Grid Search Based Hyperparameter-Tuned Deep Learning Model for Osteoporosis Diagnosis with Bi-Cubic Interpolation of X-Ray Images by Ruhul Amin, Md.Shamim Reza, Dewan Ahmed Muhtasim, Jungpil Shin, Md. Maniruzzaman, Md.Mahfujul Hasan

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Investigation of void content in Borassus flabellifer fiber/epoxy bio-nanocomposite using hyperparameter tuned ANN and response surface methodology optimisation by Suresh Thirupathi, Venkatachalam Gopalan, Elango Mallichetty

“…The optimized combination (1 wt% fiber content, 75 µm fiber mesh size and 1 wt% h-BN nanofiller) yielded 1.90% lowest void content after experimentation. This research provides fundamental understanding of the void mechanisms concerning bio-nano composites and presents an optimal predictor model that minimizes voids. …”
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Estimation of elbow flexion torque using equilibrium optimizer on feature selection of NMES MMG signals and hyperparameter tuning of random forest regression by Raphael Uwamahoro, Raphael Uwamahoro, Kenneth Sundaraj, Farah Shahnaz Feroz

“…Convergence analysis further revealed that the GLEO algorithm exhibited a superior learning capability compared to EO.ConclusionThis study underscores the potential of the hybrid GLEO approach in selecting highly informative features and optimizing hyperparameters for machine learning models. These advancements are essential for evaluating muscle function and represent a significant advancement in musculoskeletal biomechanics research.…”
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iYOLOV7-TPE-SS: Leveraging Improved YOLO Model With Multilevel Hyperparameter Optimization for Road Damage Detection on Edge Devices by Haniah Mahmudah, Aulia Siti Aisjah, Syamsul Arifin, Catur Arif Prastyantyo

“…The iYOLOV7 provides real-time processing on edge devices that have limited storage, low-speed processors, and memory. The research investigates how leveraging multilevel hyperparameter optimization using the TPE-SS model improves system performance where road damage is detected. …”
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A novel prediction of the PV system output current based on integration of optimized hyperparameters of multi-layer neural networks and polynomial regression models by Hussein Mohammed Ridha, Hashim Hizam, Seyedali Mirjalili, Mohammad Lutfi Othman, Mohammad Effendy Ya’acob, Noor Izzri Bin Abdul Wahab, Masoud Ahmadipour

“…The IMGO is employed to determine the appropriate hyperparameters of the model, ranging from the number of neurons in the hidden layers and learning rate. …”
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Lightweight convolutional neural networks using nonlinear Lévy chaotic moth flame optimisation for brain tumour classification via efficient hyperparameter tuning by Amin Abdollahi Dehkordi, Mehdi Neshat, Alireza Khosravian, Menasha Thilakaratne, Ali Safaa Sadiq, Seyedali Mirjalili

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Harmony search for hyperparameters optimization of a low resource language transformer model trained with a novel parallel corpus Ocelotl Nahuatl – Spanish by Máximo Enrique Pacheco Martínez, Maya Carrillo Ruiz, María de Lourdes Sandoval Solís

“…Given this condition, it is vital to provide as much support to the language as possible. This research aims to enhance the BLEU score in machine translation by applying the harmony search heuristic method to state-of-the-art transformers models. …”
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GA4RF: An Effective Fall Detection System Through Optimizing Random Forest Hyperparameters Using Genetic Algorithm With Mobile Sensor Data by Ha-Nam Nguyen, Hong-Lam Le, Ngo-Thi-Thu-Trang, Duc-Nhan Nguyen

“…Research and development of highly accurate falling detection systems (FDSs) for individuals with medical conditions or the elderly are crucial for mitigating the risks associated with falls. …”
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Comprehensive Performance Assessment of Multi-Neural Ensemble Model for Mortality Prediction in ICU by M. Fathima Begum, Subhashini Narayan

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Developing a machine learning-based methodology for optimal hyperparameter determination—A mathematical modeling of high-pressure and high-temperature drilling fluid behavior by Luis H. Quitian-Ardila, Yamid J. Garcia-Blanco, Angel De J. Rivera, Raquel S. Schimicoscki, Muhammad Nadeem, Oriana Palma Calabokis, Vladimir Ballesteros-Ballesteros, Admilson T. Franco

“…The dataset used in this study was obtained from extensive rheometric tests of water-based and olefin-based drilling fluids in steady-state flow curves. The optimal hyperparameters were guided by performance metrics and compared with alternative models such as Power-law and Herschel-Bulkley rheological models. …”
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Software Defect Prediction For Quality Evaluation Using Learning Techniques Ensemble Stacking by Muhammad Romadhona Kusuma, Windu Gata, Sigit Kurniawan, Dedi Dwi Saputra, Supriadi Panggabean

“…This research aims to improve the software quality and effectiveness of zakat management by the National Amil Zakat Agency (BAZNAS) through the development of a software defect prediction model (SDPM). …”
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Evaluation of Machine Learning Models for Enhancing Sustainability in Additive Manufacturing by Waqar Shehbaz, Qingjin Peng

“…Additive manufacturing (AM) presents significant opportunities for advancing sustainability through optimized process control and material utilization. This research investigates the application of machine learning (ML) models to directly associate AM process parameters with sustainability metrics, which is often a challenge by experimental methods alone. …”
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Enhanced Crop Leaf Area Index Estimation via Random Forest Regression: Bayesian Optimization and Feature Selection Approach by Jun Zhang, Jinpeng Cheng, Cuiping Liu, Qiang Wu, Shuping Xiong, Hao Yang, Shenglong Chang, Yuanyuan Fu, Mohan Yang, Shiyu Zhang, Guijun Yang, Xinming Ma

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Optimizing travel time reliability with XAI: A Virginia interstate network case using machine learning and meta-heuristics by Navid Khorshidi, Shahriar Afandizadeh Zargari, Soheil Rezashoar, Hamid Mirzahossein

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Enhancing Asset Reliability and Sustainability: A Comparative Study of Neural Networks and ARIMAX in Predictive Maintenance by Salvador Perez-Garcia, Cristina Gonzalez-Gaya, Miguel A. Sebastian

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Debris Flow Susceptibility Prediction Using Transfer Learning: A Case Study in Western Sichuan, China by Tiezhu Li, Qidi Huang, Qigang Chen

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A novel integrated TDLAVOA-XGBoost model for tool wear prediction in lathe and milling operations by Zhongyuan Che, Chong Peng, Chi Wang, Jikun Wang

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Automated Machine Learning for Optimized Load Forecasting and Economic Impact in the Greek Wholesale Energy Market by Nikolaos Koutantos, Maria Fotopoulou, Dimitrios Rakopoulos

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XAI-BO: an architecture using Grad-CAM technique to evaluate Bayesian optimization algorithms on deep learning models by Luyl-Da Quach, Nguyen Quoc Khang, Nguyen Thai-Nghe, Chi-Ngon Nguyen

“…Additionally, the research utilizes Grad-CAM to clarify the positive impact of parameter reduction when using the BO algorithm. …”
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Anomaly detection of smart grid stealing network attacks based on deep autoencoder by Huang Yan, Li Jincan, Yang Xiaqin, Li Pei, Li Zi

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