期刊文献+
共找到148篇文章
< 1 2 8 >
每页显示 20 50 100
Hybrid Optimization Algorithm for Handwritten Document Enhancement
1
作者 Shu-Chuan Chu Xiaomeng Yang +2 位作者 Li Zhang Václav Snášel Jeng-Shyang Pan 《Computers, Materials & Continua》 SCIE EI 2024年第3期3763-3786,共24页
The Gannet Optimization Algorithm (GOA) and the Whale Optimization Algorithm (WOA) demonstrate strong performance;however, there remains room for improvement in convergence and practical applications. This study intro... The Gannet Optimization Algorithm (GOA) and the Whale Optimization Algorithm (WOA) demonstrate strong performance;however, there remains room for improvement in convergence and practical applications. This study introduces a hybrid optimization algorithm, named the adaptive inertia weight whale optimization algorithm and gannet optimization algorithm (AIWGOA), which addresses challenges in enhancing handwritten documents. The hybrid strategy integrates the strengths of both algorithms, significantly enhancing their capabilities, whereas the adaptive parameter strategy mitigates the need for manual parameter setting. By amalgamating the hybrid strategy and parameter-adaptive approach, the Gannet Optimization Algorithm was refined to yield the AIWGOA. Through a performance analysis of the CEC2013 benchmark, the AIWGOA demonstrates notable advantages across various metrics. Subsequently, an evaluation index was employed to assess the enhanced handwritten documents and images, affirming the superior practical application of the AIWGOA compared with other algorithms. 展开更多
关键词 Metaheuristic algorithm gannet optimization algorithm hybrid algorithm handwritten document enhancement
下载PDF
Optimization of LSTM Ship Trajectory Prediction Based on Hybrid Genetic Algorithm
2
作者 ZHAO Pengfei 《Journal of Geodesy and Geoinformation Science》 CSCD 2024年第3期89-102,共14页
Accurate prediction of the movement trajectory of sea surface targets holds significant importance in achieving an advantageous position in the sea battle field.This prediction plays a crucial role in ensuring securit... Accurate prediction of the movement trajectory of sea surface targets holds significant importance in achieving an advantageous position in the sea battle field.This prediction plays a crucial role in ensuring security defense and confrontation,and is essential for effective deployment of military strategy.Accurately predicting the trajectory of sea surface targets using AIS(Automatic Identification System)information is crucial for security defense and confrontation,and holds significant importance for military strategy deployment.In response to the problem of insufficient accuracy in ship trajectory prediction,this study proposes a hybrid genetic algorithm to optimize the Long Short-Term Memory(LSTM)algorithm.The HGA-LSTM algorithm is proposed for ship trajectory prediction.It can converge faster and obtain better parameter solutions,thereby improving the effectiveness of ship trajectory prediction.Compared to traditional LSTM and GA-LSTM algorithms,experimental results demonstrate that this algorithm outperforms them in both single-step and multi-step prediction. 展开更多
关键词 trajectory prediction LSTM hybrid genetic algorithm
下载PDF
Simulation of Flux Distribution in Central Metabolism of Saccharo-myces cerevisiae by Hybridized Genetic Algorithm
3
作者 张慧敏 姚善泾 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2007年第2期150-156,共7页
A scheme of investigating the intracellular metabolic fluxes in central metabolism of Saccharomyces cerevisiae based on isotope model and tracer experiment was developed. The metabolic model applied in this study incl... A scheme of investigating the intracellular metabolic fluxes in central metabolism of Saccharomyces cerevisiae based on isotope model and tracer experiment was developed. The metabolic model applied in this study includes the Embden-Meyerhof-Parnas pathway,the pentose phosphate pathway,the tricarboxylic acid cycle,CO2 anaplerotic reactions,ethanol and acetate formation,and pathways involved in amino acid synthesis. The approach of hybridized genetic algorithm combined with the sequential simplex technique was used to optimize a quadratic error function without the requirement of the information on the partial derivatives. The impact of some key pa-rameters on the algorithm was studied. This approach was proved to be rapid and numerically stable in the analysis of the central metabolism of S.cerevisiae. 展开更多
关键词 Saccharomyces cerevisiae metabolic flux hybridized genetic algorithm 2D NMR central metabolism
下载PDF
Optimization of Multi-Execution Modes and Multi-Resource-Constrained Offshore Equipment Project Scheduling Based on a Hybrid Genetic Algorithm
4
作者 Qi Zhou Jinghua Li +2 位作者 Ruipu Dong Qinghua Zhou Boxin Yang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第2期1263-1281,共19页
Offshore engineering construction projects are large and complex,having the characteristics of multiple execution modes andmultiple resource constraints.Their complex internal scheduling processes can be regarded as r... Offshore engineering construction projects are large and complex,having the characteristics of multiple execution modes andmultiple resource constraints.Their complex internal scheduling processes can be regarded as resourceconstrained project scheduling problems(RCPSPs).To solve RCPSP problems in offshore engineering construction more rapidly,a hybrid genetic algorithmwas established.To solve the defects of genetic algorithms,which easily fall into the local optimal solution,a local search operation was added to a genetic algorithm to defend the offspring after crossover/mutation.Then,an elitist strategy and adaptive operators were adopted to protect the generated optimal solutions,reduce the computation time and avoid premature convergence.A calibrated function method was used to cater to the roulette rules,and appropriate rules for encoding,decoding and crossover/mutation were designed.Finally,a simple network was designed and validated using the case study of a real offshore project.The performance of the genetic algorithmand a simulated annealing algorithmwas compared to validate the feasibility and effectiveness of the approach. 展开更多
关键词 Offshore project multi-execution modes resource-constrained project scheduling hybrid genetic algorithm
下载PDF
Enhanced Detection of Cerebral Atherosclerosis Using Hybrid Algorithm of Image Segmentation
5
作者 Shakunthala Masi Helenprabha Kuttiappan 《Intelligent Automation & Soft Computing》 SCIE 2023年第4期733-744,共12页
In medical science for envisaging human body’s phenomenal structure a major part has been driven by image processing techniques.Major objective of this work is to detect of cerebral atherosclerosis for image segmenta... In medical science for envisaging human body’s phenomenal structure a major part has been driven by image processing techniques.Major objective of this work is to detect of cerebral atherosclerosis for image segmentation applica-tion.Detection of some abnormal structures in human body has become a difficult task to complete with some simple images.For expounding and distinguishing neural architecture of human brain in an effective manner,MRI(Magnetic Reso-nance Imaging)is one of the most suitable and significant technique.Here we work on detection of Cerebral Atherosclerosis from MRI images of patients.Cer-ebral Atherosclerosis is a cerebral vascular disease causes narrowing of the arteries due to buildup of fatty plaque inside the blood vessels of the brain.It leads to Ischemic stroke if not diagnosed early.Stroke affects majorly old age people and percentage of affected women is more compared to men.Results:Preproces-sing is done by using alpha trimmed meanfilter which is used to remove noise and also it enhances the image.Segmentation of cerebral atherosclerosis is done by using K-means clustering,Contextual clustering,and proposed Hybrid algo-rithm.Various parameters like Correlation,Pixel density,energy is determined and from the analysis of parameters it is determined that proposed Hybrid algo-rithm is efficient. 展开更多
关键词 ATHEROSCLEROSIS Ischemic stroke Alpha trimmed meanfilter K-MEANS Contextual clustering Hybrid algorithm
下载PDF
Hyperparameter Optimization for Capsule Network Based Modified Hybrid Rice Optimization Algorithm
6
作者 Zhiwei Ye Ziqian Fang +4 位作者 Zhina Song Haigang Sui Chunyan Yan Wen Zhou Mingwei Wang 《Intelligent Automation & Soft Computing》 SCIE 2023年第8期2019-2035,共17页
Hyperparameters play a vital impact in the performance of most machine learning algorithms.It is a challenge for traditional methods to con-figure hyperparameters of the capsule network to obtain high-performance manu... Hyperparameters play a vital impact in the performance of most machine learning algorithms.It is a challenge for traditional methods to con-figure hyperparameters of the capsule network to obtain high-performance manually.Some swarm intelligence or evolutionary computation algorithms have been effectively employed to seek optimal hyperparameters as a com-binatorial optimization problem.However,these algorithms are prone to get trapped in the local optimal solution as random search strategies are adopted.The inspiration for the hybrid rice optimization(HRO)algorithm is from the breeding technology of three-line hybrid rice in China,which has the advantages of easy implementation,less parameters and fast convergence.In the paper,genetic search is combined with the hybrid rice optimization algorithm(GHRO)and employed to obtain the optimal hyperparameter of the capsule network automatically,that is,a probability search technique and a hybridization strategy belong with the primary HRO.Thirteen benchmark functions are used to evaluate the performance of GHRO.Furthermore,the MNIST,Chest X-Ray(pneumonia),and Chest X-Ray(COVID-19&pneumonia)datasets are also utilized to evaluate the capsule network learnt by GHRO.The experimental results show that GHRO is an effective method for optimizing the hyperparameters of the capsule network,which is able to boost the performance of the capsule network on image classification. 展开更多
关键词 Hyperparameter optimization hybrid rice optimization algorithm genetic algorithm capsule network image classification
下载PDF
Detecting and Preventing of Attacks in Cloud Computing Using Hybrid Algorithm
7
作者 R.S.Aashmi T.Jaya 《Intelligent Automation & Soft Computing》 SCIE 2023年第1期79-95,共17页
Cloud computing is the technology that is currently used to provide users with infrastructure,platform,and software services effectively.Under this system,Platform as a Service(PaaS)offers a medium headed for a web de... Cloud computing is the technology that is currently used to provide users with infrastructure,platform,and software services effectively.Under this system,Platform as a Service(PaaS)offers a medium headed for a web development platform that uniformly distributes the requests and resources.Hackers using Denial of service(DoS)and Distributed Denial of Service(DDoS)attacks abruptly interrupt these requests.Even though several existing methods like signature-based,statistical anomaly-based,and stateful protocol analysis are available,they are not sufficient enough to get rid of Denial of service(DoS)and Distributed Denial of Service(DDoS)attacks and hence there is a great need for a definite algorithm.Concerning this issue,we propose an improved hybrid algorithm which is a combination of Multivariate correlation analysis,Spearman coefficient,and mitigation technique.It can easily differentiate common traffic and attack traffic.Not only that,it greatly helps the network to distribute the resources only for authenticated requests.The effects of comparing with the normalized information have shown an extra encouraging detection accuracy of 99%for the numerous DoS attack as well as DDoS attacks. 展开更多
关键词 Hybrid algorithm(HA) distributed denial of service(DDoS) denial of service(DoS) platform as a service(PaaS) infrastructure as a service(IaaS) software as a service(SaaS)
下载PDF
Contact Stress Reliability Analysis Model for Cylindrical Gear with Circular Arc Tooth Trace Based on an Improved Metamodel
8
作者 Qi Zhang Zhixin Chen +5 位作者 Yang Wu Guoqi Xiang Guang Wen Xuegang Zhang Yongchun Xie Guangchun Yang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第7期593-619,共27页
Although there is currently no unified standard theoretical formula for calculating the contact stress of cylindrical gears with a circular arc tooth trace(referred to as CATT gear),a mathematical model for determinin... Although there is currently no unified standard theoretical formula for calculating the contact stress of cylindrical gears with a circular arc tooth trace(referred to as CATT gear),a mathematical model for determining the contact stress of CATT gear is essential for studying how parameters affect its contact stress and building the contact stress limit state equation for contact stress reliability analysis.In this study,a mathematical relationship between design parameters and contact stress is formulated using the KrigingMetamodel.To enhance the model’s accuracy,we propose a new hybrid algorithm that merges the genetic algorithm with the Quantum Particle Swarm optimization algorithm,leveraging the strengths of each.Additionally,the“parental inheritance+self-learning”optimization model is used to fine-tune the KrigingMetamodel’s parameters.Following this,amathematicalmodel for calculating the contact stress of Variable Hyperbolic Circular-Arc-Tooth-Trace(VH-CATT)gears using the optimized Kriging model was developed.We then examined how different gear parameters affect the VH-CATT gears’contact stress.Our simulation results show:(1)Improvements in R2,RMSE,and RMAE.R2 rose from0.9852 to 0.9974(a 1.22%increase),nearing 1,suggesting the optimized Kriging Metamodel’s global error is minimized.Meanwhile,RMSE dropped from3.9210 to 1.6492,a decline of 57.94%.The global error of the GA-IQPSO-Kriging algorithm was also reduced,with RMAE decreasing by 58.69%from 0.1823 to 0.0753,showing the algorithm’s enhanced precision.In a comparison of ten experimental groups selected randomly,the GA-IQPSO-Kriging and FEM-based contact analysis methods were used to measure contact stress.Results revealed a maximum error of 12.11667 MPA,which represents 2.85%of the real value.(2)Several factors,including the pressure angle,tooth width,modulus,and tooth line radius,are inversely related to contact stress.The descending order of their impact on the contact stress is:tooth line radius>modulus>pressure angle>tooth width.(3)Complex interactions are noted among various parameters.Specifically,when the tooth line radius interacts with parameters such as pressure angle,tooth width,and modulus,the resulting stress contour is nonlinear,showcasing amultifaceted contour plane.However,when tooth width,modulus,and pressure angle interact,the stress contour is nearly linear,and the contour plane is simpler,indicating a weaker coupling among these factors. 展开更多
关键词 CATT gear contact stress finite element method METAMODEL hybrid algorithm influencing factors
下载PDF
HYBRID MULTI-OBJECTIVE GRADIENT ALGORITHM FOR INVERSE PLANNING OF IMRT
9
作者 李国丽 盛大宁 +3 位作者 王俊椋 景佳 王超 闫冰 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2010年第1期97-101,共5页
The intelligent optimization of a multi-objective evolutionary algorithm is combined with a gradient algorithm. The hybrid multi-objective gradient algorithm is framed by the real number. Test functions are used to an... The intelligent optimization of a multi-objective evolutionary algorithm is combined with a gradient algorithm. The hybrid multi-objective gradient algorithm is framed by the real number. Test functions are used to analyze the efficiency of the algorithm. In the simulation case of the water phantom, the algorithm is applied to an inverse planning process of intensity modulated radiation treatment (IMRT). The objective functions of planning target volume (PTV) and normal tissue (NT) are based on the average dose distribution. The obtained intensity profile shows that the hybrid multi-objective gradient algorithm saves the computational time and has good accuracy, thus meeting the requirements of practical applications. 展开更多
关键词 gradient methods inverse planning multi-objective optimization hybrid gradient algorithm
下载PDF
Bi-level programming model and algorithm for optimizing headway of public transit line
10
作者 张健 李文权 《Journal of Southeast University(English Edition)》 EI CAS 2010年第3期471-474,共4页
Due to the fact that headway is a key factor to be considered in bus scheduling, this paper proposes a bi-level programming model for optimizing bus headway in public transit lines. In this model, with the interests o... Due to the fact that headway is a key factor to be considered in bus scheduling, this paper proposes a bi-level programming model for optimizing bus headway in public transit lines. In this model, with the interests of bus companies and passengers in mind, the upper-level model's objective is to minimize the total cost, which is affected by frequency settings, both in time and economy in the transit system. The lower-level model is a transit assignment model used to describe the assignment of passengers' trips to the network based on the optimal bus headway. In order to solve the proposed model, a hybrid genetic algorithm, namely the genetic algorithm and the simulated annealing algorithm (GA-SA), is designed. Finally, the model and the algorithm are tested against the transit data, by taking some of the bus lines of Changzhou city as an example. Results indicate that the proposed model allows supply and demand to be linked, which is reasonable, and the solving algorithm is effective. 展开更多
关键词 HEADWAY bi-level model transit assignment hybrid genetic algorithm
下载PDF
Study on Multi-stream Heat Exchanger Network Synthesis with Parallel Genetic/Simulated Annealing Algorithm 被引量:13
11
作者 魏关锋 姚平经 +1 位作者 LUOXing ROETZELWilfried 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2004年第1期66-77,共12页
The multi-stream heat exchanger network synthesis (HENS) problem can be formulated as a mixed integer nonlinear programming model according to Yee et al. Its nonconvexity nature leads to existence of more than one opt... The multi-stream heat exchanger network synthesis (HENS) problem can be formulated as a mixed integer nonlinear programming model according to Yee et al. Its nonconvexity nature leads to existence of more than one optimum and computational difficulty for traditional algorithms to find the global optimum. Compared with deterministic algorithms, evolutionary computation provides a promising approach to tackle this problem. In this paper, a mathematical model of multi-stream heat exchangers network synthesis problem is setup. Different from the assumption of isothermal mixing of stream splits and thus linearity constraints of Yee et al., non-isothermal mixing is supported. As a consequence, nonlinear constraints are resulted and nonconvexity of the objective function is added. To solve the mathematical model, an algorithm named GA/SA (parallel genetic/simulated annealing algorithm) is detailed for application to the multi-stream heat exchanger network synthesis problem. The performance of the proposed approach is demonstrated with three examples and the obtained solutions indicate the presented approach is effective for multi-stream HENS. 展开更多
关键词 multi-stream heat exchanger network synthesis non-isothermal mixing mixed integer nonlinear programming model genetic algorithm simulated annealing algorithm hybrid algorithm
下载PDF
Identification of vibration loads on hydro generator by using hybrid genetic algorithm 被引量:6
12
作者 Shouju Li Yingxi Liu 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2006年第6期603-610,共8页
Vibration dynamic characteristics have been a major issue in the modeling and mechanical analysis of large hydro generators. An algorithm is developed for identifying vibration dynamic characteristics by means of hybr... Vibration dynamic characteristics have been a major issue in the modeling and mechanical analysis of large hydro generators. An algorithm is developed for identifying vibration dynamic characteristics by means of hybrid genetic algorithm. From the measured dynamic responses of a hydro generator, an appropriate estimation algorithm is needed to identify the loading parameters, including the main frequencies and amplitudes of vibrating forces. In order to identify parameters in an efficient and robust manner, an optimization method is proposed that combines genetic algorithm with simulated annealing and elitist strategy. The hybrid genetic algorithm is then used to tackle an ill-posed problem of parameter identification, in which the effectiveness of the proposed optimization method is confirmed by its comparison with actual observation data. 展开更多
关键词 Hybrid genetic algorithm Parameteridentification Vibration responses Fieldmeasurement Simulated annealing
下载PDF
A New Hybrid Algorithm and Its Numerical Realization for a Quasi-nonexpansive Mapping 被引量:7
13
作者 GAO XING-HUI MA LE-RONG Ji You-qing 《Communications in Mathematical Research》 CSCD 2017年第4期340-346,共7页
The purpose of this article is to propose a new hybrid projection method for a quasi-nonexpansive mapping. The strong convergence of the algorithm is proved in real Hilbert spaces. A numerical experiment is also inclu... The purpose of this article is to propose a new hybrid projection method for a quasi-nonexpansive mapping. The strong convergence of the algorithm is proved in real Hilbert spaces. A numerical experiment is also included to explain the effectiveness of the proposed methods. The results of this paper are interesting extensions of those known results. 展开更多
关键词 quasi-nonexpansive mapping hybrid algorithm strong convergence Hilbert space
下载PDF
Energy-absorption forecast of thin-walled structure by GA-BP hybrid algorithm 被引量:7
14
作者 谢素超 周辉 +1 位作者 赵俊杰 章易程 《Journal of Central South University》 SCIE EI CAS 2013年第4期1122-1128,共7页
In order to analyze the influence rule of experimental parameters on the energy-absorption characteristics and effectively forecast energy-absorption characteristic of thin-walled structure, the forecast model of GA-B... In order to analyze the influence rule of experimental parameters on the energy-absorption characteristics and effectively forecast energy-absorption characteristic of thin-walled structure, the forecast model of GA-BP hybrid algorithm was presented by uniting respective applicability of back-propagation artificial neural network (BP-ANN) and genetic algorithm (GA). The detailed process was as follows. Firstly, the GA trained the best weights and thresholds as the initial values of BP-ANN to initialize the neural network. Then, the BP-ANN after initialization was trained until the errors converged to the required precision. Finally, the network model, which met the requirements after being examined by the test samples, was applied to energy-absorption forecast of thin-walled cylindrical structure impacting. After example analysis, the GA-BP network model was trained until getting the desired network error only by 46 steps, while the single BP-ANN model achieved the same network error by 992 steps, which obviously shows that the GA-BP hybrid algorithm has faster convergence rate. The average relative forecast error (ARE) of the SEA predictive results obtained by GA-BP hybrid algorithm is 1.543%, while the ARE of the SEA predictive results obtained by BP-ANN is 2.950%, which clearly indicates that the forecast precision of the GA-BP hybrid algorithm is higher than that of the BP-ANN. 展开更多
关键词 thin-walled structure GA-BP hybrid algorithm IMPACT energy-absorption characteristic FORECAST
下载PDF
Image Segmentation of Brain MR Images Using Otsu’s Based Hybrid WCMFO Algorithm 被引量:6
15
作者 A.Renugambal K.Selva Bhuvaneswari 《Computers, Materials & Continua》 SCIE EI 2020年第8期681-700,共20页
In this study,a novel hybrid Water Cycle Moth-Flame Optimization(WCMFO)algorithm is proposed for multilevel thresholding brain image segmentation in Magnetic Resonance(MR)image slices.WCMFO constitutes a hybrid betwee... In this study,a novel hybrid Water Cycle Moth-Flame Optimization(WCMFO)algorithm is proposed for multilevel thresholding brain image segmentation in Magnetic Resonance(MR)image slices.WCMFO constitutes a hybrid between the two techniques,comprising the water cycle and moth-flame optimization algorithms.The optimal thresholds are obtained by maximizing the between class variance(Otsu’s function)of the image.To test the performance of threshold searching process,the proposed algorithm has been evaluated on standard benchmark of ten axial T2-weighted brain MR images for image segmentation.The experimental outcomes infer that it produces better optimal threshold values at a greater and quicker convergence rate.In contrast to other state-of-the-art methods,namely Adaptive Wind Driven Optimization(AWDO),Adaptive Bacterial Foraging(ABF)and Particle Swarm Optimization(PSO),the proposed algorithm has been found to be better at producing the best objective function,Peak Signal-to-Noise Ratio(PSNR),Standard Deviation(STD)and lower computational time values.Further,it was observed thatthe segmented image gives greater detail when the threshold level increases.Moreover,the statistical test result confirms that the best and mean values are almost zero and the average difference between best and mean value 1.86 is obtained through the 30 executions of the proposed algorithm.Thus,these images will lead to better segments of gray,white and cerebrospinal fluid that enable better clinical choices and diagnoses using a proposed algorithm. 展开更多
关键词 Hybrid WCMFO algorithm Otsu’s function multilevel thresholding image segmentation brain MR image
下载PDF
A Gridless-Finite Volume Hybrid Algorithm for Euler Equations 被引量:4
16
作者 马志华 陈红全 吴晓军 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2006年第4期286-294,共9页
A fast hybrid algorithm based on gridless method coupled with finite volume method (FVM) is developed for the solution to Euler equations. Compared with pure gridless method, the efficiency of the hybrid algorithm i... A fast hybrid algorithm based on gridless method coupled with finite volume method (FVM) is developed for the solution to Euler equations. Compared with pure gridless method, the efficiency of the hybrid algorithm is improved to the level of finite volume method for most parts of the flow filed arc covered with grid cells. Moreover, the hybrid method is flexible to deal with the configurations as clouds of points are used to cover the region adjacent to the bodies. Mirror satellites and mirror grid cells arc introduced to the interface to accomplish data communication between the different parts of the flow field. The Euler Equations arc spatially discretized with finite volume method and gridless method in mesh and clouds of points respectively, and an explicit four-stage Runge-Kutta scheme is utilized to reach the steady-state solution. Internal flows in channels and external flows over airfoils arc investigated with hybrid method, and the solutions arc comparad to those using pure finite volume method and pure gridless method. Numerical examples show that the hybrid algorithm captures the shock waves accurately, and it is as efficient as fmite volume method. 展开更多
关键词 fluid mechanicsl hybrid algorithm gridless method finite volume method Euler equations
下载PDF
Self-adaptive Bat Algorithm With Genetic Operations 被引量:4
17
作者 Jing Bi Haitao Yuan +2 位作者 Jiahui Zhai MengChu Zhou H.Vincent Poor 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2022年第7期1284-1294,共11页
Swarm intelligence in a bat algorithm(BA)provides social learning.Genetic operations for reproducing individuals in a genetic algorithm(GA)offer global search ability in solving complex optimization problems.Their int... Swarm intelligence in a bat algorithm(BA)provides social learning.Genetic operations for reproducing individuals in a genetic algorithm(GA)offer global search ability in solving complex optimization problems.Their integration provides an opportunity for improved search performance.However,existing studies adopt only one genetic operation of GA,or design hybrid algorithms that divide the overall population into multiple subpopulations that evolve in parallel with limited interactions only.Differing from them,this work proposes an improved self-adaptive bat algorithm with genetic operations(SBAGO)where GA and BA are combined in a highly integrated way.Specifically,SBAGO performs their genetic operations of GA on previous search information of BA solutions to produce new exemplars that are of high-diversity and high-quality.Guided by these exemplars,SBAGO improves both BA’s efficiency and global search capability.We evaluate this approach by using 29 widely-adopted problems from four test suites.SBAGO is also evaluated by a real-life optimization problem in mobile edge computing systems.Experimental results show that SBAGO outperforms its widely-used and recently proposed peers in terms of effectiveness,search accuracy,local optima avoidance,and robustness. 展开更多
关键词 Bat algorithm(BA) genetic algorithm(GA) hybrid algorithm learning mechanism meta-heuristic optimization algorithms
下载PDF
A Hybrid Particle Swarm Optimization and Genetic Algorithm for Model Updating of A Pier-Type Structure Using Experimental Modal Analysis 被引量:3
18
作者 Alireza MOJTAHEDI Shahriar BAYBORDI +1 位作者 Amin FATHI Aliakbar YAGHUBZADEHb 《China Ocean Engineering》 SCIE EI CSCD 2020年第5期697-707,共11页
Conventional design of pier structures is based on the assumption of fully rigid joints. In practice, the real connections are semi-rigid that cause changes in dynamic characteristics. In this study, quality of the jo... Conventional design of pier structures is based on the assumption of fully rigid joints. In practice, the real connections are semi-rigid that cause changes in dynamic characteristics. In this study, quality of the joints is investigated by considering changes in natural frequencies. For this purpose, numerical and experimental modal analyses are carried out on related physical model of a pier type structure. When numerical results are evaluated,natural frequencies generally do not match the expected experimental results. Uncertainties in different aspects of engineering problems are always a challenge for researchers. The numerical models which are constructed on the basis of highly idealized scheme may not be able to represent all of the physical aspects of the physical one. For this study, determination of percentage of semi-rigid joints is considered as an optimization problem based on the numerical and experimental frequencies. Probabilistic sensitivity analysis is also used to determine the search space.A new technique of optimization problem is solved by a combination of smart particle swarm optimization(PSO)and genetic algorithms, and a complicated and efficient system for model updating process is introduced. It is observed that the hybrid PSO-Genetic algorithm is applicable and appropriate in model updating process. It performs better than PSO algorithm, considering the good agreement between theoretical frequencies and experimental ones,before and after model updating. 展开更多
关键词 pier structure probabilistic sensitivity analysis hybrid PSO-Genetic algorithm dynamic characteristics
下载PDF
Optimization of the seismic processing phase-shift plus finite-difference migration operator based on a hybrid genetic and simulated annealing algorithm 被引量:2
19
作者 Luo Renze Huang Yuanyi +2 位作者 Liang Xianghao Luo Jun Cao Ying 《Petroleum Science》 SCIE CAS CSCD 2013年第2期190-194,共5页
Although the phase-shift seismic processing method has characteristics of high accuracy, good stability, high efficiency, and high-dip imaging, it is not able to adapt to strong lateral velocity variation. To overcome... Although the phase-shift seismic processing method has characteristics of high accuracy, good stability, high efficiency, and high-dip imaging, it is not able to adapt to strong lateral velocity variation. To overcome this defect, a finite-difference method in the frequency-space domain is introduced in the migration process, because it can adapt to strong lateral velocity variation and the coefficient is optimized by a hybrid genetic and simulated annealing algorithm. The two measures improve the precision of the approximation dispersion equation. Thus, the imaging effect is improved for areas of high-dip structure and strong lateral velocity variation. The migration imaging of a 2-D SEG/EAGE salt dome model proves that a better imaging effect in these areas is achieved by optimized phase-shift migration operator plus a finite-difference method based on a hybrid genetic and simulated annealing algorithm. The method proposed in this paper is better than conventional methods in imaging of areas of high-dip angle and strong lateral velocity variation. 展开更多
关键词 Migration operator phase-shift plus finite-difference hybrid algorithm genetic andsimulated annealing algorithm optimization coefficient
下载PDF
A new hybrid algorithm for global optimization and slope stability evaluation 被引量:3
20
作者 Taha Mohd Raihan Khajehzadeh Mohammad Eslami Mahdiyeh 《Journal of Central South University》 SCIE EI CAS 2013年第11期3265-3273,共9页
A new hybrid optimization algorithm was presented by integrating the gravitational search algorithm (GSA) with the sequential quadratic programming (SQP), namely GSA-SQP, for solving global optimization problems a... A new hybrid optimization algorithm was presented by integrating the gravitational search algorithm (GSA) with the sequential quadratic programming (SQP), namely GSA-SQP, for solving global optimization problems and minimization of factor of safety in slope stability analysis. The new algorithm combines the global exploration ability of the GSA to converge rapidly to a near optimum solution. In addition, it uses the accurate local exploitation ability of the SQP to accelerate the search process and find an accurate solution. A set of five well-known benchmark optimization problems was used to validate the performance of the GSA-SQP as a global optimization algorithm and facilitate comparison with the classical GSA. In addition, the effectiveness of the proposed method for slope stability analysis was investigated using three ease studies of slope stability problems from the literature. The factor of safety of earth slopes was evaluated using the Morgenstern-Price method. The numerical experiments demonstrate that the hybrid algorithm converges faster to a significantly more accurate final solution for a variety of benchmark test functions and slope stability problems. 展开更多
关键词 gravitational search algorithm sequential quadratic programming hybrid algorithm global optimization slope stability
下载PDF
上一页 1 2 8 下一页 到第
使用帮助 返回顶部