Image-Based Air Quality Estimation Using Convolutional Neural Network Optimized by Genetic Algorithms: A Multi-Dataset Approach by Arshad Ali Khan (23152516)

“…To mitigate overfitting, we implemented dropout layers, batch normalization, and early stopping, significantly enhancing the model’s generalization capability. Specifically, three different open-access datasets were combined into a single training dataset, capturing extensive temporal, spatial, and environmental variability. …”

DAP: A dataset-agnostic predictor of neural network performance by Sui Paul Ang (18460605)

“…<p>Training a deep neural network on a large dataset to convergence is a time-demanding task. This task often must be repeated many times, especially when developing a new deep learning algorithm or performing a neural architecture search. …”

Predicting Plasma Vitamin C Using Machine Learning by Daniel Kirk (17302798)

“…The objective of this study is to predict plasma vitamin C using machine learning. The NHANES dataset was used to predict plasma vitamin C in a cohort of 2952 American adults using regression algorithms and clustering in a way that a hypothetical health application might. …”

VHDRA: A Vertical and Horizontal Intelligent Dataset Reduction Approach for Cyber-Physical Power Aware Intrusion Detection Systems by Hisham A. Kholidy (18891802)

“…<p dir="ltr">The Cypher Physical Power Systems (CPPS) became vital targets for intruders because of the large volume of high speed heterogeneous data provided from the Wide Area Measurement Systems (WAMS). The Nonnested Generalized Exemplars (NNGE) algorithm is one of the most accurate classification techniques that can work with such data of CPPS. …”

Optimizing Document Classification: Unleashing the Power of Genetic Algorithms by Ghulam Mustafa (458105)

“…In this study, we chose four meta-data-based features such as, title, keyword, abstract, and general terms from the SANTOS dataset, which was prepared by ACM. …”

Exploring Semi-Supervised Learning Algorithms for Camera Trap Images by Sajun, Ali Reza

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Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms by Arafat Rahman (8065562)

“…To address these issues, a novel multimodal biometric system combining EEG and keystroke dynamics is proposed in this paper. A dataset was created by acquiring both keystroke dynamics and EEG signals simultaneously from 10 users. …”

An Optimized Feature Selection Technique in Diversified Natural Scene Text for Classification Using Genetic Algorithm by Ghulam Jillani Ansari (16896342)

“…Third, to improve the average F-score of the classifier, we apply a meta-heuristic optimization technique using a GA for feature selection. The proposed algorithm is tested on five publically available datasets and the results are compared with various state-of-the-art methods. …”

Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques by Abu Zitar, Raed

“…Various types of Deep Learning (DL) and Machine Learning (ML) algorithms employed in Solar and Wind energy supplies are given. …”
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Habitat in flames: How climate change will affect fire risk across koala forests by Farzin Shabani (302023)

“…</p><p><br></p><h3>Method:</h3><p dir="ltr">The Decision Tree machine learning algorithm was applied to generate a fire susceptibility index (a measure of the potential for a given area or region to experience wildfires) using a dataset of conditioning factors, namely: altitude, aspect, rainfall, distance from rivers, distance from roads, forest type, geology, koala presence and future dietary sources, land use-land cover (LULC), normalized difference vegetation index (NDVI), slope, soil, temperature, and wind speed.…”

Simultaneous identification of robust synergistic subnetwork markers for effective cancer prognosis by Navadon Khunlertgit (3480926)

“…<p>Accurate prediction of cancer prognosis based on gene expression data is generally difficult, and identifying robust prognostic markers for cancer remains a challenging problem. …”

Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts by ALSHAMSI, SUROUR

“…As a function of the proposed objective, ensembling algorithms applicable to network security have been investigated and evaluated, and a methodology for detecting infected PAGE 2 hosts using ensembling has been developed, based on experiments designed and tested with real datasets. …”
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An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting by Mohamed Massaoudi (16888710)

“…Then, the stacked LSTM model, optimized by Tabu search algorithm, uses the residual error correction associated with the original data to produce a point and interval PVPF. …”

ThoraX-PriorNet: A Novel Attention-Based Architecture Using Anatomical Prior Probability Maps for Thoracic Disease Classification by Md. Iqbal Hossain (723299)

Semi-supervised Clustering of Facial Expressions by Jalal, Ahsan

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A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks by Sakib Mahmud (15302404)

“…Persistent challenges include dataset scarcity and bias, limited generalization across assets and seasons, computational cost, safety and constraint handling, and the gap between simulation and field deployment. …”

Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases by Muhammad Ali Muzammil (17910611)

“…Genetic variations influence ECG readings, so racial diversity in datasets is significant. Furthermore, issues such as inadequate generalization, regulatory barriers, and interpretability concerns contribute to deployment difficulties. …”

An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System by Alkhatib, Osama

“…Meaning no “perfect” machine learning algorithm that will produce good results at particular problem, in fact for each type of problem a specific algorithm is suited and might achieves good outcome, while another algorithm fails heavily. …”
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Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning by Far, Reza Davoodi

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Bootstrap-based Aggregations and their Stability in Feature Selection by Salman, Reem Elfatih

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