Heuristic approaches for optimizing the performance of rule-based classifiers by Harmanani, Haidar

“…In this paper, we present an approach that optimizes the performance of the rule-based classifiers on the testing set. …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti (21593819)

“…This study focuses on optimizing and comparing various machine learning models for ASD diagnosis, while incorporating explainable AI techniques to ensure model transparency and interpretability. …”

Optimal Routing Protocol in Multimedia Wireless Sensor Networks by Al-Zurba, Hiba

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StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features by Muhammad Arif (769250)

“…Defensins are the type of AMPs that act as potential therapeutic drug agent and perform vital role in various biological process. …”

Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine by Debendra Muduli (20748758)

“…In this MOD-POA+ELM algorithm, the modified pelican optimization algorithm (MOD-POA) has been utilized to optimize the parameters of ELM’s hidden neurons. …”

Enhancing Arabic Offensive Tweet Classification: An Ensemble Approach Integrating AraBERT, Neural Networks, and LSTM Models by WAHDAN, AHLAM MOHAMMAD

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Dynamic Cyber Resilience of Interdependent Critical Information Infrastructures by JUMA, MAZEN GHAZI

“…Nevertheless, the optimized solution achieved the optimal results compared to the standard solutions. …”
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Machine Learning Based Palm Farming: Harvesting and Disease Identification by Khan, Sana Z.

“…For this purpose, we utilize deep learning (DL) models by adding additional layers and optimizing various parameters to enhance their performance for these specific tasks. …”
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UGA-GAN: Unified Geometry-Aware GAN for Enhanced Training and Generation of High-Dimensional Data by Wasi Ahmad (23124064)

“…While UGA-GAN presents state-of-the-art performance, future work will focus on optimizing its computational efficiency, scaling it to larger datasets, and integrating it with emerging models such as diffusion networks and reinforcement learning for further performance enhancement.…”

Machine learning-driven identification and predictive mapping of clogging regimes in porous media by Ahmed Elrahmani (17128837)

“…These tools provide a scalable, interpretable foundation for optimizing system performance in managed aquifer recharge, enhanced oil recovery, groundwater remediation, and filtration system design.…”

Metabolomics-based prediction model for diabetes: A comprehensive analysis of biomarkers and machine learning approaches by Doaa Farid (22565300)

“…</p><h3>Conclusion</h3><p dir="ltr">Metabolomics data can effectively predict diabetes status, with logistic regression providing the optimal balance of performance and interpretability. …”

Explainable deep learning for rainfall prediction: A CNN-XGBoost hybrid approach in the northern region of Bangladesh by Md Safayet Islam (23073187)

“…Among them, the CNN-XGB hybrid model consistently demonstrated superior performance across all evaluation metrics, establishing it as the most reliable predictor in this study. …”

Automated detection of posterior urethral valves in voiding cystourethrography images: A novel AI-Based pipeline for enhanced diagnosis and classification by Saidul Kabir (15302407)

“…DenseNet201 combined with Unet achieved the best overall segmentation performance (Dice score coefficient 66.15 %). Optimal cut-off value of urethral ratio for PUV detection was determined as 2.01. …”

Nonlinear FEA of Soil-Structure-Interaction Effects on RC Shear-Wall Structures by Saadi, Dina

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Improvement of Dialysis Dosing Using Big Data Analytics by Mumtaz, Syeda Leena

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Cells Derived from Diabetic Patients Selected from a Cohort Study Using a Visual Search Tool (VST) Are Used as Models for Metformin Resistance by Marjan Nouri-Keshtkar (15431001)

“…Identifying these patients is a specialized and time-consuming process, which requires interpretation and analysis tasks. However, by using VST, which provides a user-friendly platform, medical researchers were enabled to perform complex analyses by entering a few queries in a short time; the capability that can be also used for other cohort-driven patient selection studies. …”