ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

The actual training effect of four algorithms on original photo data (All images are original images taken by the author). by Xiaojun Wang (50332)

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The run time for each algorithm in seconds. by Edward Antonian (21453161)

“…The goal of this paper is to examine several extensions to KGR/GPoG, with the aim of generalising them a wider variety of data scenarios. The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. …”

Schematic diagram of AIC operation. by Manxian Yang (20521600)

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Algorithm process. by Wei Cui (92129)

The method for determining the chemical constituents of unknown materials in the algorithm. by Dong Hyeok Choi (12562048)

R-squared, AIC and SC comparison for BSIS values. by Elif Tuçe Bal (21367965)

Parameters of ML algorithms. by Md. Maeen Molla (20827041)

The Search process of the genetic algorithm. by Wenguang Li (6528113)

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The construction process of the FCM clustering algorithm. by Xini Fang (20861990)

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Processed results from ECG data with the P-T algorithm. by Daehyun Kwon (11985629)

Multi-sensor fusion process and algorithm workflow. by Hongliang Zou (20707270)

Bias for the method E1 (min AIC). by Jan Porthun (18360707)

“…The methods are the following: maximising the chi-square statistic, maximising the chi-square statistic with a split-sample approach, maximising the c-index using either the AddFor- or Genetic algorithm, maximising the concordance probability estimator (CPE) with the AddFor- or Genetic algorithm, and minimising the Akaike information criterion (AIC). …”

Scatter diagram of different principal elements. by Jizhong Wang (7441697)

Algorithm comparison. by Manxian Yang (20521600)

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Data is generated from ARMA (p, q) models with (p, q) , and the corresponding AIC table is created. by Jesse Wheeler (18462457)

The flowchart of GWO-VMD method. by Zhenjing Yao (22189970)

“…We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”

Data after data processing. by Jiaqi Wang (369548)

Effects of processing rate and algorithms performance on estimates of biodiversity. by Valentine Fleuré (12822137)

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Optimize process data and final results by Dawei Wang (471687)