检索结果-内蒙古大学图书馆

A Multistrategy Fusion-Improved black widow optimization algorithm for Structural Damage Identification

STRUCTURAL CONTROL & HEALTH MONITORING 2025年第1期2025卷

作者： Chen, Zhen Li, Wanying Liu, Xiaoshuai Wang, Yikai Chan, Tommy H. T. North China Univ Water Resources & Elect Power Sch Civil Engn & Commun Zhengzhou 450045 Peoples R China Queensland Univ Technol QUT Sch Civil & Environm Engn Brisbane 4000 Australia Changjiang River Sci Res Inst Key Lab Geotech Mech & Engn Minist Water Resources Wuhan 430010 Peoples R China

Structural damage identification based on metaheuristic algorithms is an important part of structural health monitoring with great potential. However, the metaheuristic intelligent algorithms probably have flaws of slow convergence speed and low calculation accuracy, which need to be improved to address engineering optimization problems. In this paper, the black widow optimization (BWO) algorithm is used for structural damage identification. In addition, a multistrategy fusion-improved BWO (IBWO) algorithm is proposed by introducing the tent chaotic mapping, the golden sine equation, the gazelle wandering equation, and the boundary treatments. First, in the population initialization stage, tent chaotic mapping is introduced to improve the quality of the initial solution. Second, the golden sine strategy is used to acquire the optimal solution quickly in local search. Then, the motion equation of the gazelle algorithm is employed to enhance the global search ability and avoid the algorithm falling into the local optimal solution. Finally, the boundary processing strategy is presented to reduce the calculation of solutions and improve the optimization efficiency. A novel damage identification objective function is redefined by combining the modal assurance criterion and the modal flexibility. Then, a two-story rigid frame structure is utilized for numerical simulations. Moreover, experimental studies with a simply supported beam were carried out to verify the performance of the proposed damage identification method. Simulation results and experimental studies demonstrate that, even with the interference of strong noise, the IBWO algorithm has a higher accuracy and efficiency in damage identification compared to the BWO algorithm.

关键词： black widow optimization algorithm experimental studies golden sine equation structural health monitoring tent chaotic mapping

来源：评论

学校读者我要写书评

暂无评论

Effective test-data generation using the modified black widow optimization algorithm

引用

SIGNAL IMAGE AND VIDEO PROCESSING 2024年第6-7期18卷 5333-5346页

作者： Arasteh, Bahman Ghaffari, Ali Khadir, Milad Torkamanian-Afshar, Mahsa Pirahesh, Sajad Istinye Univ Fac Engn & Nat Sci Dept Software Engn Istanbul Turkiye Islamic Azad Univ Dept Comp Engn Tabriz Branch Tabriz Iran Istanbul Topkapi Univ Fac Engn Comp Engn Dept TR-34087 Istanbul Turkiye Khazar Univ Dept Comp Sci Baku Azerbaijan

Software testing is one of the software development activities and is used to identify and remove software bugs. Most small-sized projects may be manually tested to find and fix any bugs. In large and real-world software products, manual testing is thought to be a time and money-consuming process. Finding a minimal subset of input data in the shortest amount of time (as test data) to obtain the maximal branch coverage is an NP-complete problem in the field. Different heuristic-based methods have been used to generate test data. In this paper, for addressing and solving the test data generation problem, the black widow optimization algorithm has been used. The branch coverage criterion was used as the fitness function to optimize the generated data. The obtained experimental results on the standard benchmarks show that the proposed method generates more effective test data than the simulated annealing, genetic algorithm, ant colony optimization, particle swarm optimization, and artificial bee colony algorithms. According to the results, with 99.98% average coverage, 99.96% success rate, and 9.36 required iteration, the method was able to outperform the other methods.

关键词： Software-test generation black widow optimization algorithm Branch coverage Success rate Stability

来源：评论

学校读者我要写书评

暂无评论

An improved black widow optimization algorithm for surfaces conversion

引用

APPLIED INTELLIGENCE 2023年第6期53卷 6629-6670页

作者： Hu, Gang Du, Bo Wang, Xiaofeng Xian Univ Technol Dept Appl Math Xian 710054 Peoples R China Xian Univ Technol Sch Comp Sci & Engn Xian 710048 Peoples R China

Bezier surfaces and Q-Bezier surfaces are effective modeling tools for shape design in computer-aided geometric design, computer vision, and computer graphics. The mutual conversion between these two kinds of surfaces is a pivotal and knotty technique in CAD/CAM. In this paper, the conversion between Q-Bezier surfaces and rectangular Bezier surfaces is investigated. However, due to the uncertain parameters of the Q-Bezier surfaces, the approximation conversion from rectangular Bezier surfaces to Q-Bezier surfaces can be regarded as an optimization problem, which is effectively dealt with by swarm intelligence algorithm. In this regard, an enhanced black widow optimization called LDBWO is proposed to find more suitable shape parameters to obtain optimal approximation Q-Bezier surfaces, which are closer to the given Bezier surfaces. The LDBWO algorithm overcomes the shortcomings of standard BWO algorithm such as low accuracy, slow convergence, and is easy to fall into local optimum by introducing golden sine learning strategy and diffusion process. Furthermore, to confirm and validate the performance of the LDBWO, eight well-known intelligent algorithms are compared with the LDBWO on various benchmark functions and engineering examples. Finally, by minimizing the conversion error defined by the L-2-norm, the optimization model of the approximation conversion from rectangular Bezier surfaces to Q-Bezier surfaces is established. Several representative numerical examples are provided to illustrate the accuracy and efficiency of the proposed methods.

关键词： black widow optimization algorithm Q-Bezier surfaces Rectangular Bezier surfaces Shape parameters Surface conversion

来源：评论

学校读者我要写书评

暂无评论

An Improved black widow optimization algorithm for Engineering Constrained optimization Problems

引用

IEEE ACCESS 2023年 11卷 32476-32495页

作者： Xu, Dongxing Yin, Jianchuan Guangdong Ocean Univ Naval Architecture & Shipping Coll Zhanjiang 524088 Peoples R China Guangdong Prov Engn Res Ctr Ship Intelligence & S Zhanjiang 524088 Peoples R China

In solving engineering constrained optimization problems, the conventional black widow optimization algorithm (BWOA) has some shortcomings such as insufficient robustness and slow convergence speed. Therefore, an improved black widow optimization algorithm (IBWOA) is proposed by combining methods of double chaotic map, Cauchy center of gravity inverse difference mutation and golden sine guidance strategy. Firstly, the quality of the initial population of the BWOA is improved based on the double chaotic map;Secondly, in order to make full use of the difference information between the current and the optimal position thus improve optimization accuracy, the golden sine algorithm (Gold-SA) is introduced to update the position of the black widow individuals;Finally, the Cauchy barycenter reverse differential mutation operator is employed to increase the diversity of the population, avoid local optimization thus improve the global search ability of the algorithm. In addition, the global convergence characteristics of the IBWOA are analyzed based on the Markov process and the convergence probability reaches 1 for the globally optimal solution. The performance of the proposed IBWOA was evaluated based on eight continuous / discrete hybrid engineering optimization problems and typical benchmark functions. The results show that the improved BWOA can improve the search accuracy, convergence speed and robustness effectively comparing with some other conventional optimization algorithms.

关键词： optimization Metaheuristics Convergence Heuristic algorithms Search problems Statistics Markov processes black widow optimization algorithm double chaotic map golden sine algorithm (Gold-SA) Cauchy barycentric reverse difference mutation operator Markov chain engineering optimization

来源：评论

学校读者我要写书评

暂无评论

optimization of synchronized frequency and voltage control for a distributed generation system using the black widow optimization algorithm

引用

Clean Energy 2022年第1期6卷 105-118页

作者： Baran Sadeghi Nima Shafaghatian Reza Alayi Mamdouh El Haj Assad Farhad Zishan Hasan Hosseinzadeh Electrical Engineering Department Ghazvin BranchIslamic Azad UniversityGhazvinIran Electrical Engineering Department Zanjan UniversityZanjanIran Department of Mechanics Germi BranchIslamic Azad UniversityGermiIran Sustainable and Renewable Energy Engineering Department University of SharjahP O Box 27272SharjahUAE Department of Electrical Engineering Sahand University of TechnologyTabrizIran Department of Mathematics Ardabil BranchIslamic Azad UniversityArdabilIran

A distributed generation network could be a hybrid power system that includes wind-diesel power generation based on induction generators(IGs)and synchronous generators(SGs).The main advantage of these systems is the possibility of using renewable energy in their *** most important challenge is to design the voltage-control loop with the frequency-control loop to obtain optimal responses for voltage and frequency *** this work,the voltage-control loop is designed by an automatic voltage regulator.A linear model of the hybrid system has also been developed with coordinated voltage and frequency *** frequency response and voltage deviations are compared for different load disturbances and different reactive *** gains of the SG and the static volt-ampere reactive compensator(SVC)controllers in the IG terminal are calculated using the black widow optimization(BWO)algorithm to insure low frequency and voltage *** BWO optimization algorithm is one of the newest and most powerful optimization methods to have been introduced so *** results showed that the BWO algorithm has a good speed in solving the proposed objective function.A 22%improvement in time adjustment was observed in the use of an optimal ***,an 18%improvement was observed in the transitory values.

关键词： microgrid voltage and frequency control black widow optimization algorithm dynamic response smart grid

来源：评论

学校读者我要写书评

暂无评论

Multilevel thresholding of images with improved Otsu thresholding by black widow optimization algorithm

引用

MULTIMEDIA TOOLS AND APPLICATIONS 2021年第18期80卷 28217-28243页

作者： Al-Rahlawee, Anfal Thaer Hussein Rahebi, Javad Altinbas Univ Dept Elect & Comp Engn Istanbul Turkey

One of the most important methods of image processing is image thresholding, which is based on image histogram analysis. These methods analyze the image histogram diagram and try to present optimal values for the image thresholds so that the image regions can be distinguished by these thresholds. Thresholding is a popular method in image processing and is used in most research related to image segmentation due to its accuracy and efficiency. Multi-level thresholding, such as the Otsu method, is one of the most common methods of thresholding image processing. These methods have high computational complexity despite their accuracy and efficiency. When the number of thresholds used increases, these methods lose their efficiency due to increased complexity and execution time. One of the ways to find thresholds in the Otsu threshold method is to use metaheuristic algorithms such as the black widow Spider optimization algorithm. These algorithms can find the appropriate thresholds for the image at the logical time. In the proposed method, each threshold is a component or one dimension of a solution of the black widow Spider optimization algorithm, and an attempt is made to calculate the optimal threshold value without high complexity by this algorithm. Experiments on several standard images show that the proposed algorithm finds better thresholds than the particle swarm optimization algorithm, the firefly algorithm, the genetic algorithm, and the gray wolf optimization algorithm. The analysis shows that the proposed method in the PSNR index has a better value in 83.33% of the experiments than other algorithms and also in 80% of the experiments the proposed method has a better SSIM index than these methods. Analysis of the proposed algorithm on several pertussis images also shows that the proposed method has a good ability to threshold medical images such as brain tumors and optic disc detection in human retinal images.

关键词： Thresholding Otsu Swarm intelligence algorithms black widow optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Suspended sediment load prediction based on soft computing models and black widow optimization algorithm using an enhanced gamma test

引用

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2021年第35期28卷 48253-48273页

作者： Panahi, Fatemeh Ehteram, Mohammad Emami, Mohammad Univ Kashan Fac Nat Resources & Earth Sci Kashan Iran Semnan Univ Dept Water Engn & Hydraul Struct Fac Civil Engn Semnan Iran

The suspended sediment load (SSL) prediction is one of the most important issues in water engineering. In this article, the adaptive neuro-fuzzy interface system (ANFIS) and support vector machine (SVM) were used to estimate the SLL of two main tributaries of the Telar River placed in the north of Iran. The main Telar River had two main tributaries, namely, the Telar and the Kasilian. A new evolutionary algorithm, namely, the black widow optimization algorithm (BWOA), was used to enhance the precision of the ANFIS and SVM models for predicting daily SSL. The lagged rainfall, temperature, discharge, and SSL were used as the inputs to the models. The present study used a new hybrid Gamma test to determine the best input scenario. In the next step, the best input combination was determined based on the gamma value. In this research, the abilities of the ANFIS-BWOA and SVM-BWOA were benchmarked with the ANFIS-bat algorithm (BA), SVM-BA, SVM-particle swarm optimization (PSO), and ANFIS-PSO. The mean absolute error (MAE) of ANFIS-BWOA was 0.40%, 2.2%, and 2.5% lower than those of ANFIS-BA, ANFIS-PSO, and ANFIS models in the training level for Telar River. It was concluded that the ANFIS-BWOA had the highest value of R-2 among other models in the Telar River. The MAE of the ANFIS-BWOA, SVM-BWOA, SVM-PSO, SVM-BA, and SVM models were 899.12 (Ton/day), 934.23 (Ton/day), 987.12 (Ton/day), 976.12, and 989.12 (Ton/day), respectively, in the testing level for the Kasilian River. An uncertainty analysis was used to investigate the effect of uncertainty of the inputs (first scenario) and the model parameters (the second scenario) on the accuracy of models. It was observed that the input uncertainty higher than the parameter uncertainty.

关键词： Suspended sediment load black widow optimization algorithm ANFIS SVM

来源：评论

学校读者我要写书评

暂无评论

The optimization of a Pipeline Temperature Monitoring Method Based on Non-Local Means with the black widow optimization algorithm

引用

ENERGIES 2023年第20期16卷 7178页

作者： Lou, Fangwei Wang, Benji Sima, Rui Chen, Zuan He, Wei Zhu, Baikang Hong, Bingyuan Zhejiang Ocean Univ Natl & Local Joint Engn Res Ctr Harbor Oil & Gas S Zhejiang Key Lab Petrochem Environm Pollut Control Zhoushan 316022 Peoples R China Zhejiang Ocean Univ Sch Shipping & Maritime Zhoushan 316022 Peoples R China PipeChina Zhejiang Pipeline Network Co Ltd Hangzhou 310000 Peoples R China

The accuracy of pipeline temperature monitoring using the Brillouin Optical Time Domain Analysis system depends on the Brillouin Gain Spectrum in the Brillouin Optical Time Domain Analysis system. The Non-Local Means noise reduction algorithm, due to its ability to use the data patterns available within the two-dimensional measurement data space, has been used to improve the Brillouin Gain Spectrum in the Brillouin Optical Time Domain Analysis system. This paper studies a new Non-Local Means algorithm optimized through the black widow optimization algorithm, in view of the unreasonable selection of smoothing parameters in other Non-Local Means algorithms. The field test demonstrates that, the new algorithm, when compared to other Non-Local Means methods, excels in preserving the detailed information within the Brillouin Gain Spectrum. It successfully restores the fundamental shape and essential characteristics of the Brillouin Gain Spectrum. Notably, at the 25 km fiber end, it achieves a 3 dB higher Signal-to-Noise Ratio compared to other Non-Local Means noise reduction algorithms. Furthermore, the Brillouin Gain Spectrum values exhibit increases of 9.4% in Root Mean Square Error, 12.5% in Sum of Squares Error, and 10% in Full Width at Half Maximum. The improved method has a better denoising effect and broad application prospects in pipeline safety.

关键词： Brillouin Gain Spectrum Non-Local Means black widow optimization algorithm pipe temperature monitoring

来源：评论

学校读者我要写书评

暂无评论

An enhanced black widow optimization algorithm for feature selection

引用

KNOWLEDGE-BASED SYSTEMS 2022年 235卷 1页

作者： Hu, Gang Du, Bo Wang, Xiaofeng Wei, Guo Xian Univ Technol Dept Appl Math Xian 710054 Peoples R China Xian Univ Technol Sch Comp Sci & Engn Xian 710048 Peoples R China Univ N Carolina Dept Math & Comp Sci Pembroke NC 28372 USA

Feature selection is an important data processing method to reduce dimension of the raw datasets while preserving the information as much as possible. In this paper, an enhanced version of black widow optimization algorithm called SDABWO is proposed to solve the feature selection problem. The black widow optimization algorithm (BWO) is a new population-based meta-heuristic algorithm inspired by the evolution process of spider population. Three main improvements were included into the BWO to overcome the shortcoming of low accuracy, slow convergence speed and being easy to fall into local optima. Firstly, a novel strategy for selecting spouses by calculating the weight of female spiders and the distance between spiders is proposed. By applying the strategy to the original algorithm, it has faster convergence speed and higher accuracy. The second improvement includes the use of mutation operator of differential evolution at mutation phase of BWO which helps the algorithm escape from the local optima. And then, three key parameters are set to adjust adaptively with the increase of iteration times. To confirm and validate the performance of the improved BWO, other 10 algorithms are used to compared with the SDABWO on 25 benchmark functions. The results show that the proposed algorithm enhances the exploitation ability, improves the convergence speed and is more stable when solving optimization problems. Furthermore, the proposed SDABWO algorithm is employed for feature selection. Twelve standard datasets from UCI repository prove that SDABWO-based method has stronger search ability in the search space of feature selection than the other five popular feature selection methods. These results confirm the capability of the proposed method simultaneously improve the classification accuracy while reducing the dimensions of the original datasets. Therefore, SDABWO-based method was found to be one of the most promising for feature selection problem over other approaches that ar

关键词： black widow optimization algorithm Feature selection K-nearest neighbor Spouses selecting strategy Mutation operator Adaptive parameters

来源：评论

学校读者我要写书评

暂无评论

Field Current Waveform-Based Method for Estimation of Synchronous Generator Parameters Using Adaptive black widow optimization algorithm

引用

IEEE ACCESS 2020年 8卷 207537-207550页

作者： Micev, Mihailo Calasan, Martin Petrovic, Dragan S. Ali, Ziad M. Quynh, Nguyen Vu Abdel Aleem, Shady H. E. Univ Montenegro Fac Elect Engn Podgorica 81000 Montenegro Univ Belgrade Sch Elect Engn Belgrade 11000 Serbia Prince Sattam Bin Abdulaziz Univ Dept Elect Engn Coll Engn Wadi Addawaser Wadi Addawasir 11991 Saudi Arabia Aswan Univ Aswan Fac Engn Dept Elect Engn Aswan 81542 Egypt Lac Hong Univ Elect & Elect Dept Bien Hoa 810000 Vietnam 15th May Higher Inst Engn Math Phys & Engn Sci Cairo 11721 Egypt

This article presents a novel method for identification of synchronous generator parameters that is based on sudden short-circuit test data and a novel metaheuristic algorithm, called the adaptive black widow optimization algorithm. Unlike traditional methods defined by IEEE and International Electrotechnical Commission (IEC) standards, which rely on the armature current oscillogram, the method proposed in this article uses the field current waveform during the short-circuit test. Moreover, the standard graphical method for extraction of the generator parameters is replaced by an effective metaheuristic algorithm. The proposed algorithm tends to minimize the normalized sum of squared errors (NSSE) between simulation and experimental results. The applicability and accuracy of the proposed optimization technique are verified using experimentally obtained results from a 100-MVA synchronous generator at the Bajina Basta hydropower plant.

关键词： Synchronous generators Windings Generators Shock absorbers optimization Current measurement Estimation black widow optimization algorithm field current waveform parameter estimation synchronous generator

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：