Hyperspectral redundancy detection and modelling with local hurst exponent

2021 ◽  
pp. 126830
Author(s):  
Jianhui Li ◽  
Qiaozhi Li ◽  
Fang Wang ◽  
Fan Liu
Keyword(s):  
Hurst Exponent ◽  
Redundancy Detection

Minimum attribute reduction algorithm based on quick extraction and multi-strategy social spider optimization

2021 ◽  
pp. 1-16
Author(s):  
Qianjin Wei ◽  
Chengxian Wang ◽  
Yimin Wen
Keyword(s):  
Rough Set Theory ◽  
Attribute Reduction ◽  
Search Space ◽  
Initial State ◽  
Solution Quality ◽  
Social Spider ◽  
Opposition Based Learning ◽  
Social Spider Optimization ◽  
Intelligent Optimization Algorithm ◽  
Redundancy Detection

Intelligent optimization algorithm combined with rough set theory to solve minimum attribute reduction (MAR) is time consuming due to repeated evaluations of the same position. The algorithm also finds in poor solution quality because individuals are not fully explored in space. This study proposed an algorithm based on quick extraction and multi-strategy social spider optimization (QSSOAR). First, a similarity constraint strategy was called to constrain the initial state of the population. In the iterative process, an adaptive opposition-based learning (AOBL) was used to enlarge the search space. To obtain a reduction with fewer attributes, the dynamic redundancy detection (DRD) strategy was applied to remove redundant attributes in the reduction result. Furthermore, the quick extraction strategy was introduced to avoid multiple repeated computations in this paper. By combining an array with key-value pairs, the corresponding value can be obtained by simple comparison. The proposed algorithm and four representative algorithms were compared on nine UCI datasets. The results show that the proposed algorithm performs well in reduction ability, running time, and convergence speed. Meanwhile, the results confirm the superiority of the algorithm in solving MAR.

scholarly journals Diversity of SARS-CoV-2 isolates driven by pressure and health index

2021 ◽  
Vol 149 ◽  
Author(s):  
R. K. Sanayaima Singh ◽  
Md. Zubbair Malik ◽  
R. K. Brojen Singh
Keyword(s):  
Fractal Dimension ◽  
Severe Acute Respiratory Syndrome ◽  
Mutation Rate ◽  
Hurst Exponent ◽  
Viral Genome ◽  
Critical Pressure ◽  
Genome Organisation ◽  
Health Index ◽  
Genome Diversity ◽  
Fast Spreading

Abstract One of the main concerns about the fast spreading coronavirus disease 2019 (Covid-19) pandemic is how to intervene. We analysed severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) isolates data using the multifractal approach and found a rich in viral genome diversity, which could be one of the root causes of the fast Covid-19 pandemic and is strongly affected by pressure and health index of the hosts inhabited regions. The calculated mutation rate (mr) is observed to be maximum at a particular pressure, beyond which mr maintains diversity. Hurst exponent and fractal dimension are found to be optimal at a critical pressure (Pm), whereas, for P > Pm and P < Pm, we found rich genome diversity relating to complicated genome organisation and virulence of the virus. The values of these complexity measurement parameters are found to be increased linearly with health index values.

scholarly journals Combinatorial redundancy detection

2016 ◽  
Vol 265 (1) ◽  
pp. 47-65 ◽  
Author(s):  
Komei Fukuda ◽  
Bernd Gärtner ◽  
May Szedlák
Keyword(s):  
Redundancy Detection

Determination of Hurst exponent by optical signal processing applied on surface roughness measurements

2009 ◽  
Author(s):  
José Antonio Marbán Salgado ◽  
Oscar Sarmiento Martínez ◽  
Darwin Mayorga Cruz ◽  
Jorge Uruchurtu Chavarín
Keyword(s):  
Surface Roughness ◽  
Signal Processing ◽  
Hurst Exponent ◽  
Optical Signal Processing ◽  
Optical Signal ◽  
Roughness Measurements
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