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A hybrid TLNNabc algorithm for reliability optimization and engineering design problems

ENGINEERING WITH COMPUTERS 2022年第6期38卷 5251-5295页

作者： Kundu, Tanmay Garg, Harish Chandigarh Univ Dept Math Chandigarh 140413 Punjab India Deemed Univ Sch Math Thapar Inst Engn & Technol Patiala 147004 Punjab India

The paper aims to present a new TLNNabc hybrid algorithm to solve reliability and engineering design optimization problems. In this algorithm, the structure of the artificial bee colony (abc) algorithm has been improved by incorporating the features of the neural network algorithm (NNA) and teaching-learning based optimization (TLBO). In the standard abc, the onlooker bees apply the same searching method as the employed bees, which causes slow convergence and also restricts its practical application of solving optimization problems. In view of this inadequacy and resulting in a better balance between exploration and exploitation, searching procedures for employed bees and onlooker bees of the conventional abc are renovated based on NNA and improved TLBO algorithms respectively and a new hybrid algorithm called TLNNabc has been developed in this paper. In TLNNabc, for the employed bee phase, NNA is used to increase the population diversity. However, the improved teaching learning-based optimization is embedded in the onlooker bee phase. In this context, a new search operator is introduced which increases the exploitation capability of the algorithm to operate, and a probabilistic selection strategy, which helps to determine whether to apply the original or the new search operator to construct a new solution. Finally, the performance of the proposed TLNNabc algorithm has been demonstrated by the well-known benchmark problems related to reliability optimization, structural engineering design problems, and 23 unconstrained benchmark functions and finally compared with several existing algorithms. Experimental results show that the proposed algorithm is very effective and achieves superior performance than the other algorithms.

关键词： abc algorithm Neural network algorithm TLBO Reliability redundancy allocation problem Constrained optimization

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Power System Oscillations Damping by Optimal Coordinated Design Between PSS and STATCOM Using PSO and abc algorithms 13

Power System Oscillations Damping by Optimal Coordinated Des...

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13th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)

作者： Shahgholian, Ghazanfar Fazeli-Nejad, Saeid Moazzami, Majid Mahdavian, Mehdi Azadeh, Manijeh Janghorbani, Mohammadreza Farazpey, Saeed Islamic Azad Univ Najafabad Branch Dept Elect Engn Esfahan Iran Islamic Azad Univ Naein Branch Dept Elect Engn Naein Isfahan Iran Islamic Azad Univ Cent Tehran Branch Young Researchers & Elite Club Tehran Iran

ISBN: (纸本)9781467397490

Coordinated design of the power system stabilizer (PSS) and static synchronous compensator controller parameters (STATCOM) using artificial bee colony algorithm (abc) to improve power system stability as an optimizations problem has been proposed in this study. abc algorithm is a collective inteligence based on optimization algorithm inspired by the feeding behavior of bees in finding food. Rapid convergence and high precision are the capabilities of this algorithm which in this study to demonstrate its effectiveness and robustness, a two zone - four machines system is used and analyzed through non-linear simulation of time-domain and the results are compared with particle swarm optimization (PSO) algorithm. The optimization after a large turbulence shows that the coordinated design of the STATCOM and PSS controllers' parameters using the abc algorithm considerably improves the system stability together with rapid damping of the system fluctuations as compared to the state without optimization. On the other hand, the optimization results using the abc algorithm shows the superiority of this method over the PSO algorithm.

关键词： PSS STATCOM abc algorithm PSO algorithm transient stability

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A New Design Method for Stable IIR Filters With Nearly Linear-Phase Response Based on Fractional Derivative and Swarm Intelligence

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IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE 2017年第6期1卷 464-477页

作者： Agrawal, Nikhil Kumar, Anil Bajaj, Varun Pandit Dwarka Prasad Mishra Indian Inst Informat Jabalpur 482005 India Gwangju Inst Sci & Technol Sch Elect Engn & Comp Sci Gwangju 61005 South Korea

In this paper, a new design method based on fractional derivative (FD) is proposed for designing digital stable infinite impulse response (IIR) filters with nearly linear-phase response. In this method, the design problem is formulated as a phase error optimization of an all-pass filter connected in parallel with a pure delay function. FD is employed to improve the frequency response of the filter at some reference point (omega(0)) in the passband. Optimal values of FD constraints and reference points in passband are determined by minimizing the sum of error in passband (E-p) and stopband (E-s) of an IIR filter, using different evolutionary techniques such as particle swarm optimization (PSO), constraint factor inertia PSO (CFI-PSO), quantum PSO, artificial bee colony algorithm, and cuckoo search technique. Comparative study provides evidence that the proposed method, based on CFI-PSO, gives the best performance amongst the employed swarm-based techniques. Experimental results show the impact of the proposed method as compared to earlier reported techniques in terms of improved response in passband and sharper transition width. However, small reduction in stopband attenuation (A(s)) is observed within the allowable limit when compared to nonfractional design approaches.

关键词： abc algorithm CS algorithm evolutionary techniques (ETs) fractional derivative constraints (FDCs) PSO QPSO

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Implementation and comparative analysis of the optimisations produced by evolutionary algorithms for the parameter extraction of PSP MOSFET model

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INTERNATIONAL JOURNAL OF ELECTRONICS 2016年第5期103卷 794-806页

作者： Hadia, Sarman K. Thakker, R. A. Bhatt, Kirit R. Charotar Univ Sci & Technol VT Patel Dept Elect & Commun Changa Gujarat India Viswakarma Govt Engn Coll Elect & Commun Dept Chandkheda Gujarat India Sardar Vallabhbhai Patel Inst Technol Elect & Commun Dept Vasad Gujarat India

The study proposes an application of evolutionary algorithms, specifically an artificial bee colony (abc), variant abc and particle swarm optimisation (PSO), to extract the parameters of metal oxide semiconductor field effect transistor (MOSFET) model. These algorithms are applied for the MOSFET parameter extraction problem using a Pennsylvania surface potential model. MOSFET parameter extraction procedures involve reducing the error between measured and modelled data. This study shows that abc algorithm optimises the parameter values based on intelligent activities of honey bee swarms. Some modifications have also been applied to the basic abc algorithm. Particle swarm optimisation is a population-based stochastic optimisation method that is based on bird flocking activities. The performances of these algorithms are compared with respect to the quality of the solutions. The simulation results of this study show that the PSO algorithm performs better than the variant abc and basic abc algorithm for the parameter extraction of the MOSFET model;also the implementation of the abc algorithm is shown to be simpler than that of the PSO algorithm.

关键词： abc algorithm Evolutionary algorithm extraction strategy PSP model particle swarm optimisation abc variant algorithm parameter extraction

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Multi-objective economic optimization scheduling of CCHP micro-grid based on improved bee colony algorithm considering the selection of hybrid energy storage system

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ENERGY REPORTS 2021年 7卷 326-341页

作者： Shan, JiaNan Lu, RenXiang Shanghai DianJi Univ Business Sch Shanghai 201306 Peoples R China

By factoring into the model selection of a hybrid energy storage system, this paper established an economically optimized multi-objective dispatching model for a micro-grid of Combined Cooling Heating and Power (CCHP) based on an improved algorithm of Artificial Bee Colony (abc). To upgrade the single-objective model in previous studies, the optimization goal of the model is to minimize the daily power generation dispatching cost and daily environmental pollutant treatment cost of the micro-grid, and the improved algorithm of abc based on Beetle Antennae Search algorithm (BAS-abc) was used to obtain a solution. To achieve a better application of theoretical results, the paper studied the summer typical daily real power load data of a grid-connected CCHP micro-grid in a district of Shanghai, and simulated a multi-objective economical dispatching model under the condition of using the Time of Use (TOU) billing system. The result shows that the minimum cost derived from the solution of the optimized abc is lower than that from the traditional abc. Furthermore, when the objective function of the CCHP microgrid is the lowest power generation cost or the lowest environmental cost, the optimized results are contradictory: it is impossible to simultaneously achieve an optimal power generation cost and an optimal environmental cost. This indicates the multi-objective optimized dispatching approach has comprehensively balanced the economic efficiency and the environmental-friendliness of the system. (C) 2021 The Author(s). Published by Elsevier Ltd.

关键词： Micro-grid Technical and economic selection abc algorithm Multi-objective optimization Economic dispatch

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Design of variable elliptical filters with direct tunability in 2D domain

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MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING 2022年第2期33卷 367-400页

作者： Sreelekha, K. R. Bindiya, T. S. Natl Inst Technol Calicut Dept Elect & Commun Engn Calicut 673601 Kerala India

This paper proposes the design of transformation based two dimensional (2D) elliptical filters using multi-objective artificial bee colony (MOabc) algorithm. The MOabc algorithm finds the one dimensional (1D) cut-off frequencies and McClellan transformation coefficients by optimizing the contour approximation errors at pass-band and stop-band regions of elliptical filters. This design approach is compared with the state of the art approaches in terms of contour approximation error, pass-band ripple and stop-band attenuation to ensure the efficiency. It is seen that an efficient mapping of 1D filter to 2D filter is possible with minimum contour approximation error using the proposed approach. The second proposal in this paper is the design of low complexity variable bandwidth and variable orientation elliptical filters with direct 2D tunability. This is achieved by mapping the coefficients of different 2D filters into a 2D Farrow structure. The performance of the proposed variable elliptical filter is measured in terms of mean error, mean square error, root mean square error, pass-band ripple, stop-band attenuation and 2D cut-off frequencies. The main feature of the proposed 2D variable filter design lies in the considerable reduction in the number of multipliers when compared to the existing methods, which in turn reduces the resource utilization and power consumption.

关键词： 2D filters Elliptical filter McClellan transformation abc algorithm Farrow structure

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Optimised annual performance of hybrid solar energy MED-TVC desalination plants with and without preheating

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INTERNATIONAL JOURNAL OF EXERGY 2020年第2期33卷 214-230页

作者： Beyralvand, Davood Yaghoubi, Mahmood Shiraz Univ Sch Mech Engn Mollasadra Ave Shiraz *** Iran

In the current study, energy, exergy, economic and environmental (4E) analysis for a multi-effect desalination plant with and without feed brine preheater integrated with a steam boiler and solar hybrid system for three coastal cities of southern Iran during a year is investigated. Four main configurations of hybrid/MED-TVC, hybrid/***, boiler/MED-TVC and boiler/*** are considered. By using artificial bee colony algorithm, systems were optimised. The results show that: using feed brine preheater, the unit cost reduced by 6.5% for the system with a boiler and 3.8% for the hybrid system.

关键词： solar energy MED-TVCFH CO2 emission abc algorithm 4E analysis

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Application of artificial bee colony algorithm for inverse modelling of a solar collector

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INVERSE PROBLEMS IN SCIENCE AND ENGINEERING 2017年第6期25卷 887-908页

作者： Das, Ranjan Akay, Bahriye Singla, Rohit K. Singh, Kuljeet Indian Inst Technol Ropar Dept Mech Engn Rupnagar India Erciyes Univ Dept Comp Engn Kayseri Turkey

This paper deals with the inverse analysis of a double-glazed flat-plate solar collector using the artificial bee colony (abc) optimization algorithm. In domestic water heating, both low and high heat output from the solar collector is undesirable, so the solar collector is required to supply the hot water at a particular temperature only, which in turn requires a given distribution of heat loss factor. With this criterion, the present analysis is aimed at predicting feasible dimensions and configurations of a solar collector satisfying a prescribed distribution of heat loss factor using abc algorithm. It is observed that many feasible alternatives of unknowns exist which satisfy a prescribed requirement, and using the abc algorithm, the size of the solar collector can be minimised by 6-32% with reference to the existing records. The effects of changing ambient conditions are also studied. Furthermore, a comparative study of the abc algorithm against other heuristic algorithms reveals its suitability and efficacy for the present estimation problem.

关键词： abc algorithm flat-plate solar collector inverse analysis sensitivity coefficients measurement error

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Comparative analysis of Mabc with KNN, SOM, and ACO algorithms for ECG heartbeat classification

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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2018年第6期26卷 2819-2830页

作者： Dilmac, Selim Dokur, Zumray Olmez, Tamer Istanbul Tech Univ Fac Elect & Elect Engn Dept Elect & Commun Engn Istanbul Turkey

In this paper, we proposed a classification method based on a nature-inspired algorithm, i.e., modified artificial bee colony (Mabc). This method was applied to electrocardiogram (ECG) heartbeat classification. ECG data was obtained from MITBIH database. Eight different types of heartbeats (N, j, V, F, f, A, a, and R) were analyzed. For a better classification result, both time domain and frequency domain features were used. Feature selection was done by divergence analysis. Mabc classification accuracy and heartbeat sensitivity values were compared with the results of other methods. Among other classifiers, k-nearest neighbor (KNN), Kohonen's self-organizing map (SOM), and ant colony optimization (ACO) were the best performing ones, and therefore their results are presented. The Mabc classifier achieved 97.18% accuracy on the analyzed dataset, as well as high sensitivity values for heartbeat types.

关键词： ECG heartbeat data classification abc algorithm nature-inspired

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Pilot Tones Optimization Using Artificial Bee Colony algorithm for MIMO-OFDM Systems

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WIRELESS PERSONAL COMMUNICATIONS 2013年第1期71卷 151-163页

作者： Seyman, Muhammet Nuri Taspinar, Necmi Kirikkale Univ Dept Elect Commun TR-71450 Kirikkale Turkey Erciyes Univ Dept Elect & Elect Engn TR-38039 Kayseri Turkey

How to design the pilot tones that are used in channel estimation has a significant effect on the estimation performance. To achieve good performance in least square (LS) algorithm, we propose the artificial bee colony (abc) algorithm for optimizing the placement of pilot tones in MIMO-OFDM systems. We also derive the upper bound of mean square error of LS estimation with the help of Gerschgorin disc theorem for fitness function of abc algorithm. The results show that designing pilot tones using the abc algorithm outperforms other considered placement strategies in terms of high system performance and low computational complexity.

关键词： MIMO-OFDM Channel estimation abc algorithm LS algorithm

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