基于bolzano增强器的Rayleigh商优势特征值快速收敛

M. Arifin, A. N. Che Pee, S. S. Rahim, A. Wibawa
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引用次数: 0

摘要

计算排序算法被广泛应用于多个信息学领域。其中之一是PageRank算法,它被认为是全球最受欢迎的搜索引擎。为了获得更好的结果,许多研究人员对排名算法进行了改进。近年来利用瑞利商加速PageRank的研究可以保证优势特征值的收敛性,并以此作为停止计算的关键值。Bolzano方法在线性函数上具有收敛性,通过将一个区间划分为两个区间来获得更好的收敛性。本研究旨在将Bolzano算法植入Rayleigh中,以提高计算速度。本研究产生的算法已经过数学家的测试和验证,与唯一的Rayleigh方法相比,该算法的优化速度最高为7.08%。利用统计软件对计算结果进行分析,表明新算法的Rayleigh + Bolzano booster (RB)曲线度为正,且比原方法更显著。换句话说,线性函数在后续的计算中总是比之前的方法更快。
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Rayleigh quotient with bolzano booster for faster convergence of dominant eigenvalues
Computation ranking algorithms are widely used in several informatics fields. One of them is the PageRank algorithm, recognized as the most popular search engine globally. Many researchers have improvised the ranking algorithm in order to get better results. Recent research using Rayleigh Quotient to speed up PageRank can guarantee the convergence of the dominant eigenvalues as a key value for stopping computation. Bolzano's method has a convergence character on a linear function by dividing an interval into two intervals for better convergence. This research aims to implant the Bolzano algorithm into Rayleigh for faster computation. This research produces an algorithm that has been tested and validated by mathematicians, which shows an optimization speed of a maximum 7.08% compared to the sole Rayleigh approach. Analysis of computation results using statistics software shows that the degree of the curve of the new algorithm, which is Rayleigh with Bolzano booster (RB), is positive and more significant than the original method. In other words, the linear function will always be faster in the subsequent computation than the previous method.
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来源期刊
International Journal of Advances in Intelligent Informatics
International Journal of Advances in Intelligent Informatics Computer Science-Computer Vision and Pattern Recognition
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3.00
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