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IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

作者： Jiechen Xia Yansong Wang Yibing Li Collage of Information and Communications Engineering Harbin Engineering University Harbin China Shanghai Radio Monitoring Station The State Radio Monitoring Centre Shanghai China

ISBN: (数字)9781728190457

ISBN: (纸本)9781728190464

In the application of Global Navigation Satellite System (GNSS), an optimal subset of observable navigation satellites needs to be selected to improve the positioning accuracy and reduce the computational burden for GNSS receiver. A navigation satellite selection method based on tabu search artificial bee colony algorithm (TSABC) is proposed in this paper. It takes the geometric dilution of precision (GDOP) as objective function, the selection problem is solved by applying the TSABC algorithm to find the optimal subset of observable satellites with the minimum value of GDOP in solution space. Simulation results show that the proposed algorithm can find the optimal combination of satellites with high positioning accuracy efficiently with few parameters to be adjusted, and has a better optimization ability compared with ant colony optimization (ACO) in navigation satellite selection problem.

关键词： Global navigation satellite system Satellites Simulation Receivers artificial bee colony algorithm Search problems Optimization

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Design of Unknown Input Estimator with artificial bee colony algorithm

Design of Unknown Input Estimator with Artificial Bee Colony...

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Annual Conference of Industrial Electronics Society

作者： Toshiyuki Satoh Shun Nishizawa Naoki Saito Jun-ya Nagase Norihiko Saga Faculty of Systems Science and Technology Akita Prefectural University Yurihonjo Akita Japan Faculty of Science and Technology Ryukoku University Otsu Shiga Japan School of Science and Technology Kwansei Gakuin University Sanda Hyogo Japan

ISBN: (数字)9781728154145

ISBN: (纸本)9781728154152

We propose a design method of a recently developed unknown-input estimator (UIE) with artificial bee colony (ABC) algorithm. The design of the UIE requires two weight matrices to compute two gain matrices. To determine the weight matrices using the ABC algorithm, we devise an appropriate objective function in that disturbance estimation in discrete-time is taken into account. The proposed method is applied to the design of the UIE for a control system of a three-link manipulator. The experimental results show that the designed UIE effectively estimates and compensates for disturbances.

关键词： artificial bee colony algorithm Estimation Transfer functions Optimization Linear programming Laplace equations Control systems

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A Fuzzy-PD Controller Optimized by artificial bee colony algorithm Applied to a Small-Scale Pasteurization Plant

A Fuzzy-PD Controller Optimized by Artificial Bee Colony Alg...

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IEEE ANDESCON

作者： Andrés Arostegui Diego S. Benítez Luis Caiza Universidad San Francisco de Quito USFQ Quito Ecuador

ISBN: (数字)9781728193656

ISBN: (纸本)9781728193663

Optimization problems are widely used in numerous fields of science, engineering, and industry. On many occasions, such optimization problems involve a large number of decision variables and complex structured objectives. Applying fuzzy logic theory to the classical or traditional control strategies often requires the use of optimization techniques to shape the membership functions better. This paper presents a fuzzy-PD controller’s design using an artificial bee colony optimization algorithm, which is based on the intelligent foraging behavior of honeybee swarm. The proposed optimized controller is then applied to control the temperature of a heat exchanger in a scale pasteurization plant. The simulation results obtained are finally compared with those obtained by a classical PID controller and a non-optimized fuzzy PD+I controller.

关键词： Temperature sensors Manganese Optimization artificial bee colony algorithm Temperature measurement Mathematical model Water heating

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Optimization of Jacobi Moments Parameters using artificial bee colony algorithm for 3D Image Analysis

Optimization of Jacobi Moments Parameters using Artificial B...

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International Conference on Intelligent Computing in Data Sciences (ICDS)

作者： Ahmed Bencherqui Hicham Karmouni Acharf Daoui Mohammed Alfidi Hassan Qjidaa Mhamed Sayyouri National School of Applied Sciences Sidi Mohamed Ben Abdellah-Fez University Fez Morocco Laboratory of Electronic Signals and Systems of Information (LESSI) Dhar El Mahrez Faculty of Science Sidi Mohamed Ben Abdellah-Fez University Fez Morocco

ISBN: (数字)9781728180847

ISBN: (纸本)9781728180854

In this article, we propose a new algorithm for the optimization of the parameters of Jacobi moments by artificial bee colony (ABC) algorithm for the analysis of 3D images. The ABC algorithm is used to select the optimal parameters α and β of Jacobi polynomials and the optimal orders of Jacobi moments to improve the quality of 3D image reconstruction. The performance of the proposed algorithm is evaluated on 3D images using quantitative criteria such as the mean square error and peak signal-to-noise ratio. The results of simulations have shown the efficiency of the proposed algorithm for the analysis of 3D images compared to conventional methods.

关键词： Jacobian matrices Three-dimensional displays Image reconstruction artificial bee colony algorithm Optimization Image analysis Two dimensional displays

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Optimization of artificial bee colony algorithm Based on Immune Regulation

Optimization of Artificial Bee Colony Algorithm Based on Imm...

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Smart BlockChain (SmartBlock), International Conference on

作者： Xiangshi Zeng Congpin Zhang Tiantian Lei Yifan Wei Henan Normal University Xinxiang Henan China Teaching Resources and Big Data of Education Evaluation Henan Engineering Laboratory

In this paper, aiming at the shortcomings of the artificial bee colony (ABC) algorithm in guiding bees and observing bees in the search mechanism, the author integrated the idea of self-regulation of antibody concentration in the immune algorithm, regarded the optimal solution as antigen, and the search bee as antibody for target search. In this paper, the differences between the optimal solution and the initial solution are compared by setting parameters when initializing the nectar source, so as to enhance the memory of antibodies, avoid falling into the local optimal when maintaining the diversity of the population, accelerate the convergence speed, and increase the global search ability of the algorithm. Simulation results of six classical test functions show that the proposed algorithm has obvious advantages over ABC algorithm in terms of optimization accuracy, convergence, accuracy and stability. We will combine the proposed algorithm with Blockchain techniques in our future work.

关键词： Chaos Simulation Sociology Blockchain artificial bee colony algorithm Stability analysis Regulation

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Optimization of Laplace Wavelet Dictionary for Sparse Decomposition of Early Weak Signal of Rolling Bearing Based on artificial bee colony algorithm

Optimization of Laplace Wavelet Dictionary for Sparse Decomp...

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International Conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP)

作者： Zhang Shuo Fusheng Li School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9781665405058

ISBN: (纸本)9781665405065

The transient components in the early weak fault vibration signals of rolling bearings are easily obscured by intense background noise and cannot be detected quickly. Based on the sparse representation principle, an artificial bee colony (ABC) optimization sparsity method of the Laplace wavelet dictionary is proposed to realize the transient characteristic components in the signal extraction. Sparse decomposition with Orthogonal Matching Pursuit (OMP) algorithm is a signal adaptive decomposition algorithm, and it is one of the effective methods for weak feature extraction under strong noise background. Aiming to select and construct an over-complete dictionary for the sparse representation of rolling bearing fault vibration signals, based on the analysis of fault signals' characteristics, an improved Laplace wavelet atomic library was constructed. For solving extensive calculation and low efficiency of the orthogonal matching pursuit algorithm, this paper combines the ABC algorithm's fast operation characteristics to select the improved Laplace wavelet atom that best matches the fault through the inner product operation, thereby improving the calculation efficiency. Experiments show that the method has a proper matching with the early weak fault signals of rolling bearings and can adequately characterize fault information and judge the fault type more accurately.

关键词： Dictionaries Matching pursuit algorithms Vibrations Rolling bearings artificial bee colony algorithm Optimization Time-frequency analysis

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Efficient Channel Estimation of Massive MIMO Systems using artificial bee colony algorithm

Efficient Channel Estimation of Massive MIMO Systems using A...

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IEEE Recent Advances in Intelligent Computational Systems (RAICS)

作者： Jazir S P A Haris Suresh K College of Engineering Trivandrum APJ Abdul Kalam Technological University Kerala India Government Engineering College Idukki APJ Abdul Kalam Technological University Kerala India Government Engineering College Barton Hill APJ Abdul Kalam Technological University Kerala India

ISBN: (数字)9781728190525

ISBN: (纸本)9781728190532

Massive Multiple Input Multiple Output (m-MIMO) employs a multitude of antennas at the base station to provide spectral and energy efficiency to various users simultaneously. In order to reap the full benefits of this system, the exact channel state information (CSI) is very crucial and the channel estimation is really challenging in m-MIMO scenario. In order to find a low complexity channel estimator for m-MIMO systems, we formulate the estimation as an optimization problem and to estimate the channel accurately, we propose bio-inspired artificial bee colony (ABC) algorithm based method in this paper. Our study demonstrates that ABC based estimator is capable of achieving the mean square error (MSE) performance of optimal minimum mean squared error (MMSE) estimator without any knowledge of channel statistics or large scale fading coefficients. In our simulation, we also compare the performance of ABC estimator with that of Genetic algorithm (GA) based estimator. The results show that ABC estimator provides better error performance, faster convergence and less computational complexity than that of GA.

关键词： Wireless communication Channel estimation Estimation artificial bee colony algorithm Computational complexity Genetic algorithms Convergence

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Improved artificial bee colony algorithm based on escaped foraging strategy

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JOURNAL OF THE CHINESE INSTITUTE OF ENGINEERS 2019年第6期42卷 516-524页

作者： Chen, Ming Liaoning Univ Technol Fac Mech Engn & Automat Jinzhou 121000 Liaoning Peoples R China

This paper presents an improved artificial bee colony algorithm. Under the framework of the basic artificial bee colony algorithm, this paper redefines the artificial bee colony and introduces search strategies for group escape and foraging based on Levy flight. The proposed algorithm is named artificial bee colony algorithm based on escaped foraging strategy (EFSABC).There are different strategies for scout bees, onlookers, and free bees searching for honey sources in the EFSABC: all working bees relinquish old honey sources due to disturbance, and select different routines to seek new honey sources. Sixteen typical high-dimensional standard functions are used to verify the effectiveness of the proposed algorithm. The EFSABC algorithm outperforms the traditional artificial bee colony algorithm in all aspects.

关键词： artificial bee colony algorithm levy flight escaped foraging strategy

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Investigation of parameters affecting optimum cost design of reinforced concrete retaining walls using artificial bee colony algorithm

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GA...

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JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY 2018年第1期33卷 239-253页

作者： Dagdeviren, Ugur Kaymak, Burak Dumlupinar Univ Muhendislik Fak Insaat Muhendisligi Bolumu TR-43100 Kutahya Turkey

The analysis and design of the reinforced concrete retaining walls (RCRWs) that are commonly used in practice are one of the important problems in geotechnical engineering and structural engineering. As the overall stability of RCRWs is evaluated, lots of different failure modes based on external and internal stability must be considered together. The design of RCRW with minimum cost is affected by many parameters such as backfill, foundation soil and wall properties. In this paper, a total of 500 optimization problems were separately defined to investigate the effects of different internal friction angles of backfill, surcharge loads, heights of the wall and passive resistances at the front of the wall on the cost of the retaining walls resting on strong foundation soil. For solving these problems, minimum cost designs of RCRW were obtained by using the artificial bee colony (ABC) algorithm. As a result of the study, it was determined that the cost of the wall increased between 31% and 46% for each one-meter increase in height of the wall. As the cost rises by average 12.7% for each 10 kPa increase in surcharge load, the increase in the internal friction angle of backfill decreases the cost of the wall between 13.4% and 18.9%. In addition, the results of the study reveal that the passive resistance at the front of the wall does not affect the cost of the RCRW at the strong foundation soil conditions.

关键词： Optimum cost design reinforced concrete retaining wall artificial bee colony algorithm parameter analysis

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System performances analysis of reservoir optimization-simulation model in application of artificial bee colony algorithm

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NEURAL COMPUTING & APPLICATIONS 2018年第7期30卷 2101-2112页

作者： Hossain, M. S. El-Shafie, A. Mahzabin, M. S. Zawawi, M. H. Univ Tenaga Nas Dept Civil Engn Kajang 43000 Malaysia Univ Malaya Dept Civil & Struct Engn Kuala Lumpur Malaysia UTAR Dept Civil Engn Jalan Sungai Long Cheras 43000 Selangor Malaysia

In reservoir system operation, optimization is very much essential and the compatibility of different optimization techniques is essential to be checked by some performance checking indices. In this study, various types of performance-measuring index are used and compared to provide a complete knowledge on adopting different approaches. Here, the considered performance-measuring indicators will check the operation policy in terms of three different scenarioshow the method is efficient in achieving best results (reliability);how vulnerable the method is for different critical situation (vulnerability);and how capable it is to handle a failure of the model (resiliency). Therefore, the study proposed the artificial bee colony (ABC) optimization technique to develop an optimal water release policy for the well-known Aswan High Dam, Egypt. Particle swarm optimization, genetic algorithm and neural network-based stochastic dynamic programming are also used in a view of comparing model performances. A release curve is developed for every month as a guidance to the decision maker. Simulation has been done for each method using historical actual inflow data, and reliability, resiliency and vulnerability are measured. All model indicators proved that the release policy provided by ABC optimization outperforms in terms of achieving minimum water deficit, less waste of water and handling critical situations.

关键词： Reservoir release policy Optimization Performance checking indices artificial bee colony algorithm Evolutionary algorithms

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