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

Control Parameters of IRSA Algorithm. by Wan-Hua Zhang (21601139)

“…This study focuses on this key area of diabetes prediction and aims to develop an innovative prediction method. Using the data set published by Kare, this paper constructs and compares various intelligent systems based on multilayer algorithms, and specifically introduces improved reptile search algorithm (IRSA) to optimize the weight and threshold initialization of traditional backpropagation (BP) neural networks. …”

DMTD algorithm. by Yunhu Huang (21402795)

“…Finally, we conducted comparative tests of the manual driving, intelligent driving algorithm (ITOR, STON), and the algorithms proposed in this paper, EITO, using real line data from the Yizhuang Line of Beijing Metro (YLBS). …”

Hyperparameters of self-supervised learning algorithms used in Experiments 1–5. by Lalit Pandey (13195488)

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

Subjects: “…crayfish optimization algorithm…”

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

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. …”

<i>Wolfset: A High-Quality Underwater Acoustic Dataset for Algorithm Development and Analysis</i> by Nuno Pessanha Santos (7381244)

“…<p dir="ltr">As data becomes increasingly available, relying on quality datasets for algorithm analysis and development is essential. …”

Confusion Matrix for the Hybrid algorithms. by Faten Al-hussein (20707521)

“…Medical records from 3,000 King Abdulaziz University Hospital patients containing demographic, lifestyle, and lipid profile data were used to develop the models. For the first time, we utilized recommended machine learning algorithms to develop hybrid prediction models to reduce the number of significant KPIs while enhancing HbA1c prediction accuracy. …”

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. …”

Characteristics of training algorithms. by Tuan Anh Nguyen (121944)

“…The model is designed with three inputs and one output, trained using data derived from a high-performance robust controller for Electric Power Steering (EPS) systems. …”

Pseudocode for the missForestPredict algorithm. by Elena Albu (15181070)

“…Missing data in input variables often occur at model development and at prediction time. …”

The pseudocode of the RFE algorithm. by Zuzhen Ji (17593348)

Proposed hybrid GA- ML algorithms. by Ankur Kumar (1357440)

Subjects:

Proposed GA-ML algorithms pseudocode. by Ankur Kumar (1357440)

Subjects:

Diagram algorithme. by Yunsuk Choi (754270)

High-Precision Landing on a Moving Platform Based on Drone Vision Using Yolo Algorithm by Satoshi Suzuki (20437556)

“…To overcome the challenge of the flight altitude is too high to detect the landing target, this paper fi rst detects large-volume targets, followed by the precise identifi cation of smaller targets, achieving enhanced recognition accuracy and speed through an improved YOLOv8 OBB algorithm. To maintain the UAV’s safety and stability throughout the landing process, This paper applies a position control approach using a reference model based sliding mode controller (RMSMC). …”

Identification of circadian rhythm-related biomarkers and development of diagnostic models for Crohn’s disease using machine learning algorithms by Zhijing Zhao (6569369)

“…Diagnostic models were constructed using machine learning algorithms, and biologic therapy efficacy was predicted with advanced regression techniques. …”