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Articles de revues sur le sujet « BACTERIA FORAGING »

Auteur : Grafiati

Publié le 11 septembre 2023

Mis à jour le 25 juillet 2025

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1

Passino, Kevin M. "Bacterial Foraging Optimization." International Journal of Swarm Intelligence Research 1, no. 1 (2010): 1–16. http://dx.doi.org/10.4018/jsir.2010010101.

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The bacterial foraging optimization (BFO) algorithm mimics how bacteria forage over a landscape of nutrients to perform parallel nongradient optimization. In this article, the author provides a tutorial on BFO, including an overview of the biology of bacterial foraging and the pseudo-code that models this process. The algorithms features are briefly compared to those in genetic algorithms, other bio-inspired methods, and nongradient optimization. The applications and future directions of BFO are also presented.

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Panda, Rutuparna, and Manoj Kumar Naik. "A Crossover Bacterial Foraging Optimization Algorithm." Applied Computational Intelligence and Soft Computing 2012 (2012): 1–7. http://dx.doi.org/10.1155/2012/907853.

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This paper presents a modified bacterial foraging optimization algorithm called crossover bacterial foraging optimization algorithm, which inherits the crossover technique of genetic algorithm. This can be used for improvising the evaluation of optimal objective function values. The idea of using crossover mechanism is to search nearby locations by offspring (50 percent of bacteria), because they are randomly produced at different locations. In the traditional bacterial foraging optimization algorithm, search starts from the same locations (50 percent of bacteria are replicated) which is not d

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Kanagasabai, Lenin. "Diminution of factual power loss by enhanced bacterial foraging optimization algorithm." International Journal of Applied Power Engineering 9, no. 3 (2022): 245~249. https://doi.org/10.5281/zenodo.7353285.

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This paper presents an enhanced bacterial foraging optimization (EBFO) algorithm for solving the optimal reactive power problem. Bacterial foraging optimization is based on foraging behaviour of Escherichia coli bacteria which present in the human intestine. Bacteria have inclination to congregate the nutrient-rich areas by an action called as Chemo taxis. The bacterial foraging process consists of four chronological methods i.e. chemo taxis, swarming and reproduction and elimination-dispersal. In this work rotation angle adaptively and incessantly modernized, which augment the diversity of th

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Wei, Zhong-hua, Xia Zhao, Ke-wen Wang, and Yan Xiong. "Bus Dispatching Interval Optimization Based on Adaptive Bacteria Foraging Algorithm." Mathematical Problems in Engineering 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/389086.

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The improved bacterial foraging algorithm was applied in this paper to schedule the bus departing interval. Optimal interval can decrease the total operation cost and passengers’ mean waiting time. The principles of colony sensing, chemotactic action, and improved foraging strategy made this algorithm adaptive. Based on adaptive bacteria foraging algorithm (ABFA), a model on one bus line in Hohhot city in China was established and simulated. Two other algorithms, original bacteria foraging algorithm (BFA) and genetic algorithm (GA), were also used in this model to decide which one could greatl

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Lenin, Kanagasabai. "Diminution of factual power loss by enhanced bacterial foraging optimization algorithm." International Journal of Applied Power Engineering (IJAPE) 9, no. 3 (2020): 245. http://dx.doi.org/10.11591/ijape.v9.i3.pp245-249.

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<div data-canvas-width="126.37004132231402">This paper presents an enhanced bacterial foraging optimization (EBFO) algorithm for solving the optimal reactive power problem. Bacterial foraging optimization is based on foraging behaviour of <em>Escherichia coli</em> bacteria which present in the human intestine. Bacteria have inclination to congregate the nutrient-rich areas by an action called as Chemo taxis. The bacterial foraging process consists of four chronological methods i.e. chemo taxis, swarming and reproduction and elimination-dispersal. In this work rotation angle a

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Yan, Xiaohui, Yunlong Zhu, Hao Zhang, Hanning Chen, and Ben Niu. "An Adaptive Bacterial Foraging Optimization Algorithm with Lifecycle and Social Learning." Discrete Dynamics in Nature and Society 2012 (2012): 1–20. http://dx.doi.org/10.1155/2012/409478.

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Bacterial Foraging Algorithm (BFO) is a recently proposed swarm intelligence algorithm inspired by the foraging and chemotactic phenomenon of bacteria. However, its optimization ability is not so good compared with other classic algorithms as it has several shortages. This paper presents an improved BFO Algorithm. In the new algorithm, a lifecycle model of bacteria is founded. The bacteria could split, die, or migrate dynamically in the foraging processes, and population size varies as the algorithm runs. Social learning is also introduced so that the bacteria will tumble towards better direct

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Shen, Hai, and Mo Zhang. "Bacterial Foraging Optimization Algorithm with Quorum Sensing Mechanism." Applied Mechanics and Materials 556-562 (May 2014): 3844–48. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.3844.

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Quorum sensing is widely distributed in bacteria and make bacteria are similar to complex adaptive systems, with intelligent features such as emerging and non-linear, the ultimate expression of the adaptive to changes in the environment. Based on the phenomenon of bacterial quorum sensing and Bacterial Foraging Optimization Algorithm, some new optimization algorithms have been proposed. In this paper, it presents research situations, such as environment-dependent quorum sensing mechanism, quorum sensing mechanism with quantum behavior, cell-to-cell communication, multi-colony communication, de

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Yawata, Yutaka, Francesco Carrara, Filippo Menolascina, and Roman Stocker. "Constrained optimal foraging by marine bacterioplankton on particulate organic matter." Proceedings of the National Academy of Sciences 117, no. 41 (2020): 25571–79. http://dx.doi.org/10.1073/pnas.2012443117.

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Optimal foraging theory provides a framework to understand how organisms balance the benefits of harvesting resources within a patch with the sum of the metabolic, predation, and missed opportunity costs of foraging. Here, we show that, after accounting for the limited environmental information available to microorganisms, optimal foraging theory and, in particular, patch use theory also applies to the behavior of marine bacteria in particle seascapes. Combining modeling and experiments, we find that the marine bacteriumVibrio ordaliioptimizes nutrient uptake by rapidly switching between attac

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Nasir, Ahmad N. K., M. O. Tokhi, and N. Maniha Abd Ghani. "Novel Adaptive Bacteria Foraging Algorithms for Global Optimization." Applied Computational Intelligence and Soft Computing 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/494271.

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This paper presents improved versions of bacterial foraging algorithm (BFA). The chemotaxis feature of bacteria through random motion is an effective strategy for exploring the optimum point in a search area. The selection of small step size value in the bacteria motion leads to high accuracy in the solution but it offers slow convergence. On the contrary, defining a large step size in the motion provides faster convergence but the bacteria will be unable to locate the optimum point hence reducing the fitness accuracy. In order to overcome such problems, novel linear and nonlinear mathematical

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AMIT, D.PUROHIT, and S. T. KHANDARE PROF. "COLOR IMAGE SEGMENTATION TECHNIQUE USING COOPERATIVE BACTERIAL FORAGING ALGORITHM." JournalNX - A Multidisciplinary Peer Reviewed Journal 3, no. 5 (2017): 56–59. https://doi.org/10.5281/zenodo.1446386.

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 Image segmentation is a crucial and challenging problem in image processing and often a basic step for high level analysis. The intent of image segmentation is to divide an image into different classes based on features, such as color, intensity or histogram, where each pixel in the image should go to one class and only one class. According to the thresholds the segmented results whether or not consistent to the image is also an issue should be considered.Here wepropose a new method for color image segmentation using multilevel thresholding. This paper proposes multilevel thresholding fo

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Mangaraj, Biswa Binayak, Manas Ranjan Jena, and Saumendra Kumar Mohanty. "Bacteria Foraging Algorithm in Antenna Design." Applied Computational Intelligence and Soft Computing 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/5983469.

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A simple design procedure to realize an optimum antenna using bacteria foraging algorithm (BFA) is proposed in this paper. The first antenna considered is imaginary. This antenna is optimized using the BFA along with a suitable fitness function formulated by considering some performance parameters and their best values. To justify the optimum design approach, one 12-element Yagi-Uda antenna is considered for an experiment. The optimized result of this antenna obtained using the optimization algorithm is compared with nonoptimized (conventional) result of the same antenna to appreciate the impo

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Murali, Dr N., Dr M. Annamalai, Dr S. Gobimohan, and Mr Vidhya Prakash. "PID Controller Design of Brushless DC Motor by Bacteria Foraging and Hybrid Bacteria Foraging-PSO Optimization." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 12 (2023): 1–10. http://dx.doi.org/10.55041/ijsrem27491.

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Brushless DC motors are widely used in industries incomparable to DC motors. In this research work transfer function is obtained for brushless DC motor for designing controller gains. The performance is analysed by with and without controller. The design of controller gains is done by bacterial foraging and hybrid bacterial PSO optimization algorithm. The simulation was done by MATLAB /SIMULINK platform and the results are compared for with and without controller. The settling time, steady state error and peak overshoot is better when compared to without controller. Key Words: PID control, opt

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Stubbusch, Astrid K. M., François J. Peaudecerf, Kang Soo Lee, et al. "Antagonism as a foraging strategy in microbial communities." Science 388, no. 6752 (2025): 1214–17. https://doi.org/10.1126/science.adr8286.

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In natural habitats, nutrient availability limits bacterial growth. We discovered that bacteria can overcome this limitation by acquiring nutrients by lysing neighboring cells through contact-dependent antagonism. Using single-cell live imaging and isotopic markers, we found that during starvation, the type VI secretion system (T6SS) lysed neighboring cells and thus provided nutrients from lysing cells for growth. Genomic adaptations in antagonists, characterized by a reduced metabolic gene repertoire, and the previously unexplored distribution of the T6SS across bacterial taxa in natural envi

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Ai, Ying, Yi Xin Su, Dan Hong Zhang, and Yao Peng. "Improved Chaotic Bacteria Foraging Optimization Algorithm Particle." Applied Mechanics and Materials 651-653 (September 2014): 2322–25. http://dx.doi.org/10.4028/www.scientific.net/amm.651-653.2322.

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. Aiming at the defects of weak global search ability and slow convergence speed in bacteria foraging algorithm optimization, this paper proposed an improved chaotic bacteria foraging optimization algorithm which has introduced the chaotic thoughts, improved the update operation of fitness and migration operation in optimization process. Using Logistic chaotic map initializes the bacteria population, so as to improve the convergence speed of the algorithm; Then adjust quorum sensing mechanism to optimize the chemotactic direction of the bacteria, and operate on perished bacteria with chaos dis

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Ackermann, Michael, Paul Prill, and Liliane Ruess. "Disentangling nematode-bacteria interactions using a modular soil model system and biochemical markers." Nematology 18, no. 4 (2016): 403–15. http://dx.doi.org/10.1163/15685411-00002965.

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Interactions between bacteria and nematode grazers are an important component of soil food webs yet, due to the cryptic habitat, they are almost exclusively investigated in artificial agar substrate. Transport, food choice and foraging experiments were performed in a modular microcosm system with the nematode Acrobeloides buetschlii and bacterial diets (Escherichia coli, Pseudomonas putida and Bacillus subtilis) in gamma-irradiated soil. Bacterial biomass was assessed by soil phospholipid fatty acids (PLFAs). Continuous random foraging of nematodes was affected by soil type. Food choice experi

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Jiang, Jianguo, Jiawei Zhou, Yingchun Zheng, and Runsheng Zhou. "A double flora bacteria foraging optimization algorithm." Journal of Shenzhen University Science and Engineering 31, no. 1 (2014): 43. http://dx.doi.org/10.3724/sp.j.1249.2014.01043.

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Periyasamy, S., and R. Kaniezhil. "Enhanced feature selection with bacterial foraging and rough set analysis for document clustering." Journal of Autonomous Intelligence 7, no. 5 (2024): 1631. http://dx.doi.org/10.32629/jai.v7i5.1631.

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<p>Most applications, such as Information Retrieval and Natural Language Processing (NLP), utilize document clustering to improve their analysis. The document consists of various features that are utilized to determine the similar and dissimilar documents. However, the traditional techniques consume high computation difficulties and convergence problems while analyzing high-dimensional data. The research difficulties are addressed with the help of Bacterial Foraging and Rough Set Analysis (BF-RSA). This study uses the TF-IDF features for analyzing similar documents. The extracted feature

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Abdul Hameed, K., and S. Palani. "Robust design of power system stabilizer using bacterial foraging algorithm." Archives of Electrical Engineering 62, no. 1 (2013): 141–52. http://dx.doi.org/10.2478/aee-2013-0010.

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Abstract In this paper, a novel bacterial foraging algorithm (BFA) based approach for robust and optimal design of PID controller connected to power system stabilizer (PSS) is proposed for damping low frequency power oscillations of a single machine infinite bus bar (SMIB) power system. This paper attempts to optimize three parameters (Kp, Ki, Kd) of PID-PSS based on foraging behaviour of Escherichia coli bacteria in human intestine. The problem of robustly selecting the parameters of the power system stabilizer is converted to an optimization problem which is solved by a bacterial foraging al

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LIU, Xiao-long, and Kui-ling ZHAO. "Bacteria foraging optimization algorithm based on immune algorithm." Journal of Computer Applications 32, no. 3 (2013): 634–37. http://dx.doi.org/10.3724/sp.j.1087.2012.00634.

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Kaur, Rajinder, Akshay Girdhar, and Surbhi Gupta. "Color Image Quantization based on Bacteria Foraging Optimization." International Journal of Computer Applications 25, no. 7 (2011): 33–42. http://dx.doi.org/10.5120/3042-4130.

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Wu, Shenli, Sun'an Wang, and Xiaohu Li. "A new dynamic bacterial foraging optimization and its application on model reduction." International Journal of Modeling, Simulation, and Scientific Computing 06, no. 02 (2015): 1550018. http://dx.doi.org/10.1142/s179396231550018x.

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Inspired by the foraging behavior of E. coli bacteria, bacterial foraging optimization (BFO) has emerged as a powerful technique for solving optimization problems. However, BFO shows poor performance on complex and high-dimensional optimization problems. In order to improve the performance of BFO, a new dynamic bacterial foraging optimization based on clonal selection (DBFO-CS) is proposed. Instead of fixed step size in the chemotaxis operator, a new piecewise strategy adjusts the step size dynamically by regulatory factor in order to balance between exploration and exploitation during optimiz

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Agarwal, Kavita, and Amanda L. Lewis. "Vaginal sialoglycan foraging by Gardnerella vaginalis: mucus barriers as a meal for unwelcome guests?" Glycobiology 31, no. 6 (2021): 667–80. http://dx.doi.org/10.1093/glycob/cwab024.

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Abstract Bacterial vaginosis (BV) is a condition of the vaginal microbiome in which there are few lactobacilli and abundant anaerobic bacteria. Members of the genus Gardnerella are often one of the most abundant bacteria in BV. BV is associated with a wide variety of poor health outcomes for women. It has been recognized since the 1980s that women with BV have detectable and sometimes markedly elevated levels of sialidase activity in vaginal fluids and that bacteria associated with this condition produce this activity in culture. Mounting evidence collected using diverse methodologies points t

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Yao, Yao, Jiankang Ren, Ran Bi, and Qian Liu. "Bacterial Foraging Algorithm Based on Activity of Bacteria for DNA Computing Sequence Design." IEEE Access 9 (2021): 2110–24. http://dx.doi.org/10.1109/access.2020.3047469.

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Ye, Fu-Lan, Chou-Yuan Lee, Zne-Jung Lee, Jian-Qiong Huang, and Jih-Fu Tu. "Incorporating Particle Swarm Optimization into Improved Bacterial Foraging Optimization Algorithm Applied to Classify Imbalanced Data." Symmetry 12, no. 2 (2020): 229. http://dx.doi.org/10.3390/sym12020229.

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In this paper, particle swarm optimization is incorporated into an improved bacterial foraging optimization algorithm, which is applied to classifying imbalanced data to solve the problem of how original bacterial foraging optimization easily falls into local optimization. In this study, the borderline synthetic minority oversampling technique (Borderline-SMOTE) and Tomek link are used to pre-process imbalanced data. Then, the proposed algorithm is used to classify the imbalanced data. In the proposed algorithm, firstly, the chemotaxis process is improved. The particle swarm optimization (PSO)

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Ding, Siyu Serena, Maksym Romenskyy, Karen S. Sarkisyan, and Andre E. X. Brown. "Measuring Caenorhabditis elegans Spatial Foraging and Food Intake Using Bioluminescent Bacteria." Genetics 214, no. 3 (2020): 577–87. http://dx.doi.org/10.1534/genetics.119.302804.

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For most animals, feeding includes two behaviors: foraging to find a food patch and food intake once a patch is found. The nematode Caenorhabditis elegans is a useful model for studying the genetics of both behaviors. However, most methods of measuring feeding in worms quantify either foraging behavior or food intake, but not both. Imaging the depletion of fluorescently labeled bacteria provides information on both the distribution and amount of consumption, but even after patch exhaustion a prominent background signal remains, which complicates quantification. Here, we used a bioluminescent E

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Kondo, Kotaro, Mirei Suzuki, Mana Amadaira, et al. "Association of maternal genetics with the gut microbiome and eucalypt diet selection in captive koalas." PeerJ 12 (May 27, 2024): e17385. http://dx.doi.org/10.7717/peerj.17385.

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Background Koalas, an Australian arboreal marsupial, depend on eucalypt tree leaves for their diet. They selectively consume only a few of the hundreds of available eucalypt species. Since the koala gut microbiome is essential for the digestion and detoxification of eucalypts, their individual differences in the gut microbiome may lead to variations in their eucalypt selection and eucalypt metabolic capacity. However, research focusing on the relationship between the gut microbiome and differences in food preferences is very limited. We aimed to determine whether individual and regional differ

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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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Scheiner, Ricarda, Sina Strauß, Markus Thamm, Gerard Farré-Armengol, and Robert R. Junker. "The Bacterium Pantoea ananatis Modifies Behavioral Responses to Sugar Solutions in Honeybees." Insects 11, no. 10 (2020): 692. http://dx.doi.org/10.3390/insects11100692.

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1. Honeybees, which are among the most important pollinators globally, do not only collect pollen and nectar during foraging but may also disperse diverse microbes. Some of these can be deleterious to agricultural crops and forest trees, such as the bacterium Pantoea ananatis, an emerging pathogen in some systems. P. ananatis infections can lead to leaf blotches, die-back, bulb rot, and fruit rot. 2. We isolated P. ananatis bacteria from flowers with the aim of determining whether honeybees can sense these bacteria and if the bacteria affect behavioral responses of the bees to sugar solutions.

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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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Wang, Shujuan, Long He, and Guiru Cheng. "Cooperative Optimization QoS Cloud Routing Protocol Based on Bacterial Opportunistic Foraging and Chemotaxis Perception for Mobile Internet." Journal of Electrical and Computer Engineering 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/641062.

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In order to strengthen the mobile Internet mobility management and cloud platform resources utilization, optimizing the cloud routing efficiency is established, based on opportunistic bacterial foraging bionics, and puts forward a chemotaxis perception of collaborative optimization QoS (Quality of Services) cloud routing mechanism. The cloud routing mechanism is based on bacterial opportunity to feed and bacterial motility and to establish the data transmission and forwarding of the bacterial population behavior characteristics. This mechanism is based on the characteristics of drug resistance

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K, Mani, and Mullai A. "Generation of Addition Chain using Bacteria Foraging Optimization Algorithm." International Journal of Engineering Trends and Technology 69, no. 2 (2021): 32–38. http://dx.doi.org/10.14445/22315381/ijett-v69i2p205.

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Majumder, Arindam, and Dipak Laha. "Bacteria Foraging Optimization Algorithm for Robotic Cell Scheduling Problem." Materials Today: Proceedings 4, no. 2 (2017): 2129–36. http://dx.doi.org/10.1016/j.matpr.2017.02.059.

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Abd-Elazim, Sahar M., and Ehab S. Ali. "Power System Stability Enhancement via Bacteria Foraging Optimization Algorithm." Arabian Journal for Science and Engineering 38, no. 3 (2012): 599–611. http://dx.doi.org/10.1007/s13369-012-0423-y.

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Jain, Arvind Kumar, Suresh Chandra Srivastava, Sri Niwas Singh, and Laxmi Srivastava. "Bacteria foraging optimization based bidding strategy under transmission congestion." IEEE Systems Journal 9, no. 1 (2015): 141–51. http://dx.doi.org/10.1109/jsyst.2013.2258229.

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Saha, Suman Kumar, Rajib Kar, Durbadal Mandal, and Sakti Prasad Ghoshal. "Bacteria foraging optimisation algorithm for optimal FIR filter design." International Journal of Bio-Inspired Computation 5, no. 1 (2013): 52. http://dx.doi.org/10.1504/ijbic.2013.053039.

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Mishra, Sudhansu Kumar, Ganapati Panda, and Ritanjali Majhi. "Constrained portfolio asset selection using multiobjective bacteria foraging optimization." Operational Research 14, no. 1 (2013): 113–45. http://dx.doi.org/10.1007/s12351-013-0138-1.

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Panigrahi, B. K., V. Ravikumar Pandi, Renu Sharma, Swagatam Das, and Sanjoy Das. "Multiobjective bacteria foraging algorithm for electrical load dispatch problem." Energy Conversion and Management 52, no. 2 (2011): 1334–42. http://dx.doi.org/10.1016/j.enconman.2010.09.031.

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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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Abbas, Nizar Hadi, and Farah Mahdi Ali. "Path Planning of an Autonomous Mobile Robot using Enhanced Bacterial Foraging Optimization Algorithm." Al-Khwarizmi Engineering Journal 12, no. 4 (2017): 26–35. http://dx.doi.org/10.22153/kej.2016.01.001.

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This paper describes the problem of online autonomous mobile robot path planning, which is consisted of finding optimal paths or trajectories for an autonomous mobile robot from a starting point to a destination across a flat map of a terrain, represented by a 2-D workspace. An enhanced algorithm for solving the problem of path planning using Bacterial Foraging Optimization algorithm is presented. This nature-inspired metaheuristic algorithm, which imitates the foraging behavior of E-coli bacteria, was used to find the optimal path from a starting point to a target point. The proposed algorith

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Gupta, Kapil Kumar, Rizwan Beg, and Jitendra Kumar Niranjan. "An Enhanced Approach of Face Detection using Bacteria Foraging Technique." International Journal of Computer Vision and Image Processing 6, no. 1 (2016): 1–11. http://dx.doi.org/10.4018/ijcvip.2016010101.

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In this study, authors present an enhanced approach of face detection using bacteria foraging technique. This approach is based on chemotexis, reproduction and elimination and dispersal step. In this study the authors analysed face detection algorithm based on human skin color and fitting the ellipse as human face can be approximate by ellipse. Their approach for face detection requires no initial pre-processing of the image. A number of Bacteria agents with evolutionary behaviours are uniformly distributed in the 2-D image environment to search the skin-like pixels and locate each face-like r

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Sun, Jianhui, and Shuai Zhang. "Rolling Bearing Fault Feature Extraction Based on Bacteria Foraging Optimization." Journal of Failure Analysis and Prevention 17, no. 6 (2017): 1217–25. http://dx.doi.org/10.1007/s11668-017-0365-5.

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Nouri, Hossein, and Tang Sai Hong. "A bacteria foraging algorithm based cell formation considering operation time." Journal of Manufacturing Systems 31, no. 3 (2012): 326–36. http://dx.doi.org/10.1016/j.jmsy.2012.03.001.

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Vivekanandan, K., and D. Ramyachitra. "Bacteria foraging optimization for protein sequence analysis on the grid." Future Generation Computer Systems 28, no. 4 (2012): 647–56. http://dx.doi.org/10.1016/j.future.2011.10.009.

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Kosewska, Olga, Sebastian Wojciech Przemieniecki, and Mariusz Nietupski. "Influence of the Chemical Properties of Cereal Grains on the Structure and Metabolism of the Bacteriome of Rhyzopertha dominica (F.) and Its Development: A Cause–Effect Analysis." International Journal of Molecular Sciences 25, no. 18 (2024): 10130. http://dx.doi.org/10.3390/ijms251810130.

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Rhyzopertha dominica causes significant economic losses in stored cereals. Insects’ digestive tract microbiome is crucial for their development, metabolism, resistance, and digestion. This work aimed to test whether the different chemical properties of different wheat and barley grain cultivars cause disturbances in insect foraging and rearrangements of the structure of the R. dominica microbiome. The results indicated that grain cultivars significantly influence the microbiome, metabolism, and insect foraging. Most observed traits and microbiome structures were not correlated at the species l

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Chen, Huang, Lide Wang, Jun Di, and Shen Ping. "Bacterial Foraging Optimization Based on Self-Adaptive Chemotaxis Strategy." Computational Intelligence and Neuroscience 2020 (May 27, 2020): 1–15. http://dx.doi.org/10.1155/2020/2630104.

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Bacterial foraging optimization (BFO) algorithm is a novel swarm intelligence optimization algorithm that has been adopted in a wide range of applications. However, at present, the classical BFO algorithm still has two major drawbacks: one is the fixed step size that makes it difficult to balance exploration and exploitation abilities; the other is the weak connection among the bacteria that takes the risk of getting to the local optimum instead of the global optimum. To overcome these two drawbacks of the classical BFO, the BFO based on self-adaptive chemotaxis strategy (SCBFO) is proposed in

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Chin, Kit Ling, Paik San H'ng, Wan Zhen Wong, et al. "Septicaemia of subterranean termites Coptotermes curvignathus caused by disturbance of bacteria isolated from termite gut and its foraging pathways." Royal Society Open Science 7, no. 8 (2020): 200847. http://dx.doi.org/10.1098/rsos.200847.

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Microbial pathogens continue to attract a great deal of attention to manage the termite population. Every bacterium has its own mode of action and in fact, the mechanisms used by bacteria to attack termites remain elusive at the moment. Hence, the objective of this study was to evaluate the susceptibility of subterranean termites Coptotermes curvignathus to opportunistic pathogens using culturable aerobic bacteria isolated from the termite gut and its foraging pathways. Bacterial suspensions were prepared in concentrations of 10 3 , 10 6 and 10 9 colony-forming units (CFU) ml −1 and introduced

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Sarangi, Archana, Sasmita Kumari Padhy, Siba Prasada Panigrahi, and Shubhendu Kumar Sarangi. "GBF Trained Neuro-fuzzy Equalizer for Time Varying Channels." International Journal of Applied Evolutionary Computation 2, no. 3 (2011): 27–38. http://dx.doi.org/10.4018/jaec.2011070103.

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This paper proposes a neuro-fuzzy filter for equalization of time-varying channels. Additionally, it proposes to tune the equalizer with a hybrid algorithm between Genetic Algorithms (GA) and Bacteria Foraging (BFO), termed as GBF. The major advantage of the method developed in this paper is that all parameters of the neuro-fuzzy network, including the rule base, are tuned simultaneously through the proposed hybrid algorithm of genetic Algorithm and bacteria foraging. The performance of the Neuro-Fuzzy equalizer designed using the proposed approach is compared with Genetic algorithm based equa

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S., Gobimohan, and Murali N. "Implementation of PWM AC chopper controller for capacitor run induction motor drive via bacterial foraging optimization algorithm." International Journal of Reconfigurable and Embedded Systems 9, no. 3 (2020): 169–77. https://doi.org/10.11591/ijres.v9.i3.pp169-177.

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This paper focuses on design of closed-loop control for pulse width modulated AC chopper controlled capacitor run induction motor drive engaging enriched optimization algorithm based on foraging of bacteria. Capacitor run induction motor is a non-linear device and its parameter varies under different functional point of the system. A linearized increment model for PWM AC chopper is illustrated for a particular functional point of the drive. The conventional method does not provide acceptable performance under different load conditions. Bacteria foraging optimization technique categorizes accur

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Liu, Jianguo, Zhanying Liu, Yucheng Liu, Min Hao, and Xianzhi Hou. "Analysis of cellulolytic bacterial flora in the rumen of inner Mongolian sheep." BioResources 14, no. 4 (2019): 9544–56. http://dx.doi.org/10.15376/biores.14.4.9544-9556.

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The cellulolytic bacterial flora present in the rumen of Inner Mongolian sheep are thought to have a high degree of cellulose-degrading activity because of their foraging feeding regimen. However, there are no report on the genetic and species composition of the cellulolytic bacterial flora. In this study, cellulolytic bacteria were isolated from the rumen of Inner Mongolian sheep using a combined method of transparent zone and filter paper degradation. Twenty-two strains were identified via morphological, physiological, and biochemical tests. Ten strains were further identified via DNA (G + C

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Muni, Manoj Kumar, Dayal R. Parhi, and Priyadarshi Biplab Kumar. "Improved Motion Planning of Humanoid Robots Using Bacterial Foraging Optimization." Robotica 39, no. 1 (2020): 123–36. http://dx.doi.org/10.1017/s0263574720000235.

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SUMMARYThis paper emphasizes on Bacterial Foraging Optimization Algorithm for effective and efficient navigation of humanoid NAO, which uses the foraging quality of bacteria Escherichia coli for getting shortest path between two locations in minimum time. The Gaussian cost function assigned to both attractant and repellent profile of bacterium performs a major role in obtaining the best path between any two locations. Mathematical formulations have been performed to design the control architecture for humanoid navigation using the proposed methodology. The developed approach has been tested in

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