Showing 481 - 500 results of 15,770 for search 'Based research algorithms', query time: 0.27s Refine Results
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    A computational enhancement of Base64 algorithm using Residue Number System algorithms by Kolawole Bariu LOGUNLEKO, Abolore Muhamin LOGUNLEKO, Ayisat Wuraola ASAJU-GBOLAGADE, Akinbowale Nathaniel BABATUNDE, Kazeem Alagbe GBOLAGADE

    Published 2025-03-01
    “…Therefore, the research bridges the security gap in the Base64 cryptographic algorithm by factoring the key mechanism of the RNS based algorithm into the newly developed algorithm. …”
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  3. 483

    A Navigation Algorithm Based on the Reinforcement Learning Reward System and Optimised with Genetic Algorithm by Mireya Cabezas-Olivenza, Ekaitz Zulueta, Iker Azurmendi-Marquinez, Unai Fernandez-Gamiz, Danel Rico-Melgosa

    Published 2024-12-01
    “…Nevertheless, it is a technique with a high number of parameters that need to be optimised without prior information, and correctly performing this is a complicated task. In this research study, a system based on the principles of reinforcement learning, specifically on the concept of rewards, is presented. …”
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    Research on the Transformer Failure Diagnosis Method Based on Fluorescence Spectroscopy Analysis and SBOA Optimized BPNN by Xueqing Chen, Dacheng Li, Anjing Wang

    Published 2025-04-01
    “…Then, the dimensionality reduction techniques of principal component analysis (PCA), kernel principal component analysis (KPCA), and multi-dimensional scale (MDS) are used for further processing. Based on various preprocessed and dimensionally reduced data, transformer failure diagnosis models based on the particle swarm optimization algorithm (PSO) and the secretary bird optimization algorithm (SBOA) optimized BPNN are established to quantitatively analyze the state of insulating oil and predict the durations of transformer failure. …”
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    Improved Firefly Algorithm Based on Heuristic Information by CUI Jia-rui, LI Qing, YANG Liu-yi, WANG Heng, ZHANG Bo-yu

    Published 2019-02-01
    “…Firefly Algorithm (FA) is an optimization algorithm based on swarm intelligence which mimics the social behavior of fireflies based on the flashing and attraction characteristics of fireflies With the aim to address the disadvantages of the firefly algorithm of slow convergence speed and ease of falling into the local optimum in the later period of the evolution process, the firefly algorithm is improved herein Two kinds of heuristic information are proposed into the algorithm to guide the convergence of the algorithm The first one takes the current global best as the heuristic information referencing the “global optimal” idea in particle swarm optimization, therefore, an algorithm called FAGO (Firefly Algorithm based on Global Optimization) is formed The second one is called FABE (Firefly Algorithm based on Bayesian Estimation) using the optimal moving direction calculated by Bayesian estimation as heuristic information The improved algorithms in this study are applied to numerical simulations of several classical test functions and compared with traditional FA and some other′s research are carried out The simulation results show that the proposed algorithms can well accelerate the convergence speed and improve the convergence accuracy…”
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  19. 499

    Graph-Based Lexical Sentiment Propagation Algorithm by Tajana Ban Kirigin, Sanda Bujačić Babić, Benedikt Perak

    Published 2025-03-01
    “…The proposed ConGraCNet Sentiment Propagation algorithm uniquely combines existing sentiment dictionaries and corpus-based syntactic–semantic embedding graphs to reliably capture and propagate sentiment values in lexical networks. …”
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