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Journal articles on the topic 'BFOA'

Author: Grafiati

Published: 11 September 2023

Last updated: 25 July 2025

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1

Lenin, K. "ACTUAL POWER LOSS REDUCTION BY AUGMENTED PARTICLE SWARM OPTIMIZATION ALGORITHM." International Journal of Research -GRANTHAALAYAH 6, no. 9 (2018): 212–19. http://dx.doi.org/10.29121/granthaalayah.v6.i9.2018.1222.

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This paper presents an advanced particle swarm optimization Algorithm for solving the reactive power problem in power system. Bacterial Foraging Optimization Algorithm (BFOA) has recently emerged as a very powerful technique for real parameter optimization. In order to overcome the delay in optimization and to further enhance the performance of BFO, this paper proposed a new hybrid algorithm combining the features of BFOA and Particle Swarm Optimization (PSO) called advanced bacterial foraging-oriented particle swarm optimization (ABFPSO) algorithm for solving reactive power problem. The simul

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Dr., K. Lenin. "ACTUAL POWER LOSS REDUCTION BY AUGMENTED PARTICLE SWARM OPTIMIZATION ALGORITHM." International Journal of Research - Granthaalayah 6, no. 9 (2018): 212–19. https://doi.org/10.5281/zenodo.1442419.

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This paper presents an advanced particle swarm optimization Algorithm for solving the reactive power problem in power system. Bacterial Foraging Optimization Algorithm (BFOA) has recently emerged as a very powerful technique for real parameter optimization. In order to overcome the delay in optimization and to further enhance the performance of BFO, this paper proposed a new hybrid algorithm combining the features of BFOA and Particle Swarm Optimization (PSO) called advanced bacterial foraging-oriented particle swarm optimization (ABFPSO) algorithm for solving reactive power problem. The simul

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3

Ernesto, Rios-Willars, and Reyes-Acosta Alfredo Valentin. "Exploring the Effects of Attraction and Repulsion Parameters on the Bacterial Foraging Algorithm through Benchmark Functions." WSEAS TRANSACTIONS ON COMPUTER RESEARCH 12 (October 25, 2023): 62–74. http://dx.doi.org/10.37394/232018.2024.12.5.

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Metaheuristics are essential when working with complex problems from different fields. However, a suitable tuning scheme for these parameters is necessary to facilitate the search for potential solutions. This tuning is a challenging task. This work aims to develop a tuning method for the BFOA algorithm regarding attraction and repulsion values. In some cases, the parameter values are taken from previous works, while in other cases, the parametrization scheme comes from an automated or dynamic process. This work explores the Bacterial Foraging Algorithm (BFOA) within its parameters related to

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Wang, Xingzhong, Xinghua Kou, Jinfeng Huang, and Xianchun Tan. "A Collision Avoidance Method for Intelligent Ship Based on the Improved Bacterial Foraging Optimization Algorithm." Journal of Robotics 2021 (February 9, 2021): 1–10. http://dx.doi.org/10.1155/2021/6661986.

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The bacterial foraging optimization algorithm (BFOA) is an intelligent population optimization algorithm widely used in collision avoidance problems; however, the BFOA is inappropriate for the intelligent ship collision avoidance planning with high safety requirements because BFOA converges slowly, optimizes inaccurately, and has low stability. To fix the above shortcomings of BFOA, an autonomous collision avoidance algorithm based on the improved bacterial foraging optimization algorithm (IBFOA) is demonstrated in this paper. An adaptive diminishing fractal dimension chemotactic step length i

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Zambrano Zambrano, Dannyll Michellc, Darío Vélez, Yohanna Daza, and José Manuel Palomares. "Parametric Analysis of BFOA for Minimization Problems Using a Benchmark Function." Enfoque UTE 10, no. 3 (2019): 67–80. http://dx.doi.org/10.29019/enfoque.v10n3.490.

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This paper presents the social foraging behavior of Escherichia coli (E. Coli) bacteria based on Bacteria Foraging Optimization algorithms (BFOA) to find optimization and distributed control values. The search strategy for E. coli is very complex to express and the dynamics of the simulated chemotaxis stage in BFOA is analyzed with the help of a simple mathematical model. The methodology starts from a detailed analysis of the parameters of bacterial swimming and tumbling (C) and the probability of elimination and dispersion (Ped), then an adaptive variant of BFOA is proposed, in which the size

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Ibrahim, K. Mohammed, and I. Abdulla Abdulla. "Balancing a Segway robot using LQR controller based on genetic and bacteria foraging optimization algorithms." TELKOMNIKA Telecommunication, Computing, Electronics and Control 18, no. 5 (2020): 2642~2653. https://doi.org/10.12928/TELKOMNIKA.v18i5.14717.

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A two-wheeled single seat Segway robot is a special kind of wheeled mobile robot, using it as a human transporter system needs applying a robust control system to overcome its inherent unstable problem. The mathematical model of the system dynamics is derived and then state space formulation for the system is presented to enable design state feedback controller scheme. In this research, an optimal control system based on linear quadratic regulator (LQR) technique is proposed to stabilize the mobile robot. The LQR controller is designed to control the position and yaw rotation of the two-wheele

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Hernández-Ocaña, Betania, José Hernández-Torruco, Oscar Chávez-Bosquez, Maria Calva-Yáñez, and Edgar Portilla-Flores. "Bacterial Foraging-Based Algorithm for Optimizing the Power Generation of an Isolated Microgrid." Applied Sciences 9, no. 6 (2019): 1261. http://dx.doi.org/10.3390/app9061261.

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An Isolated Microgrid (IMG) is an electrical distribution network combined with modern information technologies aiming at reducing costs and pollution to the environment. In this article, we implement the Bacterial Foraging Optimization Algorithm (BFOA) to optimize an IMG model, which includes renewable energy sources, such as wind and solar, as well as a conventional generation unit based on diesel fuel. Two novel versions of the BFOA were implemented and tested: Two-Swim Modified BFOA (TS-MBFOA), and Normalized TS-MBFOA (NTS-MBFOA). In a first experiment, the TS-MBFOA parameters were calibra

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Alhasnawi, Bilal Naji, Basil H. Jasim, Ali M. Jasim, et al. "A Multi-Objective Improved Cockroach Swarm Algorithm Approach for Apartment Energy Management Systems." Information 14, no. 10 (2023): 521. http://dx.doi.org/10.3390/info14100521.

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The electrical demand and generation in power systems is currently the biggest source of uncertainty for an electricity provider. For a dependable and financially advantageous electricity system, demand response (DR) success as a result of household appliance energy management has attracted significant attention. Due to fluctuating electricity rates and usage trends, determining the best schedule for apartment appliances can be difficult. As a result of this context, the Improved Cockroach Swarm Optimization Algorithm (ICSOA) is combined with the Innovative Apartments Appliance Scheduling (IAA

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Teja, Venigalla Sai, Chilakapati Srinivas, and P. Radhika. "Plant Disease Detection and Classification Using Bacteria Foraging Optimization Algorithm Through Convolution Neural Network." Journal of Computational and Theoretical Nanoscience 17, no. 8 (2020): 3567–76. http://dx.doi.org/10.1166/jctn.2020.9233.

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Humans can recognize the plants infected by diseases but separated from our visual perception it is hard to recognize plant diseases. In croplands without taking the right care and prompt action, the entire field may become a region afflicted by diseases. So we identify the plant diseases ahead of time with the assistance of present-day computer technologies. An advanced model was introduced to accurately recognize and classification plant diseases. Here we proposed an approach that can use the Convolutional Neural Network (CNN) based on BFOA for distinguishing diseases in plants. The input pi

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Intan, Azmira Wan Abdul Razak, Zainal Abidin Izham, Keem Siah Yap, et al. "An Hour Ahead Electricity Price Forecasting with Least Square Support Vector Machine and Bacterial Foraging Optimization Algorithm." Indonesian Journal of Electrical Engineering and Computer Science 10, no. 2 (2018): 748–55. https://doi.org/10.11591/ijeecs.v10.i2.pp748-755.

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Predicting electricity price has now become an important task in power system operation and planning. An hour-ahead forecast provides market participants with the pre-dispatch prices for the next hour. It is beneficial for an active bidding strategy where amount of bids can be reviewed or modified before delivery hours. However, only a few studies have been conducted in the field of hour-ahead forecasting. This is due to most power markets apply two-settlement market structure (day-ahead and real time) or standard market design rather than single-settlement system (real time). Therefore, a hyb

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Sodsri, Parichart, Bongkoj Sookananta, and Mongkol Pusayatanont. "Optimal Placement of Distributed Generation Using Bacterial Foraging Optimization Algorithm." Applied Mechanics and Materials 781 (August 2015): 329–32. http://dx.doi.org/10.4028/www.scientific.net/amm.781.329.

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This paper presents the determination of the optimal distributed generation (DG) placement using bacterial foraging optimization algorithm (BFOA). The BFO mimics the seeking-nutrient behavior of the E. coli bacteria. It is utilized here to find the location and size of the DG installation in radial distribution system in order to obtain minimum system losses. The operation constraints include bus voltage limits, distribution line thermal limits, system power balance and generation power limits. The algorithm is tested on the IEEE 33 bus system. The result shows that the algorithm could be used

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Zaini, Farah Anishah, Mohamad Fani Sulaima, Intan Azmira Wan Abdul Razak, Mohammad Lutfi Othman, and Hazlie Mokhlis. "Improved Bacterial Foraging Optimization Algorithm with Machine Learning-Driven Short-Term Electricity Load Forecasting: A Case Study in Peninsular Malaysia." Algorithms 17, no. 11 (2024): 510. http://dx.doi.org/10.3390/a17110510.

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Accurate electricity demand forecasting is crucial for ensuring the sustainability and reliability of power systems. Least square support vector machines (LSSVM) are well suited to handle complex non-linear power load series. However, the less optimal regularization parameter and the Gaussian kernel function in the LSSVM model have contributed to flawed forecasting accuracy and random generalization ability. Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improv

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Abdul Razak, Intan Azmira Wan, Izham Zainal Abidin, Yap Keem Siah, et al. "An Hour Ahead Electricity Price Forecasting with Least Square Support Vector Machine and Bacterial Foraging Optimization Algorithm." Indonesian Journal of Electrical Engineering and Computer Science 10, no. 2 (2018): 748. http://dx.doi.org/10.11591/ijeecs.v10.i2.pp748-755.

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<span lang="EN-US">Predicting electricity price has now become an important task in power system operation and planning. An hour-ahead forecast provides market participants with the pre-dispatch prices for the next hour. It is beneficial for an active bidding strategy where amount of bids can be reviewed or modified before delivery hours. However, only a few studies have been conducted in the field of hour-ahead forecasting. This is due to most power markets apply two-settlement market structure (day-ahead and real time) or standard market design rather than single-settlement system (rea

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14

Zheng, S., A. N. Jiang, X. R. Yang, and G. C. Luo. "A New Reliability Rock Mass Classification Method Based on Least Squares Support Vector Machine Optimized by Bacterial Foraging Optimization Algorithm." Advances in Civil Engineering 2020 (August 17, 2020): 1–13. http://dx.doi.org/10.1155/2020/3897215.

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Classification of the surrounding rock is the basis of tunnel design and construction. However, conventional classification methods do not allow dynamic tunnel construction adjustments because they are time-consuming and do not consider the randomness of rock mass. This paper presents a new reliability rock mass classification method based on a least squares support vector machine (LSSVM) optimized by a bacterial foraging optimization algorithm (BFOA). The LSSVM is adopted to express the implicit relationship between classification indicators and rock mass grades, which is a response surface f

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Elsisi, M., M. Soliman, M. A. S. Aboelela, and W. Mansour. "ABC Based Design of PID Controller for Two Area Load Frequency Control with Nonlinearities." TELKOMNIKA Indonesian Journal of Electrical Engineering 16, no. 1 (2015): 58. http://dx.doi.org/10.11591/tijee.v16i1.1588.

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This paper presents an application of the Artificial Bee Colony (ABC) to optimize the parameters of Proportional-Integral-Derivative controller (PID) of nonlinear Load Frequency Controller (LFC) for a power system. A two area non reheat thermal system is equipped with PID controller. ABC is employed to search for optimal controller parameters to minimize the time domain objective function. The performance of the proposed technique has been evaluated with the performance of the conventional Ziegler Nichols (ZN) , Genetic Algorithm (GA) and Bacterial Foraging Optimization Algorithm (BFOA) in ord

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16

Zhu, Yuanyuan, Shijie Su, Yuchen Qian, Yun Chen, and Wenxian Tang. "Parameter Optimization for Ship Antiroll Gyros." Applied Sciences 10, no. 2 (2020): 661. http://dx.doi.org/10.3390/app10020661.

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Ship antiroll gyros are a type of equipment used to reduce ships’ roll angle, and their parameters are related to the parameters of a ship and wave, which affect gyro performance. As an alternative framework, we designed a calculation method for roll reduction rate and considered random waves to establish a gyro parameter optimization model, and we then solved it through the bacteria foraging optimization algorithm (BFOA) and pattern search optimization algorithm (PSOA) to obtain optimal parameter values. Results revealed that the two methods could effectively reduce the overall mass and floor

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Miglani, Sonia, and Kavita Kathuria. "A Review on Energy Efficiency in WSN Using BFOA." International Journal of Scientific Engineering and Research 3, no. 8 (2015): 103–5. https://doi.org/10.70729/30071502.

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Yang, Jiali, Yanxia Shen, and Yongqiang Tan. "Parameter Compensation for the Predictive Control System of a Permanent Magnet Synchronous Motor Based on Bacterial Foraging Optimization Algorithm." World Electric Vehicle Journal 15, no. 1 (2024): 23. http://dx.doi.org/10.3390/wevj15010023.

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The accurate identification of permanent magnet synchronous motor (PMSM) parameters is the foundation for high-performance driving in predictive control systems. The traditional PMSM multi-parameter identification method suffers from insufficient rank of the identification equation and is prone to getting stuck in local optimal solutions. This article combines the bacterial foraging optimization algorithm (BFOA) to establish a built-in PMSM predictive control parameter compensation model. Firstly, we analyzed the reasons why the distortion of PMSM motor parameters affects the actual speed and

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19

Yongqiang, Bao, Xi Ji, and Xu Haiyan. "Practical Speech Emotion Recognition Based on Im-BFOA." Journal of Applied Sciences 13, no. 22 (2013): 5349–55. http://dx.doi.org/10.3923/jas.2013.5349.5355.

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20

Benmachiche, A., A. Makhlouf, and T. Bouhadada. "Optimization learning of hidden Markov model using the bacterial foraging optimization algorithm for speech recognition." International Journal of Knowledge-based and Intelligent Engineering Systems 24, no. 3 (2020): 171–81. http://dx.doi.org/10.3233/kes-200039.

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Nowadays, the speech recognition applications can be found in several activities, and their existence as a field of study and research lasts for a long time. Although, many studies deal with different problems, in security-related areas, biometric identification, access to the Smartphone… Etc. In automatic speech recognition (ASR) systems, hidden Markov models (HMMs) have widely used for modeling the temporal speech signal. In order to optimize HMM parameters (i.e., observation and transition probabilities), iterative algorithms commonly used such as Forward-Backward or Baum-Welch. In this art

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Ju, Hae-ji, and Soo-kyung Jeon. "Effect of Ultrasound Irradiation on the Properties and Sulfur Contents of Blended Very Low-Sulfur Fuel Oil (VLSFO)." Journal of Marine Science and Engineering 10, no. 7 (2022): 980. http://dx.doi.org/10.3390/jmse10070980.

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Quality issues concerning very low-sulfur fuel oil (VLSFO) have increased significantly since the IMO sulfur-limit regulation became mandatory in 2020, as most VLSFO is produced by blending high-sulfur fuel oil (HSFO) with VLSFO. For instance, the conversion of VLSFO paraffins (C19 or higher alkanes) into waxes at low temperatures adversely affects cold flow properties. This study investigates the effects of ultrasonication on the chemical composition, dispersion stability, and sulfur content of samples prepared by blending ISO-F-DMA-grade marine gas oil (i.e., VLSFO) and ISO-F-RMG-grade marin

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Srinivasulu, G., B. Subramanyam, and Surya Kalavathi M. "Transmission Expansion Planning Using Bacterial Foraging Optimization Algorithm (BFOA)." i-manager's Journal on Power Systems Engineering 2, no. 2 (2014): 9–15. http://dx.doi.org/10.26634/jps.2.2.2928.

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Sri Krishna Sarath, P., and I. Swetha Monica. "Application of BFOA in Two Area Load Frequency Control." International Journal of Engineering & Technology 7, no. 3.31 (2018): 50. http://dx.doi.org/10.14419/ijet.v7i3.31.18200.

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This paper presents Bacterial foraging optimization algorithm which is based on food searching process of Escherichia coli bacteria, which is gaining popularity due to its effectiveness and providing solution to real world optimization problems .BFOA is applied to control the parameter optimization of load frequency controller for tuning the parameters of the proportional integral and derivative controller. A simple two area system with thermal-thermal generating units is considered for simulation study which is controlled with PID controller. The main objective of this work is to design the c

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Barisal, Ajit Kumar, and Deepak Kumar Lal. "Application of Moth Flame Optimization Algorithm for AGC of Multi-Area Interconnected Power Systems." International Journal of Energy Optimization and Engineering 7, no. 1 (2018): 22–49. http://dx.doi.org/10.4018/ijeoe.2018010102.

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A novel attempt has been made to use Moth Flame Optimization (MFO) algorithm to optimize PI/PID controller parameters for AGC of power system. Four different power systems are considered in the present article. Initially, a two area thermal power system is considered for simulation. The superiority of the proposed MFO optimized PI/PID controller has been demonstrated by comparing the results with recently published approaches such as conventional, GA, BFOA, DE, PSO, Hybrid BFOA-PSO, FA and GWO algorithm optimized PI/PID controller for the same power system model. Then, a sensitivity analysis i

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Sahoo, Dillip Kumar, Rabindra Kumar Sahu, and Sidharth Panda. "Fractional Order Fuzzy PID Controller for Automatic Generation Control of Power Systems." ECTI Transactions on Electrical Engineering, Electronics, and Communications 19, no. 1 (2021): 71. http://dx.doi.org/10.37936/ecti-eec.2021191.222284.

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In this study, a Hybrid Adaptive Differential Evolution and Pattern Search (hADE-PS) tuned Fractional Order Fuzzy PID (FOFPID) structure is suggested for AGC of power systems. At first, a non-reheat type two-area thermal system is considered and the improvement of the proposed approach over Bacteria Foraging Optimization Algorithm (BFOA), Teaching Learning Based Optimization (TLBO), Jaya Algorithm (JA), Genetic Algorithm (GA) and Hybrid BFOA and Particle Swarm Optimization Algorithm (hBFOA-PSO) for the identical test systems has been demonstrated. The analysis was then extended to interconnect

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Kumari, G. Vimala, G. Sasibhushana Rao, and B. Prabhakara Rao. "NEW BACTERIA FORAGING AND PARTICLE SWARM HYBRID ALGORITHM FOR MEDICAL IMAGE COMPRESSION." Image Analysis & Stereology 37, no. 3 (2018): 249. http://dx.doi.org/10.5566/ias.1865.

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For perfect diagnosis of brain tumour, it is necessary to identify tumour affected regions in the brain in MRI (Magnetic Resonance Imaging) images effectively and compression of these images for transmission over a communication channel at high speed with better visual quality to the experts. An attempt has been made in this paper for identifying tumour regions with optimal thresholds which are optimized with the proposed Hybrid Bacteria Foraging Optimization Algorithm (BFOA) and Particle Swarm Optimization (PSO) named (HBFOA-PSO) by maximizing the Renyi’s entropy and Kapur’s entropy. BFOA may

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Kaur, Mandeep, and Sanjay Kadam. "Bio-Inspired Workflow Scheduling on HPC Platforms." Tehnički glasnik 15, no. 1 (2021): 60–68. http://dx.doi.org/10.31803/tg-20210204183323.

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Efficient scheduling of tasks in workflows of cloud or grid applications is a key to achieving better utilization of resources as well as timely completion of the user jobs. Many scientific applications comprise several tasks that are dependent in nature and are specified by workflow graphs. The aim of the cloud meta-scheduler is to schedule the user application tasks (and the applications) so as to optimize the resource utilization and to execute the user applications in minimum amount of time. During the past decade, there have been several attempts to use bio-inspired scheduling algorithms

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Hernández-Ocaña, Betania, Ma Del Pilar Pozos-Parra, Efrén Mezura-Montes, Edgar Alfredo Portilla-Flores, Eduardo Vega-Alvarado, and Maria Bárbara Calva-Yáñez. "Two-Swim Operators in the Modified Bacterial Foraging Algorithm for the Optimal Synthesis of Four-Bar Mechanisms." Computational Intelligence and Neuroscience 2016 (2016): 1–18. http://dx.doi.org/10.1155/2016/4525294.

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This paper presents two-swim operators to be added to the chemotaxis process of the modified bacterial foraging optimization algorithm to solve three instances of the synthesis of four-bar planar mechanisms. One swim favors exploration while the second one promotes fine movements in the neighborhood of each bacterium. The combined effect of the new operators looks to increase the production of better solutions during the search. As a consequence, the ability of the algorithm to escape from local optimum solutions is enhanced. The algorithm is tested through four experiments and its results are

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Nayak, Smrutiranjan, Sanjeeb Kumar Kar, and Subhransu Sekhar Dash. "Optimized CFPID controller for SCiWOA in allocated grid." Journal of Statistics & Management Systems 26, no. 1 (2023): 241–47. http://dx.doi.org/10.47974/jsms-973.

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In persistently expanding region and construction of current power system having trouble request vulnerabilities, the utilization of proficient and lively recurrence power methodology is fundamental for palatable working of Power-System. In this examination, a CFPID regulator is recommended for regularity management of Power-System. To upgrade the regulator boundaries, a Sine Cosine enhanced Whale-Optimization-Algorithm is used. It’s first benefits of the SCiWOA changed CFPID regulator over hPSO-PS changed Fuzzy-PI regulator, hybrid-BFOA PSO changed PI regulator, GA changed PI regulator, BFOA

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Xin, Fengming, Mingfeng Zhang, Jing Li, and Chen Luo. "Phase Retrieval for Radar Constant–Modulus Signal Design Based on the Bacterial Foraging Optimization Algorithm." Electronics 13, no. 3 (2024): 506. http://dx.doi.org/10.3390/electronics13030506.

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Optimizing the energy spectrum density (ESD) of a transmitted waveform can improve radar performance. The design of a time–domain constant–modulus signal corresponding to the transmitted waveform ESD is practically important because constant–modulus signals can maximize transmission power and meet the hardware requirements of radar transmitters. Here, we present a time–domain signal design under dual constraints of energy and constant modulus. The mutual information (MI)–based waveform design method is used to design transmitted waveform ESD under the energy constraint. Then, the bacterial for

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Hassan, Elia Erwani, Titik Khawa Abdul Rahman, Zuhaina Zakaria, and Nazrulazhar Bahaman. "The Improved of BFOA for Ensuring the Sustainable Economic Dispatch." Applied Mechanics and Materials 785 (August 2015): 83–87. http://dx.doi.org/10.4028/www.scientific.net/amm.785.83.

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This paper introduced a new heuristic method the Improved to Bacterial Foraging Optimization Algorithm or IBFO to provide minimize objective functions in Secured Environmental Economic Dispatch (SEED) problems. An optimization problem may involve the highly non linear, non convex and non differentiable tends the solutions observed from a multiple local minima. The limitation faced by conventional methods are being trapped at any this local minima and prevent to reach the global minima. For that reason, this approach IBFO is tested under IEEE 118 bus system to obtain the minimum total cost func

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Kumar, Rajeev, Sourav Diwania, Pavan Khetrapal, Sheetal Singh, and Manoj Badoni. "Multimachine stability enhancement with hybrid PSO-BFOA based PV-STATCOM." Sustainable Computing: Informatics and Systems 32 (December 2021): 100615. http://dx.doi.org/10.1016/j.suscom.2021.100615.

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CH. VENKATESWARA, RAO, S. S. TULSIRAM, B. BRAHMAIAH, and CH RAMYA. "FEATURES OF PSO - BFOA BASED INCREMENT CONDUCTANCE METHOD WITH FPGA." i-manager's Journal on Circuits and Systems 7, no. 1 (2019): 14. http://dx.doi.org/10.26634/jcir.7.1.15391.

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Zhang, Jiangjiang, Zhihua Cui, Yechuang Wang, et al. "A Coupling Approach With GSO-BFOA for Many-Objective Optimization." IEEE Access 7 (2019): 120248–61. http://dx.doi.org/10.1109/access.2019.2937538.

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Manoharan, Neelamegam, Subhransu Sekhar Dash, Kurup Sathy Rajesh, and Sidhartha Panda. "Automatic Generation Control by Hybrid Invasive Weed Optimization and Pattern Search Tuned 2-DOF PID Controller." International Journal of Computers Communications & Control 12, no. 4 (2017): 533. http://dx.doi.org/10.15837/ijccc.2017.4.2751.

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A hybrid invasive weed optimization and pattern search (hIWO-PS) technique is proposed in this paper to design 2 degree of freedom proportionalintegral- derivative (2-DOF-PID) controllers for automatic generation control (AGC) of interconnected power systems. Firstly, the proposed approach is tested in an interconnected two-area thermal power system and the advantage of the proposed approach has been established by comparing the results with recently published methods like conventional Ziegler Nichols (ZN), differential evolution (DE), bacteria foraging optimization algorithm (BFOA), genetic a

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Motiram, Pawar Shalikram, and Subhash Shankar Zope. "Optimum Load Frequency Control in Power System using BFOA and CA." International Journal of Innovations in Engineering and Science 6, no. 11 (2021): 8. http://dx.doi.org/10.46335/ijies.2021.6.11.3.

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Nair, S. Anu H., and P. Aruna. "Comparison of DCT, SVD and BFOA based multimodal biometric watermarking systems." Alexandria Engineering Journal 54, no. 4 (2015): 1161–74. http://dx.doi.org/10.1016/j.aej.2015.07.002.

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Kumar, Vineet. "Enhancing Transient Stability in Multimachine Power Systems Using PV-STATCOM with PSO-BFOA Optimization." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem49967.

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Abstract - The integration of photovoltaic (PV) systems into multimachine power systems presents significant challenges to transient stability due to their intermittent nature and lack of inherent inertia. This study proposes the use of a PV-STATCOM system, combining PV generation with Static Synchronous Compensator (STATCOM) functionality, to enhance stability in Kundur’s two-area multimachine power system. The PV-STATCOM controller parameters are optimized using a hybrid Particle Swarm Optimization with Bacterial Foraging Optimization Algorithm (PSO-BFOA). Simulations conducted in MATLAB/Sim

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Kumar, Amandeep, Vishal Kumar Goar, Manoj Kuri, and Mohit Srivastava. "Directional antenna with reproduction optimisation (BFOA) used in mobile ad-hoc network." International Journal of Mobile Network Design and Innovation 10, no. 3 (2022): 141. http://dx.doi.org/10.1504/ijmndi.2022.10051468.

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Kuri, Manoj, Mohit Srivastava, Vishal Kumar Goar, and Amandeep Kumar. "Directional antenna with reproduction optimisation (BFOA) used in mobile ad-hoc network." International Journal of Mobile Network Design and Innovation 10, no. 3 (2022): 141. http://dx.doi.org/10.1504/ijmndi.2022.126449.

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Gupta, Prateek, and Ajay K. Sharma. "Designing of energy efficient stable clustering protocols based on BFOA for WSNs." Journal of Ambient Intelligence and Humanized Computing 10, no. 2 (2018): 681–700. http://dx.doi.org/10.1007/s12652-018-0719-1.

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Jutharee, Wisanu, Boonserm Kaewkamnerdpong, and Thavida Maneewarn. "Joint Reconfiguration after Failure for Performing Emblematic Gestures in Humanoid Receptionist Robot." Sensors 23, no. 22 (2023): 9277. http://dx.doi.org/10.3390/s23229277.

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This study proposed a strategy for a quick fault recovery response when an actuator failure problem occurred while a humanoid robot with 7-DOF anthropomorphic arms was performing a task with upper body motion. The objective of this study was to develop an algorithm for joint reconfiguration of the receptionist robot called Namo so that the robot can still perform a set of emblematic gestures if an actuator fails or is damaged. We proposed a gesture similarity measurement to be used as an objective function and used bio-inspired artificial intelligence methods, including a genetic algorithm, a

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Awais, Muhammad, Nadeem Javaid, Khursheed Aurangzeb, Syed Haider, Zahoor Khan, and Danish Mahmood. "Towards Effective and Efficient Energy Management of Single Home and a Smart Community Exploiting Heuristic Optimization Algorithms with Critical Peak and Real-Time Pricing Tariffs in Smart Grids." Energies 11, no. 11 (2018): 3125. http://dx.doi.org/10.3390/en11113125.

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Nowadays, automated appliances are exponentially increasing. Therefore, there is a need for a scheme to accomplish the electricity demand of automated appliances. Recently, many Demand Side Management (DSM) schemes have been explored to alleviate Electricity Cost (EC) and Peak to Average Ratio (PAR). In this paper, energy consumption problem in a residential area is considered. To solve this problem, a heuristic based DSM technique is proposed to minimize EC and PAR with affordable user’s Waiting Time (WT). In heuristic techniques: Bacterial Foraging Optimization Algorithm (BFOA) and Flower Po

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Pappachen, Abhijith, and A. Peer Fathima. "BFOA Based FOPID Controller for Multi Area AGC System with Capacitive Energy Storage." International Journal on Electrical Engineering and Informatics 7, no. 3 (2015): 429–42. http://dx.doi.org/10.15676/ijeei.2015.7.3.6.

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Nandakumar, E., R. Dhanasekaran, and N. K. Senapathi. "Real and Reactive Power Compensation Using UPFC by Bacterial Foraging Optimization Algorithm (BFOA)." Research Journal of Applied Sciences, Engineering and Technology 9, no. 11 (2015): 1027–33. http://dx.doi.org/10.19026/rjaset.9.2596.

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Ali, E. S., and S. M. Abd-Elazim. "Optimal SSSC Design for Damping Power Systems Oscillations via Hybrid BFOA-PSO Approach." JES. Journal of Engineering Sciences 41, no. 3 (2013): 1127–50. http://dx.doi.org/10.21608/jesaun.2013.114785.

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Roy, Kallol, Kamal Krishna Mandal, Atis Chandra Mandal, and Sankar Narayan Patra. "Analysis of energy management in micro grid – A hybrid BFOA and ANN approach." Renewable and Sustainable Energy Reviews 82 (February 2018): 4296–308. http://dx.doi.org/10.1016/j.rser.2017.07.037.

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Liang, Dong Ying, and Wei Kun Zheng. "An Intelligent Feature Selection Method Based on the Bacterial Foraging Algorithm." Applied Mechanics and Materials 50-51 (February 2011): 304–8. http://dx.doi.org/10.4028/www.scientific.net/amm.50-51.304.

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This paper puts forward an agent genetic algorithm based on bacteria foraging strategy (BFOA-L) as the feature selection method. The algorithm introduces the bacteria foraging (BF) behavior, and integrates the neural network and link agent structure to achieve fuzzy logic reasoning, so that the weights with no definite physical meaning in traditional neural network are endowed with the physical meaning of fuzzy logic reasoning parameters. The algorithm can maintain the diversity of the agent, so as to achieve satisfactory global optimization precision. The test result shows that this algorithm

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B. Venkata, Srikanth, and Lakshmi Devi Ai. "Saddle Node Bifurcation Point Analysis of Voltage Stability of IEEE 30-BUS Power System for Removal of Generation through Bacteria Foraging Optimization Algorithm." International Journal of Engineering & Technology 7, no. 3.31 (2018): 36. http://dx.doi.org/10.14419/ijet.v7i3.31.18196.

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This paper deals with the identification of instability nodes of IEEE 30 BUS power system to generation removal. Optimal sizing and locations of reactive power compensations are obtained. Firstly one of the generators is assumed to be removed from service and the saddle node bifurcation (SNB) point voltages are evaluated without reactive power compensation. Secondly two generators are assumed to be removed from service and the saddle node point voltage magnitudes are obtained without reactive power compensation. For both cases the study is conducted by placing optimal reactive power compensati

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Karuppiah, N., S. Muthubalaji, S. Ravivarman, Md Asif, and Abhishek Mandal. "Enhancing the performance of Transmission Lines by FACTS Devices using GSA and BFOA Algorithms." International Journal of Engineering & Technology 7, no. 4.6 (2018): 203. http://dx.doi.org/10.14419/ijet.v7i4.6.20463.

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Flexible Alternating Current Transmission System devices have numerous applications in electrical transmission lines like improvement of voltage stability, reactive power compensation, congestion management, Available Transfer Capacity enhancement, real power loss reduction, voltage profile improvement and much more. The effectiveness of these FACTS devices is enhanced by the placement of these devices in the transmission lines. The placement is based on transmission line sensitivity factors such as Bus voltage stability index and line voltage stability index. This research article focuses on

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