Data-Driven Loan Default Prediction: A Machine Learning Approach for Enhancing Business Process Management by Xinyu Zhang, Tianhui Zhang, Lingmin Hou, Xianchen Liu, Zhen Guo, Yuanhao Tian, Yang Liu

“…This study evaluates the effectiveness of machine learning models, specifically XGBoost, Gradient Boosting, Random Forest, and LightGBM, in predicting loan defaults. The research investigates the following question: How effective are machine learning models in predicting loan defaults compared to traditional approaches? …”
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Intelligent Feature Selection Ensemble Model for Price Prediction in Real Estate Markets by Daniel Cristóbal Andrade-Girón, William Joel Marin-Rodriguez, Marcelo Gumercindo Zuñiga-Rojas

“…These dimensionality reduction techniques enhanced computational efficiency and proved effective for practical applications without significantly compromising accuracy. Future research should explore automatic hyperparameter optimization and hybrid approaches to improve the adaptability and robustness of models in complex contexts.…”
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Diagnosis and classification of neuromuscular disorders using Bi-LSTM optimized with grey Wolf optimizer for EMG signals by Ruth Keziah Mani, Balakrishnan Nagaraj

“…However, the performance of these models is heavily influenced by hyperparameters such as the number of neurons, hidden layers, and learning rates. …”
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Explainable artificial intelligence with temporal convolutional networks for adverse weather condition detection in driverless vehicles by Samah Alzanin

“…Abstract Autonomous driving has reached significant milestones in research and development over the last few decades. …”
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Optimization of TCN-BiLSTM for dissolved oxygen prediction based on improved sparrow search algorithm by Pei Shi, Mingjie Tang, Quan Wang, Xiaofei Ma

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Detecting Software Anomalies in Robots by Means of One-class Classifiers by Héctor Quintián, Esteban Jove, Francisco Zayas-Gato, Nuño Basurto, Carlos Cambra, Álvaro Herrero

“…While most anomaly detection research has focused on hardware anomalies, this study addresses the underexplored challenge of software anomaly detection in component-based robotic systems. …”
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A unified DNN weight compression framework using reweighted optimization methods by Mengchen Fan, Tianyun Zhang, Xiaolong Ma, Jiacheng Guo, Zheng Zhan, Shanglin Zhou, Minghai Qin, Caiwen Ding, Baocheng Geng, Makan Fardad, Yanzhi Wang

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Bayesian Optimized of CNN-M-LSTM for Thermal Comfort Prediction and Load Forecasting in Commercial Buildings by Chi Nghiep Le, Stefan Stojcevski, Tan Ngoc Dinh, Arangarajan Vinayagam, Alex Stojcevski, Jaideep Chandran

“…To address this energy consumption challenge, a predictive model named Bayesian optimisation Convolution Neural Network Multivariate Long Short-term Memory (BO CNN-M-LSTM) is introduced in this research. The proposed model is designed to perform load forecasting, optimizing energy usage in commercial buildings. …”
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Deep learning application to roughness classification of road surface conditions through an e-scooter’s ride quality by Asher Virin, Lalitphat Khongsomchit, Sakdirat Kaewunruen

“…Three machine learning models—Random Forest Classifier, Extreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM) with k-means clustering—were tested using various hyperparameter tuning, post-processing, and data splitting strategies. …”
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Proto-Caps: interpretable medical image classification using prototype learning and privileged information by Luisa Gallée, Catharina Silvia Lisson, Timo Ropinski, Meinrad Beer, Michael Götz

“…Through extensive hyperparameter studies, we also found optimal model settings, providing a starting point for further research. …”
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Aboveground biomass estimation using multimodal remote sensing observations and machine learning in mixed temperate forest by Shashika Himandi Gardeye Lamahewage, Chandi Witharana, Rachel Riemann, Robert Fahey, Thomas Worthley

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“intelligent Read Across (iRA)”- A tool for read-across-based toxicity prediction of nanoparticles by Souvik Pore, Kunal Roy

“…Experimental evaluation of NP toxicity is resource-intensive and raises ethical issues; therefore, various computational methods are used for toxicity assessments. In this research, we introduce a Python-based tool called “intelligent Read Across (iRA),” which makes predictions using similarity-based read-across algorithms. …”
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Optimized machine learning algorithms with SHAP analysis for predicting compressive strength in high-performance concrete by Samuel Olaoluwa Abioye, Yusuf Olawale Babatunde, Oluwafikejimi Abigail Abikoye, Aisha Nene Shaibu, Bailey Jonathan Bankole

“…Abstract This research examines the application of eight different machine learning (ML) algorithms for predicting the compressive strength of high-performance concrete (HPC). …”
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Linear B-cell epitope prediction for SARS and COVID-19 vaccine design: Integrating balanced ensemble learning models and resampling strategies by Fatih Gurcan

“…This study contributes to vaccine development efforts and the advancement of immunoinformatics research by identifying promising epitope candidates.…”
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An explainable AI-based approach for predicting undergraduate students academic performance by Fatema Tuz Johora, Md Nahid Hasan, Aditya Rajbongshi, Md Ashrafuzzaman, Farzana Akter

“…The accurate prediction of students' academic achievement has garnered considerable attention in the research community due to its importance in understanding students' progress and assisting them in achieving success. …”
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Toward Reliable Post-Disaster Assessment: Advancing Building Damage Detection Using You Only Look Once Convolutional Neural Network and Satellite Imagery by César Luis Moreno González, Germán A. Montoya, Carlos Lozano Garzón

“…This dataset has been publicly released, providing a benchmark for future disaster assessment research. Additionally, we conduct a systematic evaluation of optimization strategies, comparing SGD with momentum, RMSProp, Adam, AdaMax, NAdam, and AdamW. …”
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Optimization of machine learning methods for de-anonymization in social networks by Nurzhigit Smailov, Fatima Uralova, Rashida Kadyrova, Raiymbek Magazov, Akezhan Sabibolda

“…By proposing a scalable and effective framework for analyzing anonymized data in social networks, this research contributes to improved fraud detection and strengthened Internet security. …”
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Eeg based smart emotion recognition using meta heuristic optimization and hybrid deep learning techniques by M Karthiga, E Suganya, S Sountharrajan, Balamurugan Balusamy, Shitharth Selvarajan

“…Abstract In the domain of passive brain-computer interface applications, the identification of emotions is both essential and formidable. Significant research has recently been undertaken on emotion identification with electroencephalogram (EEG) data. …”
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Detecting cognitive impairment in cerebrovascular disease using gait, dual tasks, and machine learning by Vânia Guimarães, Inês Sousa, Miguel Velhote Correia

“…Nested cross-validation was used for model training, hyperparameter tuning, and evaluation. Grid search with cross-validation was used to optimize the hyperparameters of a set of feature selectors and classifiers. …”
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Intelligent System for Reducing Waste and Enhancing Efficiency in Copper Production Using Machine Learning by Bagdaulet Kenzhaliyev, Timur Imankulov, Aksultan Mukhanbet, Sergey Kvyatkovskiy, Maral Dyussebekova, Nurdaulet Tasmurzayev

“…This backward-driven strategy proposed in this research aims to determine optimal ore compositions to achieve desired outputs, reducing waste and energy consumption. …”
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