deep-Seated Faults Parameters from Gravity Data Using the cuckoo search algorithm

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PURE AND APPLIED GEOPHYSICS 2023年第12期180卷 4147-4173页

作者： Ozyalin, Senol Tuncel, Aykut Dokuz Eylul Univ Engn Fac Dept Geophys Engn TR-35160 Izmir Turkiye

cuckoo search algorithm (CSA) is a nature-inspired metaheuristic optimization algorithm. The optimization algorithm was inspired by the life story of a family of birds called the cuckoo. In this paper, an application of the CSA, is implemented to estimate model parameters of deep-seated faults by using gravity anomalies. To increase the efficiency of the algorithm, parameter tuning studies are carried out for the optimum algorithm-based control parameters. In addition, the reliability and possible uncertainties of the obtained solutions were examined using probability density function analysis. The model parameters (z1, z2, alpha, x0 and rho) for noisy and noise-free synthetic models were obtained by using CSA. These obtained parameters are very compatible with the true model parameters for noise-free data, similarly well-nigh compatible results for noisy data. As a result we can say that the method works successfully when applied to synthetic data. The technique is tested on three widely studied benchmark field data including gravity anomaly [Garber Fault (USA), Gazal Fault (Egypt), Mersa Matruh Fault (Egypt)]. In previous studies, various solution techniques have been used for the inversion of these field data and the compatibility of the model parameters obtained in this study with the values obtained from previous studies was compared. The results demonstrate that the CSA is a very effective and robust approach for the optimization of gravity anomalies.

关键词： cuckoo search algorithm Deep-seated faults Gravity inversion Parameter tuning

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Parameter estimation of activated sludge process based on an improved cuckoo search algorithm

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BIORESOURCE TECHNOLOGY 2018年 249卷 447-456页

作者： Du, Xianjun Wang, Junlu Jegatheesan, Veeriah Shi, Guohua Lanzhou Univ Technol Coll Elect & Informat Engn Lanzhou 730050 Gansu Peoples R China RMIT Univ Sch Engn Melbourne Vic 3000 Australia Lanzhou Univ Technol Key Lab Gansu Adv Control Ind Proc Lanzhou 730050 Gansu Peoples R China Lanzhou Univ Technol Natl Demonstrat Ctr Expt Elect & Control Engn Edu Lanzhou 730050 Gansu Peoples R China North China Elect Power Univ Dept Energy & Power Engn Baoding 071003 Hebei Peoples R China

It is essential to use appropriate values for kinetic parameters in activated sludge model when the model is applied for wastewater treatment processes under different environments. An improved cuckoo search (ICS) algorithm was proposed in this paper for the estimation of kinetic parameters used in Activated Sludge Model No. 1 (ASM1). ICS is tested for its speed and accuracy in reaching solution by searching global minima of six standard functions. Cyclical adjustment strategy was employed into the detected probability to increase searching ability. Meanwhile, the searching step was adaptively adjusted based on the optimal nest of the last generation and the current iteration numbers. Subsequently, ICS is used to estimate 7 sensitive parameters in ASM1 for practical applications. Field data are used to validate prediction accuracy of ASM1 with estimated parameters. Predicted results of the model are closer to the actual data with adjusted parameters.

关键词： Activated sludge process ASM1 cuckoo search algorithm Parameter estimation Wastewater treatment

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Comprehensive study of linear antenna array optimisation using the cuckoo search algorithm

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IET MICROWAVES ANTENNAS & PROPAGATION 2019年第9期13卷 1325-1333页

作者： Khodier, Majid Jordan Univ Sci & Technol Dept Elect Engn Irbid 22110 Jordan

This study presents a comprehensive study of the design and optimisation of linear antenna arrays using the cuckoo search (CS) algorithm. The method is used to control important radiation characteristics of the antenna arrays (such as side-lobe level, beamwidth, nulls) by optimising the parameters of the array elements (amplitude, phase, and position). Different design examples are presented that illustrate the robustness of the CS algorithm and its ability in achieving the design goals. The considered design examples clearly show that the CS algorithm is a simple and yet a powerful optimisation tool that can be used in antenna array design problems with great confidence.

关键词： antenna radiation patterns linear antenna arrays antenna arrays optimisation search problems linear antenna array optimisation cuckoo search algorithm comprehensive study linear antenna arrays important radiation characteristics side-lobe level array elements different design examples CS algorithm design goals considered design examples powerful optimisation tool antenna array design problems

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A New Approach to Optimal Location and Sizing of DSTATCOM in Radial Distribution Networks Using Bio-Inspired cuckoo search algorithm

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ENERGIES 2020年第18期13卷 4615页

作者： Rukmani, Devabalaji Kaliaperumal Thangaraj, Yuvaraj Subramaniam, Umashankar Ramachandran, Sitharthan Elavarasan, Rajvikram Madurai Das, Narottam Baringo, Luis Rasheed, Mohamed Imran Abdul Hindustan Inst Technol & Sci Dept Elect & Elect Engn 1 OMR Rd Chennai 600077 Tamil Nadu India Saveetha Inst Med & Tech Sci Saveetha Sch Engn Dept Elect & Elect Engn Chennai 600077 Tamil Nadu India Prince Sultan Univ Coll Engn Renewable Energy Lab Riyadh 11586 Saudi Arabia Vellore Inst Technol Sch Elect Engn Vellore 632014 Tamil Nadu India AA Industries Elect & Automot Parts Mfg Unit Chennai 600123 Tamil Nadu India Cent Queensland Univ Sch Engn & Technol Melbourne Vic 3000 Australia Cent Queensland Univ Ctr Intelligent Syst Sch Engn & Technol Brisbane Qld 4000 Australia Univ Castilla La Mancha Escuela Tecn Super Ingn Ind Campus Univ S-N Ciudad Real 13071 Spain Vellore Inst Technol Sch Elect Engn Chennai 600127 Tamil Nadu India

This article proposes a new approach based on a bio-inspired cuckoo search algorithm (CSA) that can significantly envisage with several issues for optimal allocation of distribution static compensator (DSTATCOM) in Radial Distribution System (RDS). In the proposed method, optimal locations of the DSTATCOM are calculated by using the Loss Sensitivity Factor (LSF). The optimal size of the DSTATCOM is simulated by using the newly developed CSA. In the proposed method, load flow calculations are performed by using a fast and efficient backward/forward sweep algorithm. Here, the mathematically formed objective function of the proposed method is to reduce the total system power losses. Standard 33-bus and 69-bus systems have been used to show the effectiveness of the proposed CSA-based optimization method in the RDS with different load models. The simulated results confirm that the optimal allocation of DSTATCOM plays a significant role in power loss minimization and enhanced voltage profile. The placement of DSTATCOM in RDS also plan an important role for minimizing uncertainties in the distribution level. The proposed method encourages one to use renewable-based resources, which results in affordable and clean energy.

关键词： cuckoo search algorithm DSTATCOM power loss minimization radial distribution system system power losses

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