Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

Mean prevalence of CoC across groups created using the k-means algorithm. by Shafayet Khan Shafee (22593191)

Classification of PavCA Index scores with the k-Means algorithm where k = 3. by Camille Godin (21445879)

Comparison of different optimization algorithms. by Hang Zhao (143592)

Subjects: “…crayfish optimization algorithm…”

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

Clustering graph for 10 species based on K-means clustering algorithm into three clusters based on similarity analysis. by Riaz Hussain Khan (19688168)

Flowchart of the algorithm. by Xingan Fu (21594713)

Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

Spatial spectrum estimation for three algorithms. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

Parameter estimates and estimated standard errors from the EE algorithm. by Alex Stivala (8356257)

Flowchart of DQN algorithm. by Jiandong Qiu (20389944)

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. …”

Workflow of the CAECENET algorithm. by Celia Herrero del Barrio (20479635)

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Top-rated mode of transport based on the SEU algorithm (SEU scores from 0 to 40). by Johannes Weyer (13392175)

Risk element category diagram. by Yao Hu (3479972)

“…This article extracted features related to risk assessment, such as weather factors, airport facility inspections, and security check results, and conducted qualitative and quantitative analysis on these features to generate a datable risk warning weight table. This article used these data to establish an LSTM model, which trained LSTM to identify potential risks and provide early warning by learning patterns and trends in historical data. …”

Example measurement and analysis units for landscape elements. by Jaewon Han (8660295)

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Association estimates (Exp(β) representing ratios of geometric means) with 95%CI between the Root Mean Square Error (RMSE) and covariates (imputation method, % of NAs, and gap leng... by Sofia Tagliaferro (20291213)

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Comparison of Point Cloud rigid registration algorithms. by Morena Raiola (22439390)

“…So, we decided to implement the TMM-based algorithm as the first step in the spatial mapping pipeline.…”

Distribution of median Root Mean Square Error (RMSE) for the Variation Index by pollen/station. by Sofia Tagliaferro (20291213)

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Distribution of the median Root Mean Square Error (RMSE) values for pollen/station by imputation method. by Sofia Tagliaferro (20291213)

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