Research on Thickness Error Optimization Method of Rolling System Based on Improved Sparrow Search Algorithm–Bidirectional Long Short-Term Memory Network–Attention by Qingyun Wu, Xinchen Li, Jiafei Ji, Bowen Xing

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Research on productivity prediction method of infilling well based on improved LSTM neural network: A case study of the middle-deep shale gas in South Sichuan by GUAN Wenjie, PENG Xiaolong, ZHU Suyang, YANG Chen, PENG Zhen, MA Xiaoran

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Leveraging advanced deep learning and machine learning approaches for snow depth prediction using remote sensing and ground data by Haytam Elyoussfi, Abdelghani Boudhar, Salwa Belaqziz, Mostafa Bousbaa, Karima Nifa, Bouchra Bargam, Abdelghani Chehbouni

“…The dataset was processed and normalized for optimal performance, and hyperparameters were fine-tuned using a randomized search method. …”
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Statistical mechanics of dynamical system identification by Andrei A. Klishin, Joseph Bakarji, J. Nathan Kutz, Krithika Manohar

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Pulse engineering via projection of response functions by Nicolas Heimann, Lukas Broers, Ludwig Mathey

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Universal scaling laws of absorbing phase transitions in artificial deep neural networks by Keiichi Tamai, Tsuyoshi Okubo, Truong Vinh Truong Duy, Naotake Natori, Synge Todo

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Scalable circuit depth reduction in feedback-based quantum optimization with a quadratic approximation by Don Arai, Ken N. Okada, Yuichiro Nakano, Kosuke Mitarai, Keisuke Fujii

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Analysing and Forecasting the Energy Consumption of Healthcare Facilities in the Short and Medium Term. A Case Study by Ali Koç, Serap Ulusam Seçkiner

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Evaluation of Prediction Performances of Deep Learning Models for the Aerodynamic Characteristics of Flettner Rotors by Seo Janghoon, Park Jung Yoon, Ma Juhwan, Kim Young Bu, Park Dong-Woo

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A novel method for power transformer fault diagnosis considering imbalanced data samples by Jun Chen, Yong Wang, Lingming Kong, Yilong Chen, Mianzhi Chen, Qian Cai, Gehao Sheng

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Harnessing machine learning approach for hardness optimization of Al-Si alloy composites reinforced with coconut shell ash by M Poornesh, Shreeranga Bhat, Mithun Kanchan

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Prediction of UHPC mechanical properties using optimized hybrid machine learning model with robust sensitivity and uncertainty analysis by ZhiGuang Zhou, Jagaran Chakma, Md Ahatasamul Hoque, Vaskar Chakma, Asif Ahmed

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Artificial Neural Network and response surface methodology modeling-based optimization approach for the ultrasonication-assisted extraction of phenolics from mustard (BARI Sharisa-... by Md. Waziur Rahman Chy, Tanvir Ahmed, Robin Sarkar, Md. Zohurul Islam, Md. Rahmatuzzaman Rana

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Predicting biogas production in real scale anaerobic digester under dynamic conditions with machine learning approach by M. Erdem Isenkul, Sevgi Güneş-Durak, Yasemin Poyraz Kocak, İnci Pir, Mertol Tüfekci, Güler Türkoğlu Demirkol, Selçuk Sevgen, Aslı Seyhan Çığgın, Neşe Tüfekci

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Machine Learning Methods for Predicting Cardiovascular Diseases: A Comparative Analysis by Aiym B. Temirbayeva, Arshyn Altybay

“…The primary research question is to identify which algorithm demonstrates the best predictive performance for heart disease diagnosis. …”
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Review of machine learning-assisted multi-property design of high-entropy alloys: phase structure, mechanical, tribological, corrosion, and hydrogen storage properties by Yunlong Li, Jialiang Tan, Cheng Qian, Xiaochao Liu, Rui Nie

“…Accordingly, this paper reviews recent advancements in the application of ML to HEAs research. It outlines the basic workflow, including data collection, data preprocessing, ML algorithm selection, hyperparameter optimization, model evaluation and model interpretability. …”
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Intelligent prediction and oriented design of high-hardness high-entropy ceramics by Anzhe Wang, Jicheng Liu, Linwei Guo, Kejie Qu, Haishen Xie, Yawei Li, Bin Du

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Predicting the high-strain-rate deformation behavior and constructing processing maps of 304L stainless steel through machine learning and deep learning by M. Ghaffari Farid, H.R. Abedi, R. Ghasempour, A. Taylor, S. Khoddam, P.D. Hodgson

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Machine Learning for the estimation of foliar nitrogen content in pineapple crops using multispectral images and Internet of Things (IoT) platforms by Jorge Enrique Chaparro, José Edinson Aedo, Felipe Lumbreras Ruiz

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Comparison of 7 artificial intelligence models in predicting venous thromboembolism in COVID-19 patients by Indika Rajakaruna, Mohammad Hossein Amirhosseini, Mike Makris, Mike Laffan, Yang Li, Deepa J. Arachchillage

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