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2nd IEEE International Conference on Computational Intelligence and Applications (ICCIA)

作者： Cheng, Long Qu, Lu Xu, Yu-wei Northeastern Univ Qinhuangdao Dept Comp & Commun Engn Qinhuangdao Peoples R China

ISBN: (纸本)9781538620304

Inspired by artificial bee colony algorithm (ABC), which is widely employed in various kinds of aspects. However, there is a lack of research on source seeking problem through ABC algorithm. This paper proposes a strategy which utilizes a swarm of robots to accomplish autonomous mutilple-source localization. The location method for the strategy is based on a kind of population based stochastic optimization algorithm which is called artificial bee colony algorithm (ABC). We do simulation experiments to get the most suitable parameters of the ABC algorithm according to the time and the error between each optimal solution and the source point. This strategy will minimize the overall error and maintain a shorter run time. In the future, our strategy will be utilizing in real environment, and will be employed on many kinds of different flied.

关键词： Multiple-source artificial bee colony algorithm wireless sensor network localization

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Identification of Main Steam Temperature of Power Plant Using Fractional-order Transfer Function Based on Lévy Flights-artificial bee colony algorithm 36

Identification of Main Steam Temperature of Power Plant Usin...

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第36届中国控制会议

作者： Ming Sun Ze Dong Qin Zhang Department of Automation North China Electric Power University

ISBN: (纸本)9781538629185

Fractional-order calculus with special memorability could describe dynamic characteristics of the object more accurately, and the establishment of fractional-order mathematical model can provide more convenience for tuning the parameters of PIλDμ controller. Fractional-order transfer functions can completely represent characteristics of thermal process compared with the integral-order ones applied in coal-fired power plant, such as strong coupling, disturbance factors, huge difference between response speed, etc. Aiming at the characteristics of multiple parameters for fractional-order transfer function model, two promising approaches are proposed. Firstly, an improved artificial bee colony algorithm, based on Lévy flights strategy, is introduced in optimizing the parameters of nominal model. Secondly, objective(fitness) function with penalty factor is developed to obtain the static gain of model. Finally, it is attempted to apply the proposed identification method, based on fractional-order transfer function model, to a circulating fluidized bed(CFB) superheater in an in-service power unit. The field data identification well demonstrates the virtues of improved identification method and indicates promising prospects for fractional-order transfer function model in thermal process of power plant.

关键词： Fractional-order transfer function artificial bee colony algorithm Main steam temperature object Identification

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Free parameter search of multiple tuned mass dampers by using artificial bee colony algorithm

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STRUCTURAL CONTROL & HEALTH MONITORING 2018年第2期25卷 e2066.1-e2066.1页

作者： Bozer, Ali Ozsariyildiz, Saban S. Nuh Naci Yazgan Univ Dept Civil Engn TR-38170 Kayseri Turkey

In optimization of multiple tuned mass dampers (MTMDs), certain restrictions or preconditions such as uniform distribution of stiffness, mass, or frequency spacing had been applied for simplification, but in turn, solution of individual stiffness and damping parameters are not the true optima. The main purpose of this paper is to obtain the true optima of individual stiffness and damping parameters of MTMD system. In the proposed method, parameters of TMD units are treated as free search optimization variables, and an efficient optimization algorithm, namely, artificial bee colony algorithm has been utilized in obtaining optimum parameters of MTMDs. Performance proposed method with respect to uncontrolled structure is verified through numerical analyses and compared with other reported methods. Comparisons show a superior performance of proposed approach. The basic properties of optimum design, the effectiveness, and robustness with respect to number of dampers are also discussed.

关键词： artificial bee colony algorithm earthquake multiple tuned mass dampers (MTMD) optimization robustness vibration control

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An artificial bee colony-based algorithm to Automatically Create Colour Schemes for Geovisualizations

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CARTOGRAPHIC JOURNAL 2019年第2期56卷 161-174页

作者： Wu, Mingguang Chen, Taisheng Wang, Hong Lv, Guonian Li, Huien Jin, Zhao Tao, Yi Nanjing Normal Univ Key Lab Virtual Geog Environm Minist Educ Nanjing Jiangsu Peoples R China Nanjing Normal Univ Coll Geog Sci Nanjing Jiangsu Peoples R China Jiangsu Ctr Collaborat Innovat Geog Informat Reso Nanjing Jiangsu Peoples R China Chuzhou Univ Dept Geog Informat Sci Chuzhou Peoples R China Anhui Ctr Collaborat Innovat Geog Informat Integr Chuzhou Peoples R China

Creating appropriate colour schemes is challenging for both novice and experienced cartographers. This paper introduces an artificial bee colony (ABC) algorithm to automatically create various colour schemes. Colour scheme creation is treated as a constrained search problem in a continuous colour space. We considered the gamut of the target device and a series of cartographic rules, such as convention, discrimination, contrast, perceptual uniformity and brightness mirror, in the ABC algorithm and presented detailed initialization, fitness definition, local exploration, and global exploration methods for creating qualitative, sequential and diverging colour schemes. The proposed method is evaluated with a case study, and the results indicate that compared with the brute force search method, the proposed method can create satisfying colour schemes of similar quality but significantly improved efficiency.

关键词： Colour cartographic rules artificial bee colony algorithm on-demand mapping

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An improved artificial bee colony algorithm for global numerical optimisation

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INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION 2017年第4期9卷 251-258页

作者： Yaghoobi, Tahere Esmaeili, Elahe Payame Noor Univ Dept Comp Engn Esfahan *** Iran

artificial bee colony (ABC) is a simple and powerful optimisation algorithm, which simulates the random behaviour of honey bees. In this study, a modified version of ABC algorithm is proposed by considering: 1) initialising the population based on chaos theory;2) utilising multiple searches, instead of single search, in employee and onlooker bee phases;3) controlling the frequency of perturbation by a modification rate. The proposed algorithm implemented by C# programming language and executed on benchmark functions of Sphere, Rosenbrock, Rastrigin, non-continuous Rastrigin, Griewank, Schwefel, Schwefel 1.2, Schwefel 2.2, Step and Ackley. The performance of proposed ABC algorithm is compared with ABC and modified ABC algorithms, on different tests, according to measures of mean and standard deviation. Findings showed the suggested algorithm outperforms ABC and modified ABC algorithms in 65% of test cases in getting best mean and in 55% of cases for standard deviation.

关键词： artificial bee colony algorithm metaheuristics optimisation swarm intelligence chaos

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Design of a dual-wideband monopole antenna by artificial bee colony algorithm for UMTS, WLAN, and WiMAX applications

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INTERNATIONAL JOURNAL OF MICROWAVE AND WIRELESS TECHNOLOGIES 2017年第5期9卷 1197-1208页

作者： Ustun, Deniz Akdagli, Ali Mersin Univ Fac Tarsus Technol Dept Software Engn TR-33400 Tarsus Mersin Turkey Mersin Univ Fac Engn Dept Elect Elect Engn TR-33343 Yenisehir Mersin Turkey

In this study, a dual-wideband monopole antenna has been designed and developed for the universal mobile telecommunications system (UMTS), wireless local area network (WLAN), and worldwide interoperability for microwave access (WiMAX) applications. A novel approach integrating artificial bee colony (ABC) with the HyperLynx (R) 3D electromagnetic platform based on the method of moments has been employed to calculate the design parameters of the monopole antenna performance for the respective target frequencies and return loss. The proposed dual-wideband antenna operates in the dual-frequency ranges of 1.69-3.99 and 4.75-6.22 GHz applicable for the UMTS, WLAN, and WiMAX applications and it is fabricated on the flame resistant-4 substrate plate of 42 x 51 x 1.6 mm(3). The performance of the presented monopole antenna is analyzed in terms of gain, radiation pattern, and s-parameter. The input reflection coefficient (S-11) parameter and radiation pattern of the antenna are verified through the measurements. The measured values of the antenna parameters are found to match well within tolerable limits with the simulation results. The results illustrate that the presented dual-wideband monopole antenna obtained by using the ABC algorithm exhibits better performance in point of operating bands and s-parameter as compared with the multi-band antennas previously published in the literature.

关键词： Antenna design Modeling and measurements Modeling Simulation and characterizations of devices and circuits artificial bee colony algorithm Dual-wideband UMTS WLAN WiMAX

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Fatigue crack growth prediction of 7075 aluminum alloy based on the GMSVR model optimized by the artificial bee colony algorithm

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ENGINEERING COMPUTATIONS 2017年第4期34卷 1034-1053页

作者： Yang, Dalian Liu, Yilun Li, Songbai Tao, Jie Liu, Chi Yi, Jiuhuo Hunan Univ Sci & Technol Hunan Prov Key Lab Hlth Maintenance Mech Equipmen Xiangtan Peoples R China Cent South Univ Changsha Hunan Peoples R China Cent South Univ Sch Mech & Elect Engn State Key Lab High Performance & Complex Mfg Changsha Hunan Peoples R China Cent South Univ Light Alloy Res Inst Changsha Hunan Peoples R China

Purpose - The aim of this paper is to solve the problem of low accuracy of traditional fatigue crack growth (FCG) prediction methods. Design/methodology/approach - The GMSVR model was proposed by combining the grey modeling (GM) and the support vector regression (SVR). Meanwhile, the GMSVR model parameter optimal selection method based on the artificial bee colony (ABC) algorithm was presented. The FCG prediction of 7075 aluminum alloy under different conditions were taken as the study objects, and the performance of the genetic algorithm, the particle swarm optimization algorithm, the n-fold cross validation and the ABC algorithm were compared and analyzed. Findings - The results show that the speed of the ABC algorithm is the fastest and the accuracy of the ABC algorithm is the highest too. The prediction performances of the GM(1, 1) model, the SVR model and the GMSVR model were compared, the results show that the GMSVR model has the best prediction ability, it can improve the FCG prediction accuracy of 7075 aluminum alloy greatly. Originality/value - A new prediction model is proposed for FCG combined the non-equidistant grey model and the SVR model. Aiming at the problem of the model parameters are difficult to select, the GMSVR model parameter optimization method based on the ABC algorithm was presented. the results show that the GMSVR model has better prediction ability, which increase the FCG prediction accuracy of 7075 aluminum alloy greatly.

关键词： Parameter optimization artificial bee colony algorithm (ABC) Fatigue crack growth (FCG) GMSVR prediction model

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Research of direction-of-arrival estimation in fewer snapshots based on niche artificial bee colony algorithm

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2017年第5期32卷 3475-3485页

作者： Lei, Liu Ming, Diao Harbin Engn Univ Coll Informat & Commun Engn 145 Nantong St Harbin 150001 Heilongjiang Peoples R China

This paper focuses on the issue of the large calculation when searching for the optimal solution of weighted subspace fitting algorithm (WSF) in the Direction of Arrival (DOA) estimation and introduces the artificial bee colony algorithm (ABC) to optimize solving process. Taking advantage of Niche technique and coordinating with improved strategy and control exclusion method, the proposed algorithm can overcome the weakness that bee colony algorithm itself can only get the global solutions, and hence get the local optimization solution for the multimodal problem. The experiment results demonstrate the proposed algorithm has small computation load, less controlling parameters, and high accuracy.

关键词： DOA weighted subspace fitting algorithm artificial bee colony algorithm niche

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Optimisation of Multiple Hydropower Reservoir Operation Using artificial bee colony algorithm

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WATER RESOURCES MANAGEMENT 2017年第4期31卷 1397-1411页

作者： Choong, Shi-Mei El-Shafie, A. Mohtar, W. H. M. Wan Univ Kebangsaan Malaysia Fac Engn & Built Environm Civil & Struct Engn Dept Ukm Bangi 43600 Selangor Darul Malaysia Univ Malaya Fac Engn Dept Civil Engn Jalan Univ Kuala Lumpur 50603 Malaysia

In this study, the artificial bee colony (ABC) algorithm was developed to solve the Chenderoh Reservoir operation optimisation problem which located in the state of Perak, Malaysia. The proposed algorithm aimed to minimise the water deficit in the operating system and examine its performance impact based on monthly and weekly data input. Due to its capability to identify different possible events occurring in the reservoir, the ABC algorithm provides promising and comparable solutions for optimum release curves. The optimal release curves were then used to stimulate the reservoir release under different operating times under different inflow scenarios. To investigate the performance of both the monthly and weekly ABC optimisation employed in the reservoir, the well-known reliability, resilience and vulnerability indices were used for performance assessment. The indices tests revealed that weekly ABC optimisation outperformed in terms of reliability and vulnerability leading to the development of a better release policy for optimal operation.

关键词： Reservoir optimisation artificial bee colony algorithm Operation system Simulation Reliability

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A hybrid artificial bee colony algorithm for the cooperative maximum covering location problem

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INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 2017年第2期8卷 691-697页

作者： Jayalakshmi, B. Singh, Alok Univ Hyderabad Sch Comp & Informat Sci Hyderabad 500046 Andhra Pradesh India

This paper proposes a hybrid artificial bee colony algorithm for the cooperative maximum covering location problem (CMCLP) on a network. In location covering problems, it is assumed that each facility generates a signal whose strength decreases with the increase in distance and a demand point is considered to be covered if the total signal strength received by it from various facilities exceeds a certain threshold. The objective of the CMCLP is to locate the facilities in such a way that maximizes the total demands covered. The proposed hybrid approach obtained better quality solutions in comparison to the methods available in the literature.

关键词： artificial bee colony algorithm Cooperative maximum covering location problem Heuristic Networks Swarm intelligence

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