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Low power 2D finite impulse response filter design using modified artificial bee colony algorithm with experimental validation using field-programmable gate array

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IET SCIENCE MEASUREMENT & TECHNOLOGY 2016年第6期10卷 671-678页

作者： Dwivedi, Atul Kumar Ghosh, Subhojit Londhe, Narendra D. NIT Raipur Dept Elect Engn Raipur Madhya Pradesh India

Motivated by the need of reducing power consumption (PC) in two dimensional (2D) finite impulse response (FIR) filters, in this work, the 2D FIR filter design task is formulated as an optimisation problem that seeks to attain the desired frequency response and reduces PC. The optimisation problem has been solved using the modified version of artificial bee colony algorithm. The applicability of the proposed approach has been evaluated by designing circular shaped 2D FIR filters for a set of specifications in frequency domain. The designed filters have been compared with other reported state of the art techniques. The evaluation is carried out in terms of pass band and stop band ripple minimisation, convergence profile and PC during filter execution in hardware. The proposed technique is found to outperform all other techniques in achieving minimum ripple for a given filter order. To prove the effectiveness of the proposed approach for PC reduction, the designed filters have been implemented in hardware using field-programmable gate array (xc7vx485t-2ffg1761). The PC computed using Xilinx X-power analyser shows that 23.53% power can be saved using the proposed approach as compared with conventional design approaches.

关键词： FIR filters field programmable gate arrays singular value decomposition band-pass filters band-stop filters minimisation low power 2D finite impulse response filter design modified artificial bee colony algorithm field-programmable gate array cooling maintenance power consumption PC low power two-dimensional FIR filter singular value decomposition Hamming distance optimisation problem circular shaped 2D FIR filter frequency domain analysis pass band ripple minimisation stop band ripple minimisation Xilinx X-power analyser

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A modified artificial bee colony algorithm for Parameter Estimation of Fractional-Order Nonlinear Systems

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IEEE ACCESS 2018年 6卷 48600-48610页

作者： Cai, Di Yu, Yongguang Wei, Jiamin Beijing Jiaotong Univ Dept Math Beijing 100044 Peoples R China

In this paper, a modified artificial bee colony (MABC) algorithm is proposed to estimate the unknown fractional-order nonlinear systems. First, the parameter estimation problem can be mathematically transformed into a multi-dimensional continuous function optimization problem, which is solved via the MABC algorithm. The proposed MABC algorithm well combines the original artificial bee colony algorithm (ABC) and the Nelder-Mead simplex method (NMS) in a very simple way, which takes full advantage of the exploration ability of the ABC algorithm and the exploitation ability of the NMS. And in the meanwhile, the proposed algorithm improves the speed of convergence. To evaluate the effectiveness of the proposed MABC algorithm, numerical simulations contain two typical uncertain fractional-order nonlinear systems. The results show that compared with the other population-based algorithm and ABC-variants, the proposed MABC for solving the problem of parameter estimation get the faster convergence speed and higher calculation accuracy.

关键词： modified artificial bee colony algorithm fractional-order parameter estimation

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Groundwater management using a new coupled model of meshless local Petrov-Galerkin method and modified artificial bee colony algorithm

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COMPUTATIONAL GEOSCIENCES 2018年第3期22卷 657-675页

作者： Boddula, Swathi Eldho, T., I Indian Inst Technol IIT Bombay Dept Civil Engn Bombay Maharashtra India Indian Inst Technol Dept Civil Engn Bombay Maharashtra India

To develop sustainable groundwater management strategies, generally coupled simulation-optimization (SO) models are used. In this study, a new SO model is developed by coupling moving least squares (MLS)-based meshless local Petrov-Galerkin (MLPG) method and modified artificial bee colony (MABC) algorithm. The MLPG simulation model utilizes the advantages of meshless methods over the grid-based techniques such as finite difference (FDM) and finite element method (FEM). For optimization, the basic artificial bee colony algorithm is modified to balance the exploration and exploitation capacity of the model more effectively. The performance of the developed MLPG-MABC model is investigated by applying it to hypothetical and field problems with three different management scenarios. The model results are compared with other available SO model solutions for its accuracy. Further, sensitivity analyses of various model parameters are carried out to check the robustness of the SO model. The proposed model gave quite promising results, showing the applicability of the present approach.

关键词： Groundwater management Simulation-optimization Meshless local Petrov Galerkin method Moving least squares modified artificial bee colony algorithm

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A modified artificial bee colony algorithm for numerical function optimization

A modified artificial bee colony algorithm for numerical fun...

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17th IEEE Symposium on Computers and Communications (lSCC)

作者： Babayigit, Bilal Ozdemir, Resul Erciyes Univ Dept Comp Engn Kayseri Turkey Nevsehir Univ Urgup USET Vocat Sch Nevsehir Turkey

ISBN: (纸本)9781467327138

artificial bee colony (ABC) algorithm, explored in recent literature, is an efficient optimization technique which simulates the foraging behavior of honeybees. ABC algorithm is good at exploration but poor at exploitation. This paper presents a new modified ABC algorithm for numerical optimization problems to improve the exploitation capability of the ABC algorithm. A different probability function and a new searching mechanism are proposed. The modified ABC algorithm is tested on seven numerical optimization problems. The results demonstrate that the modified ABC algorithm outperforms the ABC algorithm on solution quality and faster convergence.

关键词： Swarm intelligence modified artificial bee colony algorithm numerical function optimization

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Solution to Economic Emission Load Dispatch Problem Using modified artificial bee colony algorithm

Solution to Economic Emission Load Dispatch Problem Using Mo...

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3rd International Conference on Electric Power and Energy Conversion Systems (EPECS)

作者： Jadhav, H. T. Raj, Shubham Roy, Ranjit Rajarambapu Inst Technol Dept Elect Engn Islampur India SV Natl Inst Technol Dept Elect Engn Surat India

ISBN: (纸本)9781479906871;9781479906888

This paper presents an application of modified artificial bee colony algorithm (MABC) to determine the optimized solution of economic and emission load dispatch (EELD) problem. The EELD problem is formulated as a biobjective problem by taking minimization of fuel cost and emission levels as objectives. In order to convert a biobjective problem into a single objective function weighing factor is used. Effectiveness of the MABC algorithm is verified by applying it on five standard test systems and the outcomes are compared with the latest reported literatures. It is proved from the results that MABC algorithm is more powerful than other algorithms.

关键词： economic and emission load dispatch modified artificial bee colony algorithm price penalty factor weighing factor

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Transmission network expansion planning using a modified artificial bee colony algorithm

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INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS 2017年第9期27卷 1-23页

作者： Das, Soumya Verma, Ashu Bijwe, Pradeep R. IIT Delhi Ctr Energy Studies New Delhi India IIT Delhi Dept Elect Engn New Delhi India

Transmission network expansion planning (TNEP) problem is an essential part of power system expansion planning, and it is an extremely complex nonlinear, nonconvex, mixed-integer optimization problem. Solution to such a computationally intensive problem is a challenge for any optimization algorithm. Consideration of security constraints makes the problem even more formidable. Although various conventional and metaheuristic methods have been used in the past to solve such problem, scope for better optimization techniques always remain. The artificial bee colony (ABC) algorithm is one of the newest swarm intelligence-based optimization algorithms, which has delivered promising results in solving numerical optimization problems. However, the algorithm is quite less efficient in solving real-life constrained engineering problems. In this paper, a modified ABC (MABC) algorithm is formulated by incorporating the idea of global attraction, universal gravitation, and by introducing modified ways of searching in various bees' phases of the ABC algorithm. The MABC is able to get better results in a very efficient manner, when used for solving various benchmark functions. The efficiency and effectiveness of the MABC algorithm in solving constrained engineering problems is demonstrated by solving TNEP problems for different systems. The proposed method is tested on IEEE 24 bus system, South Brazilian 46 bus system, Colombian 93 bus system for direct current TNEP model, and Garver 6 bus system for alternating current TNEP model. Results confirm that MABC can be an attractive alternative to the existing optimization algorithms for solving very complex nonlinear engineering optimization problems in a real-world situation.

关键词： metaheuristic algorithm modified artificial bee colony algorithm network security constraints power system planning transmission network expansion planning

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A modified artificial bee colony (ABC) algorithm for constrained optimization problems

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APPLIED SOFT COMPUTING 2011年第3期11卷 3021-3031页

作者： Karaboga, Dervis Akay, Bahriye Erciyes Univ Dept Comp Engn TR-38039 Kayseri Turkey

artificial bee colony (ABC) algorithm was firstly proposed for unconstrained optimization problems on where that ABC algorithm showed superior performance. This paper describes a modified ABC algorithm for constrained optimization problems and compares the performance of the modified ABC algorithm against those of state-of-the-art algorithms for a set of constrained test problems. For constraint handling, ABCalgorithm uses Deb's rules consisting of three simple heuristic rules and a probabilistic selection scheme for feasible solutions based on their fitness values and infeasible solutions based on their violation values. ABC algorithm is tested on thirteen well-known test problems and the results obtained are compared to those of the state-of-the-art algorithms and discussed. Moreover, a statistical parameter analysis of the modified ABC algorithm is conducted and appropriate values for each control parameter are obtained using analysis of the variance (ANOVA) and analysis of mean (ANOM) statistics. (C) 2010 Elsevier B. V. All rights reserved.

关键词： Swarm intelligence modified artificial bee colony algorithm Constrained optimization

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Optimal Sizing of Distributed Energy in AC/DC Hybrid Stand-alone Micro-grid Using modified artificial bee colony algorithm

Optimal Sizing of Distributed Energy in AC/DC Hybrid Stand-a...

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2016 6th International Conference on Machinery,Materials,Environment,Biotechnology and Computer(MMEBC 2016)

作者： Xingjie Liu Zhe Du Xiao Yan School of North China Electric Power University

In order to reduce investment and maintenance cost, the optimal sizing of distributed energy in AC/DC hybrid stand-alone micro-grid is studied in this paperThe optimization model is built and economics, power supply reliability and environmental protection are taken into accountBy means of the modified artificial bee colony algorithm, the optimal sizing method is obtainedFinally, the feasibility of method is verified by calculating example analysisBy comparing the optimal sizing results of three different micro-grid configurations, hybrid AC/DC micro-grid is proved to be superior to traditional micro-gridFurthermore, the modified ABC is more suitable for solving optimization problems because of the higher convergence precision.

关键词： hybrid AC/DC micro-grid control strategy optimal sizing modified artificial bee colony algorithm

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Research on modified artificial bee colony Clustering algorithm

Research on Modified Artificial Bee Colony Clustering Algori...

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International Conference on Network and Information Systems for Computers (ICNISC)

作者： Cao, Lilu Xue, Dashen Maritime Univ Transportat & Management Dept Dalian Dalian Peoples R China

ISBN: (纸本)9781479918430

In order to overcome the disadvantages of the K-Means Clustering algorithm, such as the poor global search ability, being sensitive to initial cluster centric, as well as the vulnerable to trap in local optima and the slow convergence velocity in later period of the original artificial bee colony (ABC) algorithm, a modified ABC algorithm was proposed. modified artificial bee colony algorithm combined with K-means Clustering algorithm, named it as MABC-K-means algorithm, to establish Hybrid algorithm for solving framework. Through extensive testing, the MABC-K-means algorithm can improve cluster performance effectively. Finally, according to optimization solution strategy, instantiate Customer Relationship Management issue in the process of instantiating framework.

关键词： cluster analysis modified artificial bee colony algorithm Customer Relationship Management

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Design Optimization of a Six-Phase Induction Motor by Flower pollination and modified artificial bee colony algorithms

Design Optimization of a Six-Phase Induction Motor by Flower...

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IEEE Region 10 Conference (TENCON)

作者： Das, Pratyush Prasanna Mahato, S. N. NIT Durgapur Dept Elect Engn Durgapur India

ISBN: (纸本)9781509025978

A modified version of artificial bee colony algorithm and Flower pollination algorithm are used in this paper, in order to optimize the design of a six phase induction motor (SPIM). The objective functions used are more than one for the said optimization. In this paper, a comparison of the results as obtained by traditional method, modified artificial bee colony algorithm (mABC) and Flower Pollination algorithm (FPA) has been carried out and presented. The results show that much more superior and efficient design is obtained by modified ABC and Flower Pollination algorithms as compared to traditional design procedure. The comparison of the results is only to find the fittest method and also the performance of the said machine is evaluated for each of the cases as mentioned.

关键词： design optimization efficiency flower pollination algorithm modified artificial bee colony algorithm six-phase induction motor

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