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30 results for “Swarm Intelligence (SI)”
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Research ArticleOpen accessIn the keywordsConsensus Decision Making on Scale-Free Buyer NetworksSunantha Sodsee, Maytiyanin Komkhao, Phayung MeesadProblem statement: Due to a behavior of buyers effects to a growth of marketing, then a group of agreement of buyers and buyers’ behavior on eventually placing orders are investigating. Approach: In this study, a discrete-time consensus protocol for a scale-free buyer networks is proposed. Herein, an initial purchase intention of each buyer is defined to be active or non-active … …Journal of Computer Science, Vol. 7, Issue 10 · 8 Aug 2011 · 6,714 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Efficient Ant Algorithm for Swarm-Based Image ClusteringSalima Ouadfel, Mohamed BatoucheA collective approach to resolve the segmentation problem was proposed. AntClust is a new ant-based algorithm that uses the self-organizing and autonomous brood sorting behavior observed in real ants. Ants and pixels are scatted on a discrete array of cells represented the ants’ environment. Using simple local rules and without any central control, ants form homogeneous clusters by moving pixels … …Journal of Computer Science, Vol. 3, Issue 3 · 31 Mar 2007 · 7,155 accessesView PDFCite
Research ArticleOpen accessIn the abstractFL-CARE: Federated Learning-Based Contention-Aware and Energy-Balanced Routing for Dense FANETsHalimjon Khujamatov, Elyanora Jolimbetova et al.In dense multi-drone FANET environments, routing efficiency is often reduced due to constant competition for a wireless channel, frequent changes in network topology, and uneven energy consumption between UAV nodes. These factors lead to a decrease in the packet delivery ratio, an increase in delays on the busiest or most unstable routes, and a reduction in the total network lifespan. … …Journal of Computer Science, Vol. 22, Issue 8 · 13 Aug 2026 · 1,172 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Holistic Approach to Security, Availability and Reliability in Fog ComputingAbdulrahman Alshehri, Hazzaa Alshareef, Samah Alhazmi et al.Abdulkareem, K. H., Mohammed, M. A., Gunasekaran, S. S., Al-Mhiqani, M. N., Mutlag, A. A., Mostafa, S. A., Ali, N. S., & Ibrahim, D. A. (2019). A Review of Fog Computing and Machine Learning: Concepts, Applications, Challenges, and Open Issues. IEEE Access, 7, 153123–153140. https://doi.org/10.1109/access.2019.2947542 Alrawais, A., Alhothaily, A., Hu, C., & Cheng, X. (2017). Fog Computing for the Internet … …Journal of Computer Science, Vol. 20, Issue 6 · 20 Mar 2024 · 6,372 accessesView PDFCite
Special issueIndustrial RobotsAmerican Journal of Engineering and Applied Sciences · 11 Feb 2021
Research ArticleOpen accessIn the abstractAn Elite Pool-Based Big Bang-Big Crunch Metaheuristic for Data ClusteringIbrahim Al-Marashdeh, Ghaith M. Jaradat, Masri Ayob et al.This paper delves into the capacity of enhanced Big Bang-Big Crunch (EBB-BC) metaheuristic to handle data clustering problems. BB-BC is a product of an evolution theory of the universe in physics and astronomy. Two main phases of BB-BC are big bang and big crunch. The big bang phase involves a creation of a population of random initial solutions, while in … …Journal of Computer Science, Vol. 14, Issue 12 · 19 Jun 2018 · 7,879 accessesView PDFCite
Research ArticleOpen accessIn the abstractSwarm Optimization Techniques for Segmenting Gel Electrophoresis ImagesSara Ibrahim Ibrahim, Mohamed Abd Allah Makhlouf, Ghada.S. El-Tawel, M.E. WahedGel Electrophoresis (GE) are discussed as the main tool to dissociate DNA sequences. It helps in analyzing the genome such that each image resulting from it consists of lanes that include several bands. Image segmentation plays the foremost role in image processing. It helps in producing accurate results in medical diagnosis. Image segmentation works by dividing an image into regions … …Current Research in Bioinformatics, Vol. 5, Issue 1 · 18 Jun 2016 · 8,092 accessesView PDFCite
Research ArticleOpen accessIn the abstractVIRTUAL MINING MODEL FOR CLASSIFYING TEXT USING UNSUPERVISED LEARNINGS. Koteeswaran, E. Kannan, P. VisuIn real world data mining is emerging in various era, one of its most outstanding performance is held in various research such as Big data, multimedia mining, text mining etc. Each of the researcher proves their contribution with tremendous improvements in their proposal by means of mathematical representation. Empowering each problem with solutions are classified into mathematical and implementation models. … …American Journal of Applied Sciences, Vol. 11, Issue 5 · 20 Feb 2014 · 6,582 accessesView PDFCite
Research ArticleOpen accessIn the abstractAN ALGORITHM FOR MINING USABLE RULES USING A HOLISTIC SWARM BASED APPROACHVeenu Mangat, Renu VigEvolutionary algorithms are capable of finding near optimal solutions to problems which are intractable to solve using conventional methods. One such problem is to accurately classify patients using rule mining methodology while controlling the size of output rules. A massive amount of data pertaining to medicine is generated and recorded daily. Uncovering useful knowledge and assisting decision makers in the … …Journal of Computer Science, Vol. 10, Issue 4 · 9 Dec 2013 · 6,667 accessesView PDFCite