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A novel approach to speckle noise filtering based on artificial bee colony algorithm: An ultrasound image application

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COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2013年第3期111卷 561-569页

作者： Latifoglu, Fatma Erciyes Univ Fac Engn Dept Biomed Engn Kayseri Turkey

In this study a novel approach based on 2D FIR filters is presented for denoising digital images. In this approach the filter coefficients of 2D FIR filters were optimized using the artificial bee colony (ABC) algorithm. To obtain the best filter design, the filter coefficients were tested with different numbers (3 x 3, 5 x 5, 7 x 7, 11 x 11) and connection types (cascade and parallel) during optimization. First, the speckle noise with variances of 1, 0.6, 0.8 and 0.2 respectively was added to the synthetic test image. Later, these noisy images were denoised with both the proposed approach and other well-known filter types such as Gaussian, mean and average filters. For image quality determination metrics such as mean square error (MSE), peak signal-to-noise ratio (PSNR) and signal-to-noise ratio (SNR) were used. Even in the case of noise having maximum variance (the most noisy), the proposed approach performed better than other filtering methods did on the noisy test images. In addition to test images, speckle noise with a variance of 1 was added to a fetal ultrasound image, and this noisy image was denoised with very high PSNR and SNR values. The performance of the proposed approach was also tested on several clinical ultrasound images such as those obtained from ovarian, abdomen and liver tissues. The results of this study showed that the 2D FIR filters designed based on ABC optimization can eliminate speckle noise quite well on noise added test images and intrinsically noisy ultrasound images. (c) 2013 Elsevier Ireland Ltd. All rights reserved.

关键词： 2D FIR filter artificial bee colony algorithm Mean square error Peak signal-to-noise ratio Speckle noise Ultrasound image denoising

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Stacking optimized with artificial bee colony for driving style classification by feature reconstruction from OBD II data

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SOFT COMPUTING 2023年第1期27卷 591-603页

作者： Priyadharshini, G. Ukrit, M. Ferni SRM Inst Sci & Technol Sch Comp Kattankulathur 603203 Tamil Nadu India

Awareness and attention of drivers while driving show a vital role in decreasing the number of collisions. In the modern decades, in-car entertainment is a major cause of degradation of drivers' performance and losing consciousness. However, there are other factors such as drowsiness and tiredness that have an important part as well. Earlier detection of this degradation in behavior can be used to provide suggestions to the driver while driving. The main motive behind the work is to mitigate the effects of manually labeling the data which costs lot of time and also would result in inaccurate labels. The proposed work has 2 parts: Feature reconstruction and Stacking for classification. The Feature reconstruction phase involves clustering of data from different sensors and labeling the style of driving. Then ensemble-based Stacking classifiers which are optimized with artificial bee colony algorithm is adopted for the driving style classification. The performance analysis is done by applying the stacking classifier to data from OBD. The Stacking classifier is able to achieve an accuracy of above 98% irrespective of the classical learning algorithms.

关键词： Driving style artificial bee colony algorithm Stacking OBD data Clustering Feature reconstruction

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Using an artificial bee colony algorithm for the optimal placement of viscous dampers in planar building frames

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STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 2013年第2期48卷 395-409页

作者： Sonmez, M. Aydin, E. Karabork, T. Aksaray Univ Dept Civil Engn Fac Engn TR-68100 Aksaray Turkey Nigde Univ Fac Engn Dept Civil Engn TR-51240 Nigde Turkey

In this study, an artificial bee colony algorithm (ABCA) is used to obtain the optimal size and location of viscous dampers in planar buildings to reduce the damage to the frame systems during an earthquake. The transfer function amplitude of the top displacement and the elastic base shear force evaluated at the first natural circular frequency of structures are chosen as objective functions. The damper coefficients of the added viscous dampers are taken into consideration as design variables in a planar building frame. Transfer function amplitude of the top displacement and the amplitude of the elastic base shear force at the fundamental natural frequency are minimized under an active constraint on sum of the damper coefficients of the added dampers. According to two specified objective functions, an optimization algorithm based on the ABCA is proposed. The proposed method is verified by a gradient-based algorithm;steepest direction search algorithm (SDSA). The proposed ABCA and the SDSA are applied to find the optimal damper distribution for a nine-storey planar building then the optimal damper allocation obtained from the ABCA is investigated to rehabilitate models of irregular planar buildings. The validity of the proposed method was demonstrated through a time history analysis of the optimal damper designs, which were determined based on the frequency domain using the ABCA. The numerical results of the proposed optimal damper design method show that the use of the ABCA can be a practical and powerful tool to determine the optimal damper allocation in planar building structures.

关键词： Optimal dampers artificial bee colony algorithm Passive dampers Structural optimization

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Design of frequency response masking FIR filter in the Canonic Signed Digit space using modified artificial bee colony algorithm

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ENGINEERING APPLICATIONS OF artificial INTELLIGENCE 2013年第1期26卷 660-668页

作者： Manuel, Manju Elias, Elizabeth Natl Inst Technol Dept Elect & Commun Engn Calicut 673601 Kerala India

Frequency response masking (FRM) technique along with the Canonic Signed Digit (CSD) representation is a good alternative for the design of a computationally efficient, sharp transition width, high speed finite impulse response (FIR) filter. This paper proposes two novel approaches for the joint optimization of an FRM FIR digital filter in the CSD space. The first approach uses the recently emerged artificial bee colony (ABC) algorithm and the second approach uses the Differential Evolution (DE) algorithm. In this paper, both the algorithms are modified in such a way that, they are suitable for the solution of the optimization problem posed, in which the search space consists of integers and the objective function is nonlinear. The optimization variables are encoded such that they permit the reduction in computational cost. The salient feature of the above approaches is the reduced computational complexity while obtaining good performance. Simulation results show that the ABC based design technique performs better than that using DE, which in turn outperforms the one using integer coded genetic algorithm (GA). The proposed optimization approaches can be extended to the solution of integer programming problems in other engineering disciplines also. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： artificial bee colony algorithm Differential Evolution algorithm Frequency response masking filter Canonic Signed Digit Discrete optimization

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Routing and wavelength assignment in optical networks using artificial bee colony algorithm

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OPTIK 2013年第12期124卷 1243-1249页

作者： Kavian, Yousef S. Rashedi, Arash Mahani, Ali Ghassemlooy, Zabih Shahid Chamran Univ Fac Engn Ahvaz Iran Iran Telecom Co Ahvaz Iran Shahid Bahonar Univ Fac Engn & Technol Kerman Iran Northumbria Univ Sch Comp Engn & Informat Sci Newcastle Upon Tyne NE1 8ST Tyne & Wear England

This paper presents an intelligent approach for modelling Routing and wavelength assignment (RWA) problem in wavelength-routed Dense-Wavelength-Division-Multiplexing (DWDM) optical networks. A new idea based on artificial bee colony (ABC) algorithm is introduced for solving RWA problem which is known to be an NP-hard problem. In the proposed ABC-RWA approach every food source represents a possible and feasible candidate lightpath between each original and destination node pair in demand matrix. The positions of food sources are modified by some artificial bees in the population where the aim is to discover the places of food sources. The food source with the highest nectar value seems to be a solution which is evaluated by the fitness function. The proposed approach is evaluated for both path length (propagation delay) and hops count optimization schemes for PAN EUROPEAN and NSFNET test bench optical networks. The performance of ABC based approach is compared with the Genetic algorithm (GA) model for solving RWA problem under random and heavy load traffic models. Simulation results demonstrate the ability and efficiency of proposed ABC model for solving RWA in real-world optical networks. Furthermore a comparison study approves that ABC is faster than GA to hit RWA global optimization solutions due to less complexity and computational processing. (C) 2012 Elsevier GmbH. All rights reserved.

关键词： Transparent optical networks DWDM technique Intelligent networks Routing and wavelength assignment artificial bee colony algorithm Genetic algorithm Optimization

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An artificial bee colony algorithm for locating the critical slip surface in slope stability analysis

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ENGINEERING OPTIMIZATION 2013年第2期45卷 207-223页

作者： Kang, Fei Li, Junjie Ma, Zhenyue Dalian Univ Technol Fac Infrastruct Engn Dalian Peoples R China

Determination of the critical slip surface with the minimum factor of safety of a slope is a difficult constrained global optimization problem. In this article, an artificial bee colony algorithm with a multi-slice adjustment method is proposed for locating the critical slip surfaces of soil slopes, and the Spencer method is employed to calculate the factor of safety. Six benchmark examples are presented to illustrate the reliability and efficiency of the proposed technique, and it is also compared with some well-known or recent algorithms for the problem. The results show that the new algorithm is promising in terms of accuracy and efficiency.

关键词： slope stability artificial bee colony algorithm non-circular failure surface factor of safety swarm intelligence

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DETERMINATION OF AEROSOL PARTICLE SIZE DISTRIBUTION BY A NOVEL artificial bee colony-DIFFERENTIAL EVOLUTION HYBRID algorithm

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THERMAL SCIENCE 2019年第2期23卷 1161-1172页

作者： He, Zhen-Zong Mao, Jun-Kui Han, Xing-Si Liu, Zhao-Ying NUAA Coll Energy & Power Engn Jiangsu Prov Key Lab Aerosp Power Syst Nanjing Jiangsu Peoples R China

The aerosol size distribution, a vitally important environmental quality evaluation criterion, has a significant influence on radiative transfer and meteorological phenomena. To measure the aerosol size distribution effectively and accurately, the light scattering measurement method combined with a novel artificial bee colony-dyferential evolution hybrid algorithm which was based on the artificial bee colony algorithm and differential evolution algorithm, was proposed. First, the retrieval accuracy and convergence properties of the artificial bee colony differential evolution algorithm were compared with those of the artificial bee colony algorithm. The results revealed that the artificial bee colony-differential evolution algorithm could avoid the phenomenon of local optima and low convergence accuracy which exited in artificial bee colony algorithm. Then, the parametric estimation of two commonly used monomodal aerosol size distribution, i. e. the Gamma distribution and the logarithmic normal distribution were studied under different random measurement errors. The investigation indicated that the retrieval results using the artificial bee colony-differential evolution showed better accuracy and robustness than those using the artificial bee colony. Moreover, the retrieval parameters with better monodromy characteristic would have better inverse accuracy. Finally, the actual measured aerosol size distribution over city of Harbin, China were also retrieved. All the results confirm that the artificial bee colony-dfferential evolution algorithm was an effective and reliable technique for estimating the aerosol size distribution.

关键词： artificial bee colony algorithm aerosol size distribution inverse problem light scattering measurement method

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Fuzzified artificial bee colony algorithm for nonsmooth and nonconvex multiobjective economic dispatch problem

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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2013年第Sup1期21卷 1995-2014页

作者： Koodalsamy, Chandrasekaran Simon, Sishaj Pulikottil Natl Inst Technol Dept Elect & Elect Engn Pondicherry India Natl Inst Technol Dept Elect & Elect Engn Tiruchirappalli Tamil Nadu India

The economic dispatch (ED) problem is one of the important optimization problems in power system operation. Recently the power system has stressed the need for reliable, nonpolluting, and economic operation. Hence, 3 conflicting functions of reliability, emission, and fuel cost are considered in the objective function of the proposed ED problem. The problem is formulated as a nonsmooth and nonconvex problem when the valve-point effects of thermal units are considered in the proposed reliable emission and economic dispatch (REED) problem. This paper presents a multiobjective optimization methodology for solving the newly developed REED problem using a fuzzified artificial bee colony algorithm. The artificial bee colony algorithm is used to schedule the optimal dispatch and fuzzy membership approach is used to find the best compromise solution from the Pareto optimal set. The methodology is validated on an IEEE 30-bus system and 3-, 6-, 10-, 26-, and 40-unit systems and the results are compared with the existing literature. The results clearly show that the proposed method is able to produce well-distributed Pareto optimal solutions when compared with other methods reported in the literature.

关键词： artificial bee colony algorithm reliable emission and economic dispatch problem fuzzy set theory

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An adaptive chaotic artificial bee colony algorithm for short-term hydrothermal generation scheduling

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2013年第1期53卷 34-42页

作者： Liao, Xiang Zhou, Jianzhong Ouyang, Shuo Zhang, Rui Zhang, Yongchuan Huazhong Univ Sci & Technol Sch Hydropower & Informat Engn Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Hubei Key Lab Digital Valley Sci & Technol Wuhan 430074 Hubei Peoples R China

Short-term hydrothermal scheduling (SHS) is a complicated nonlinear optimization problem with a set of constraints, which plays an important role in power system operations. In this paper, we propose to use an adaptive chaotic artificial bee colony (ACABC) algorithm to solve the SHS problem. In the proposed method, chaotic search is applied to help the artificial bee colony (ABC) algorithm to escape from a local optimum effectively. Furthermore, an adaptive coordinating mechanism of modification rate in employed bee phase is introduced to increase the ability of the algorithm to avoid premature convergence. Moreover, a new constraint handling method is combined with the ABC algorithm in order to solve the equality coupling constraints. We used a hydrothermal test system to demonstrate the effectiveness of the proposed method. The numerical results obtained by ACABC are compared with those obtained by the adaptive ABC algorithm (AABC), the chaotic ABC algorithm (CABC) and other methods mentioned in literature. The simulation results indicate that the proposed method outperforms those established optimization algorithms. (c) 2013 Elsevier Ltd. All rights reserved.

关键词： Hydrothermal scheduling artificial bee colony algorithm Adaptive Constrained optimization Swarm intelligence

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Solution of transient stability-constrained optimal power flow using artificial bee colony algorithm

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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2013年第2期21卷 360-372页

作者： Ayan, Kursat Kilic, Ulas Sakarya Univ Fac Comp & Informat Sci Dept Comp Engn Adapazari Sakarya Turkey Mehmet Akif Ersoy Univ Bucak Emin Gulmez Tech Vocat Sch Dept Elect Bucak Burdur Turkey

The transient stability constraint should be taken into consideration for the solution of the optimization problems in power systems. This paper presents a solution for the transient stability-constrained optimal power flow (TSCOPF) by a novel approach based on the artificial bee colony algorithm. The formulas of TSCOPF are derived through the addition of rotor angle inequality constraints into optimal power flow relationships. In this nonlinear optimization problem, the objective function is taken into consideration as the fuel cost of the system. The proposed approach is tested on both a WSCC 3-generator, 9-bus system and a IEEE 30-bus system, and the test results obtained are compared to prove the efficiency and effectiveness of the approach with other approaches in the literature.

关键词： artificial bee colony algorithm constrained optimization optimal power flow power system transient stability

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