检索结果-内蒙古大学图书馆

第30届中国控制与决策会议

作者： Yang Yang Feiyi Xu Haidong Hu Hao Gao The Institute of Advanced Technology Nanjing University of Posts and Telecommunications Beijing Institute of Control Engineering

The artificial bee colony（ABC） algorithm invented by Karaboga is a relative new nature inspired heuristic for optimization problem. It has been proved to be competitive with some conventional optimization algorithms. This paper proposes an adaptive unified artificial bee colony（auABC） algorithm which employs a single equation unifying multiple strategies into one expression. As we all know, ABC is good at exploration but poor at exploitation due to the insufficiency in its solution search equation and its one-dimensional search strategy leads to slower convergence speed. In order to improve the above defects, we created a combined self-adaptive equation that its parameters are determined by the current iteration times to solve the problem mentioned above. We also introduce a chaotic strategy when generating candidate food sources which balance the proportion of exploration and exploitation. Experiments conducted on benchmark functions demonstrate that our algorithm achieves good performance in both unimodal and multimodal functions as expected compared to several state-of-the-art algorithms.

关键词： artificial bee colony algorithm Solution search equation Adaptive strategy

来源：评论

学校读者我要写书评

暂无评论

artificial bee colony algorithm with Principal Component Analysis

引用

ELECTRONICS AND COMMUNICATIONS IN JAPAN 2016年第9期99卷 47-61页

作者： Mori, Daisuke Yamaguchi, Satoshi Chiba Inst Technol Grad Sch Informat & Comp Sci Narashino Chiba Japan Chiba Inst Technol Fac Informat & Comp Sci Narashino Chiba Japan

This paper proposes novel artificial bee colony (ABC) algorithms for solving problems including interdependence among variables. ABC algorithms are one method of solving multivariable real number space optimization problems, in which the search space is a set of vectors constructed of variables. The main search process in the ordinary ABC algorithm creates a new solution vector by changing only one variable of the current solution vector. Therefore, the new solution vector is created along only one coordinate axis. This procedure, however, is not appropriate for solving problems including interdependence among variables. For such problems, a method that is able to change more than one variable of a solution vector at the same time is required. In our proposed methods, the original coordinate axes are transformed to linearly uncorrelated axes by using principal component analysis (PCA) in the searching process. Our ABC algorithms create a new solution vector along one of the axes transformed by PCA. Hence, from the viewpoint of the original coordinate axes, the new algorithms are able to change more than one variable. The proposed algorithms have been compared with the ordinary ABC algorithm by solving five benchmark problems. Through the computer simulation results, our algorithms were shown to have better performance for solving problems including interdependence among variables than the ordinary ABC algorithm.

关键词： artificial bee colony algorithm principal component analysis interdependence among variables medial axis transformation

来源：评论

学校读者我要写书评

暂无评论

artificial bee colony algorithm for clustering: an extreme learning approach

引用

SOFT COMPUTING 2016年第8期20卷 3163-3176页

作者： Alshamiri, Abobakr Khalil Singh, Alok Surampudi, Bapi Univ Hyderabad Sch Comp & Informat Sci Hyderabad 500046 Andhra Pradesh India Int Inst Informat Technol Cognit Sci Lab Hyderabad 500032 Andhra Pradesh India

Extreme learning machine (ELM) as a new learning approach has shown its good generalization performance in regression and classification applications. Clustering analysis is an important tool to explore the structure of data and has been employed in many disciplines and applications. In this paper, we present a method that builds on ELM projection of input data into a high-dimensional feature space and followed by unsupervised clustering using artificial bee colony (ABC) algorithm. While ELM projection facilitates separability of clusters, a metaheuristic technique such as ABC algorithm overcomes problems of dependence on initialization of cluster centers and convergence to local minima suffered by conventional algorithms such as K-means. The proposed ELM-ABC algorithm is tested on 12 benchmark data sets. The experimental results show that the ELM-ABC algorithm can effectively improve the quality of clustering.

关键词： Clustering Extreme learning machine K-means algorithm artificial bee colony algorithm

来源：评论

学校读者我要写书评

暂无评论

IIR Filter Design Using Multiobjective artificial bee colony algorithm

IIR Filter Design Using Multiobjective Artificial Bee Colony...

引用

IEEE Canadian Conference on Electrical and Computer Engineering

作者： Rija Raju Hon Keung Kwan Department of Electrical and Computer Engineering University of Windsor 401 Sunset Avenue Windsor Ontario N9B 3P4 Canada

ISBN: (纸本)9781538624111

In this paper, IIR filters are designed using Gbest-guided Multiobjective artificial bee colony algorithm (GMOABC). artificial bee colony algorithm (ABC) is a stochastic optimization algorithm inspired by the food seeking behavior of honey bee colonies. Even though ABC algorithm can converge to a global optimum for complex problems, the time taken for convergence is longer than classical methods. Gbest guided multiobjective ABC algorithm can reduce the time taken for converging to global optimum and improves the quality of the solutions by tuning the search process towards the global best in each iteration. IIR filter design is a non-convex optimization problem and requires the optimization of both the magnitude and group delay. The results show that, GMOABC can achieve lower passband error and group delay error than the recent results obtained by other methods.

关键词： IIR filters optimization artificial bee colony algorithm multiobjective optimization minimax design digital filters evolutionary algorithms

来源：评论

学校读者我要写书评

暂无评论

An Improved Adaptive artificial bee colony algorithm

An Improved Adaptive Artificial Bee Colony Algorithm

引用

第30届中国控制与决策会议

作者： Peng Chen Qing Li Cong Xu Yue-fei Zhao En-ji Dong Jia-rui Cui School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing Key Laboratory of Knowledge Engineering for Materials Science

Aiming to the main disadvantages of artificial bee colony algorithm: slow searching speed arisen from the low exploitation of global information and the high possibility to be caught into local convergence, an improved algorithm is proposed in this paper. Two different location updating strategies are separately designed for employed bees and onlooker bees(when they are changed into employed bees). At first, the location(food source) updating formula for employed bees is developed by obtaining the current global optimal information so as to accelerate the convergence speed. In addition, an adaptive strategy is introduced to increase the probability by which the employed bees are changed into scouts, thereby strengthening the randomness and the possibility to find a better solution. After that, a new location updating method is presented for onlooker bees in order to keep the randomness in a reasonable degree. The results of experiments on several test functions show that this new algorithm has a satisfactory performance such as high quality of solutions and quick convergence speed.

关键词： artificial bee colony algorithm Adaptive Location Updating Strategy Scouts

来源：评论

学校读者我要写书评

暂无评论

Elitism Based artificial bee colony algorithm

Elitism Based Artificial Bee Colony Algorithm

引用

IEEE International Conference on Computing, Communication and Automation (ICCCA)

作者： Rajawat, Ankita Sharma, Nirmala Sharma, Harish Rajasthan Tech Univ Kota India

ISBN: (纸本)9781509064717

artificial bee colony (ABC) algorithm is one of the efficient meta-heuristic optimization algorithm, based on bee behavior for food searching. In order to improve the exploitation ability of ABC algorithm, an elitism based exploitation strategy is incorporated in ABC and the proposed variant is named as Elitism Based ABC algorithm (EbABC). In the proposed search strategy, the step sizes of the solutions during the solution search process depend on a weighted component, calculated by using three best solutions of the swarm. Further, in order to compensate the exploration, a global search ability is introduced in scout bee stage. To analyze the performance of EbABC, it is applied on 15 standard benchmark functions and the results are compared with some significant variants of ABC. The analysis of the results shows that the proposed EbABC algorithm is a competitive variant of ABC algorithm.

关键词： Nature Inspired algorithm artificial bee colony algorithm Elitism Optimization algorithm Natural phenomenon

来源：评论

学校读者我要写书评

暂无评论

An improved multi-cores parallel artificial bee colony optimization algorithm for parameters calibration of hydrological model

引用

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2018年 81卷 492-504页

作者： Huo, Jiuyuan Liu, Liqun Zhang, Yaonan Lanzhou Jiaotong Univ Sch Elect & Informat Engn Lanzhou 730070 Gansu Peoples R China Gansu Agr Univ Coll Informat Sci & Technol Lanzhou 730070 Gansu Peoples R China Chinese Acad Sci Northwest Inst Ecoenvironm & Resources Lanzhou 730000 Gansu Peoples R China Gansu Data Engn & Technol Res Ctr Resources & Env Lanzhou 730000 Gansu Peoples R China

Parameter optimization and calibration play a crucial role in the overall performance of hydrological models and the quality of hydrologic forecast results. The hydrological model is characterized by high complexity, a large number of parameters, high dimensionality and a large amount of data processing. Therefore, there are many computationally intensive tasks in model parameter optimization that require a large CPU processing time. To improve the optimization precision and performance for parameters optimization of the Xinanjiang model, a parallel Multi-core Parallel artificial bee colony algorithm (MPABC) was proposed based on the hybrid hierarchical model and Fork/Join framework. The algorithm is to introduce the multi-populations' parallel operation to guarantee the population's diversity, improve the global convergence ability and avoid falling into the local optimum. And also in order to divide the complex computing task into several independent parallel sub-tasks on different cores, so as to take all the performance advantages of multi-core CPU. The experiment is divided into two parts. In the first part, the performance of the original serial ABC algorithm and the MPABC algorithm is analyzed and compared based on four benchmark objective functions. The results show that the MPABC algorithm can achieve a speedup of 3.795 and an efficiency of 94.87% in solving complex problems. The MPABC algorithm could greatly improve the optimization efficiency. The second part is to select the Nash-Sutcliffe coefficient as the objective function and apply the MPABC and PPSO and PgGA algorithms to optimize the Xinanjiang hydrological model in the Heihe River Basin. The results showed that the MPABC algorithm can make full use of multi-core resources, improve the solution's quality and efficiency, and have the advantages of low parallel cost and simple realizing process. Thus, the MPABC algorithm is an effective and feasible method to solve the hydrological model parameters'

关键词： Parallel Hydrological model Parameter calibration Xinanjiang model artificial bee colony algorithm Fork/Join framework

来源：评论

学校读者我要写书评

暂无评论

Modeling of Co(II) adsorption by artificial bee colony and genetic algorithm

引用

MEMBRANE AND WATER TREATMENT 2018年第5期9卷 363-371页

作者： Ozturk, Nurcan Senturk, Hasan Basri Gundogdu, Ali Durang, Celal Karadeniz Tech Univ Fac Technol Dept Civil Engn TR-61830 Trabzon Turkey Karadeniz Tech Univ Fac Sci Dept Chem TR-61080 Trabzon Turkey Gumushane Univ Fac Engn & Nat Sci Dept Food Engn TR-29100 Gumushane Turkey

In this work, it was investigated the usability of artificial bee colony (ABC) and genetic algorithm (GA) in modeling adsorption of Co(II) onto drinking water treatment sludge (DWTS). DWTS, obtained as inevitable byproduct at the end of drinking water treatment stages, was used as an adsorbent without any physical or chemical pre-treatment in the adsorption experiments. Firstly, DWTS was characterized employing various analytical procedures such as elemental, FT-IR, SEM-EDS, XRD, XRF and TGA/DTA analysis. Then, adsorption experiments were carried out in a batch system and DWTS's Co(II) removal potential was modelled via ABC and GA methods considering the effects of certain experimental parameters (initial pH, contact time, initial Co(II) concentration, DWTS dosage) called as the input parameters. The accuracy of ABC and GA method was determined and these methods were applied to four different functions: quadratic, exponential, linear and power. Some statistical indices (sum square error, root mean square error, mean absolute error, average relative error, and determination coefficient) were used to evaluate the performance of these models. The ABC and GA method with quadratic forms obtained better prediction. As a result, it was shown ABC and GA can be used optimization of the regression function coefficients in modeling adsorption experiments.

关键词： adsorption artificial bee colony algorithm modeling genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Routing and Spectrum Allocation for Time Varying Traffic by artificial bee colony algorithm in Elastic Optical Networks

Routing and Spectrum Allocation for Time Varying Traffic by ...

引用

IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Gang Xu Xiaoxiao Li Guojun Yuan Zhan Wang Guangming Tan Xuejun An Institute of Computing Technology Chinese Academy of Sciences Beijing China Huawei Technologies Co. Ltd Beijing China Institute of Computing Technology Beijing China

ISBN: (纸本)9781728111421;9781728111414

Elastic optical networks are considered to be a promising technology in high-speed network interconnections. In order to address the time-varying routing and spectrum allocation problem in elastic optical networks, we propose a algotithm by artificial bee colony algorithm considering the time varying traffic (ABC-TV). The objective of the proposed ABC-TV algorithm is to minimize both the network spectrum utilization and the average path length criterions on the effect of benefis by sharing of spectrum slots among spectrumadjacent connections. The algorithm is simulated in different networks (NSFNET and EON). The results reveal that the algorithm improves the spectrum utilization and minimizes the number of the used frequency slots compared to other considered approaches in elastic optical networks.

关键词： Optical fiber networks Resource management Routing Heuristic algorithms Bandwidth Frequency selective surfaces artificial bee colony algorithm

来源：评论

学校读者我要写书评

暂无评论

Application of Image Segmentation Based on the artificial bee colony algorithm in Fire Detection of Mine Belt Conveyor 10

Application of Image Segmentation Based on the Artificial Be...

引用

10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)

作者： Liu, Yuxin Ma, Xianmin Xian Univ Sci & Technol Sch Elect & Control Xian Shaanxi Peoples R China

ISBN: (纸本)9781538619377

The traditional method of mine belt conveyor fire accident detection is limited. A novel image processing method is proposed in this paper, which combines 2D-Dimensional Otsu, Canny dge detection and artificial bee colony algorithm. The noise interference of image is reduced by using median filtering techniques. In order to obtain gray value and neighborhood gray scale average, 2-Dimensional histogram of image is constructed. The fitness function of artificial bee colony algorithm is designed by 2-Dimensional Otsu method and the maximum value of the fitness function is the optimal threshold for image segmentation. Finally, the canny edge detection and grayscale morphology were used to extract the target. Theoretical analysis and simulation results show that the proposed method is effective to detect fire accident of mine belt conveyor in complex undeground environment.

关键词： Mine Fire Detection Belt Conveyor Image Processing artificial bee colony algorithm Edge detection

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

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

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

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

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：