Algorithm performance comparison. by Haiyan Wang (25821)

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

Types of machine learning algorithms. by Md. Merajul Islam (12646837)

“…<div><p>Background and objectives</p><p>Child undernutrition is a leading global health concern, especially in low and middle-income developing countries, including Bangladesh. Thus, the objectives of this study are to develop an appropriate model for predicting the risk of undernutrition and identify its influencing predictors among under-five children in Bangladesh using explainable machine learning algorithms.…”

Improve algorithm settings. by Hui Zhao (7395)

Subjects:

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

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

Performance of machine learning algorithms. by Wenxue Liu (6877754)

Evaluation of model aggregation algorithms. by JiaMing Wang (334865)

“…To address these challenges, this paper proposes a federated learning-based intrusion detection algorithm (NIDS-FGPA) that utilizes gradient similarity model aggregation. …”

Workflow of our study to evaluate the performance of GNNs compared to benchmark algorithms. by Daniel Walke (21680915)

Subjects:

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

“…This article presents the design of a hybrid self-learning algorithm to address the above challenges. The proposed approach is developed by integrating fuzzy logic and neural network structures into an Adaptive Network-Based Fuzzy Inference System (ANFIS), which leverages the strengths of both components. …”

IOU values of four algorithms. by Hong Li (20183)

Computational Micromechanics and Machine Learning-Informed Design of Composite Carbon Fiber-Based Structural Battery for Multifunctional Performance Prediction by Mohamad A. Raja (19640297)

Subjects: “…bayesian optimization algorithm…”

Coati optimization algorithm for brain tumor identification based on MRI with utilizing phase-aware composite deep neural network by Rajesh Kumar Thangavel (20591164)

“…In this research, Utilizing Phase-aware Composite Deep Neural Network Optimized with Coati Optimized Algorithm for Brain Tumor Identification Based on Magnetic resonance imaging (PACDNN-COA-BTI-MRI) is proposed. …”

Ultrafast Hydrogen Detection System Using Vertical Thermal Conduction Structure and Neural Network Prediction Algorithm Based on Sensor Response Process by Ruilin Yang (151028)

“…Here we report an ultrafast (0.4 s) hydrogen detection system based on a wafer-scale fabrication process. It consists of a low power (20.2 mW) hydrogen sensor based on vertical thermal conduction structure and a signal processing circuit introduced with a neural network prediction algorithm based on sensor response process. …”

Ultrafast Hydrogen Detection System Using Vertical Thermal Conduction Structure and Neural Network Prediction Algorithm Based on Sensor Response Process by Ruilin Yang (151028)

“…Here we report an ultrafast (0.4 s) hydrogen detection system based on a wafer-scale fabrication process. It consists of a low power (20.2 mW) hydrogen sensor based on vertical thermal conduction structure and a signal processing circuit introduced with a neural network prediction algorithm based on sensor response process. …”

Supervised Predictive Modeling of High-dimensional Data with Group l0-norm Constrained Neural Networks by Zhihuang Yang (22530437)

“…By leveraging group <math><mrow><msub><mrow><mi>l</mi></mrow><mn>0</mn></msub></mrow></math>-norm constrained neural networks, the proposed approach aims to simultaneously extract crucial features and estimate the underlying model function with statistically guaranteed accuracy. …”

Comparison of homomorphic encryption algorithms. by JiaMing Wang (334865)

“…To address these challenges, this paper proposes a federated learning-based intrusion detection algorithm (NIDS-FGPA) that utilizes gradient similarity model aggregation. …”

The diagram of the LSTM neural network. by Mohd Sakib (20565228)

“…This study proposes an ensemble approach that integrates a genetic algorithm with multiple forecasting models to optimize feature selection. …”

The comparison of results from the proposed architecture and state-of-the-art algorithms on the UNSW-B15, NSL-KDD and KDDCUP’99 dataset. by Abdullah Asım Yılmaz (20715311)

Overview of the Cell2Spatial algorithm. by Huamei Li (8815955)

“…Feedforward neural network (FNN) was employed for cell pre-assignment to ST clusters (Step 6), and the Jonker-Volgenant algorithm iteratively mapped individual cells to specific spatial spots based on similarities and estimated cell counts (Step 7).…”