• Journal of Electrical Engineering and Technology
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• 제10권3호
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• pp.944-951
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• 2015

Pulse Width Modulation (PWM) techniques are increasingly employed for PWM inverter fed induction motor drive. Among various popular PWM methods used, Selective Harmonic Elimination PWM (SHEPWM) has been widely accepted for its better harmonic elimination capability. In addition, using SHEPWM, it is also possible to maintain better voltage regulation. Hence, in this paper, an attempt has been made to apply Bacterial Foraging Algorithm (BFA) for solving selective harmonic elimination problem. The problem of voltage harmonic elimination together with output voltage regulation is drafted as an optimization task and the solution is sought through proposed method. For performance comparison of BFA, the results obtained are compared with other techniques such as derivative based Newton-Raphson method, and Genetic Algorithm. From the comparison, it can be observed that BFA based approach yields better results. Further, it provides superior convergence, reduced computational burden, and guaranteed global optima. The simulation results are validated through experimental findings.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.569-570
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• 2007

본 논문에서는 대장균 먹이찾기(E. Coli Bacterial Foraging)를 최적화 기법에 도입한 사례로서 이를 이용하여 Nonconvex 배전용 경제급전 알고리즘(distribution economic dispatch: DED을 제안한다. 제안된 DED 알고리즘은 향후 지역이나 구역 발전사업자를 중심으로 배전계통운용시스템에 필요한 경제급전 알고리즘으로 활용 할 수 있다.

• ETRI Journal
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• 제40권6호
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• pp.726-735
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• 2018

Femtocells are good examples of the ultimate networking technology, offering enhanced indoor coverage and higher data rate. However, the dense deployment of femto base stations (FBSs) and the exploitation of subcarrier reuse between macrocell base stations and FBSs result in significant co-tier and cross-tier interference, thus degrading system performance. Therefore, appropriate resource allocations are required to mitigate the interference. This paper proposes a discrete bacterial foraging optimization (DBFO) algorithm to find the optimal resource allocation in two-tier networks. The simulation results showed that DBFO outperforms the random-resource allocation and discrete particle swarm optimization (DPSO) considering the small number of steps taken by particles and bacteria.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2007년도 춘계학술대회 학술발표 논문집 제17권 제1호
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• pp.241-244
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• 2007

본 논문에서는 박테리아의 주화성에 기초한 Bacteria Cooperative Optimization(BCO) 알고리즘을 소개한다. BCO는 Ant Colony Optimization (ACO)처럼 자연계에 존재하는 생명체의 행동양식을 모방하여 만든 최적화 알고리즘으로 크게 초기화, 측정, 행동결정, 이동으로 구성된다. 우리는 먼저 BCO 알고리즘을 설명하고 2차원 함수 최적화 문제를 이용하여 BCO알고리즘과 Genetic Algorithm(GA) 그리고 Bacterial Foraging for Distributed Optimization(BFO)의 성능 측정 결과를 기술한다. 실험 결과 BCO의 성능이 GA나 BFO보다 우수함을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권4호
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• pp.1437-1459
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• 2020

Wireless Sensor Networks (WSN) is a distributed Sensor network whose terminals are sensors that can sense and check the environment. Sensors are typically battery-powered and deployed in where the batteries are difficult to replace. Therefore, maximize the consumption of node energy and extend the network's life cycle are the problems that must to face. Low-energy adaptive clustering hierarchy (LEACH) protocol is an adaptive clustering topology algorithm, which can make the nodes in the network consume energy in a relatively balanced way and prolong the network lifetime. In this paper, the novel multi-objective LEACH protocol is proposed, in order to solve the proposed protocol, we design a multi-objective coupling algorithm based on bat algorithm (BA), glowworm swarm optimization algorithm (GSO) and bacterial foraging optimization algorithm (BFO). The advantages of BA, GSO and BFO are inherited in the multi-objective coupling algorithm (MBGF), which is tested on ZDT and SCH benchmarks, the results are shown the MBGF is superior. Then the multi-objective coupling algorithm is applied in the multi-objective LEACH protocol, experimental results show that the multi-objective LEACH protocol can greatly reduce the energy consumption of the node and prolong the network life cycle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권2호
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• pp.442-460
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• 2021

Nowadays, recommendation systems (RSs) are applied to all aspects of online life. In order to overcome the problem that individuals who do not meet the constraints need to be regenerated when the many-objective evolutionary algorithm (MaOEA) solves the hybrid recommendation model, this paper proposes a many-objective particle swarm optimization algorithm based on multiple criteria (MaPSO-MC). A generation-based fitness evaluation strategy with diversity enhancement (GBFE-DE) and ISDE⁺ are coupled to comprehensively evaluate individual performance. At the same time, according to the characteristics of the model, the regional optimization has an impact on the individual update, and a many-objective evolutionary strategy based on bacterial foraging (MaBF) is used to improve the algorithm search speed. Experimental results prove that this algorithm has excellent convergence and diversity, and can produce accurate, diverse, novel and high coverage recommendations when solving recommendation models.

• Journal of Electrical Engineering and Technology
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• 제11권6호
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• pp.1535-1547
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• 2016

This paper proposes various design procedures for computing Power System Ancillary Service Requirement Assessment Indices (PSASRAI) for a Two-Area Thermal Reheat Interconnected Power System (TATRIPS) in a restructured environment. In an interconnected power system, a sudden load perturbation in any area causes the deviation of frequencies of all the areas and also in the tie-line powers. This has to be corrected to ensure the generation and distribution of electric power companies to ensure good quality. A simple Proportional and Integral (PI) controllers have wide usages in controlling the Load Frequency Control (LFC) problems. So the design of the PI controller gains for the restructured power system are obtained using Bacterial Foraging Optimization (BFO) algorithm. From the simulation results, the PSASRAI are calculated based on the settling time and peak over shoot concept of control input deviations of each area for different possible transactions. These Indices are useful for system operator to prepare the power system restoration plans. Moreover, the LFC loop coordinated with Redox Flow Batteries (RFB) has greatly improved the dynamic response and it reduces the control input requirements and to ensure improved PSASRAI, thereby improving the system reliability.

• 한국ITS학회 논문지
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• 제22권6호
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• pp.182-195
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• 2023

최근 인공지능 알고리즘을 활용한 교통 신호 제어에 관한 관심 증대와 함께, 관련 모델구축 연구가 활발히 진행되고 있다. 그러나 대부분의 연구는 독립 교차로를 대상으로, 교통량 변화에 연동되는 신호 주기 산정을 위한 이론 전개가 주를 이루고 있다. 본 연구에서는 신호제어 알고리즘 구축을 위한 실증 분석을 통해, 신호운영과 회전교차 방식의 실제 교차로를 대상으로 분석을 진행하였다. 기존 연구에서 많이 활용되는 GA와 PSO 알고리즘을 개선한 PSO-BFO 알고리즘을 제시하여 두 교차로의 운영 효과 증진을 위한 신호제어 방안을 강구 하였다. 그 결과, 158초의 신호 주기하에 신호 교차로의 경우, 용량 증대 3.4%, 지체도 및 정지횟수 감소는 각각 8.2%, 8.3%의 효과가 발생하고, 회전교차로에서는 용량증대 9.2%, 지체도 및 정지횟수 감소가 각각 7.1%, 27.2%에 이르는 효과가 발생하는 것으로 나타났다.