Long short-term memory (LSTM) networks for precision prediction of Schottky barrier photodiode behavior at different illumination levels by Gökalp Tulum, Sajjad Nematzadeh, İlke Taşçıoğlu, Şemsettin Altındal, Fahrettin Yakuphanoğlu

“…Abstract This study has focused on modeling and predicting the electrical properties and parameters of CdZnO interlayered Al/p-Si Schottky Diodes (SDs) using the Long Short-Term Memory (LSTM) algorithm. …”
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A High-Resolution Spectral Analysis Method Based on Fast Iterative Least Squares Constraints by Yanyan Ma, Haixia Kang, Weifeng Luo, Yunxiao Zhang, Lintao Luo

Subjects: “…thickness prediction…”
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Optimizing Heart-Kidney Interaction for Cancer Detection Through Physiological Process Simulation as a Decision Support System by Najmeh Sadat Jaddi, Salwani Abdullah, Zalinda Othman, Yazrina Yahya, Mohd Zakree Ahmad Nazri, Say Leng Goh, Fatemeh Alvankarian, Jafar Alvankarian

Subjects: “…Heart-kidney algorithm…”
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Bridging the Gap Between Machine Learning and Medicine: A Critical Evaluation of the Dworak Regression Grade in Rectal Cancer by Camille Raets, Chaimae El Aisati, Amir L. Rifi, Mark De Ridder, Koen Putman, Johan De Mey, Alexandra Sermeus, Kurt Barbe

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Novel disctete grey Bernoulli seasonal model with a time powter term for predicting monthly carbon dioxide emissions in the United States by Jianming Jiang, Yandong Ban, Sheng Nong

“…This study proposes a more efficient discrete grey prediction model to describe the seasonalvariation trends of carbon dioxide emissions. …”
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A simplified approach for efficiency analysis of machine learning algorithms by Muthuramalingam Sivakumar, Sudhaman Parthasarathy, Thiyagarajan Padmapriya

“…This article presents a comprehensive framework for evaluating ML algorithm efficiency by incorporating metrics, such as training time, prediction time, memory usage, and computational resource utilization. …”
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Predicting the Magnitude of Earthquakes Using Grammatical Evolution by Constantina Kopitsa, Ioannis G. Tsoulos, Vasileios Charilogis

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Optimal Driving Torque Control Strategy for Front and Rear Independently Driven Electric Vehicles Based on Online Real-Time Model Predictive Control by Hang Yin, Chao Ma, Haifeng Wang, Zhihao Sun, Kun Yang

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AN ONBOARD IMAGE RECOGNITION MODULE FOR MONITORING SYSTEMS: METHODS AND ALGORITHMS by V. A. Kovalev, A. A. Kalinovsky, A. A. Dmitruk

“…The methods and algorithms of a compact on-board image recognition module to be used as a part of monitoring systems is presented. …”
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Review and classification of trajectory summarisation algorithms: From compression to segmentation by Daniel Amigo, David Sánchez Pedroche, Jesús García, José Manuel Molina

“…With the continuous development and cost reduction of positioning and tracking technologies, a large amount of trajectories are being exploited in multiple domains for knowledge extraction. …”
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Quantifying the impact of precision errors on quantum approximate optimization algorithms by Gregory Quiroz, Paraj Titum, Phillip Lotshaw, Pavel Lougovski, Kevin Schultz, Eugene Dumitrescu, Itay Hen

“…The quantum approximate optimization algorithm (QAOA) is a hybrid quantum-classical algorithm that seeks to achieve approximate solutions to optimization problems by iteratively alternating between intervals of controlled quantum evolution. …”
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Paradigm predictive analysis of two-phase Eyring–Powell fluid flow over a vertical stretching sheet with temperature-dependent viscosity by multilayer neural networks by Zahoor Shah, Hamza Iqbal, Waqar Azeem Khan, Taseer Muhammad, Muhammad Shoaib

“…Deep-learning neural networks optimized with the Levenberg-Marquardt algorithm (DLNNs-LMA) is a supervised AI-based approach that is used to analyze the Eyring Powell fluid in a two-phase flow (EPFM-TPF) with dust particles and at temperature-dependent viscosity. …”
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Weed detection on embedded systems using computer vision algorithms by D. Shadrin, S. Illarionova, R. Kasatov, M. Akimenkova, G. Rudensky, E. Erhan

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Machine learning approach for revealing the nickel grade and recovery optimization in reduction process of laterite ores by Vuri Ayu Setyowati, Fakhreza Abdul

“…Data sets were collected from published studies that feature nickel ore grade (Ni and Fe content) and reduction process (temperature, additives, reductant, etc.), while prediction models for Ni grade and recovery were formed from four types of regression algorithms. …”
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Sustainable Mineral Processing Technologies Using Hybrid Intelligent Algorithms by Olga Shiryayeva, Batyrbek Suleimenov, Yelena Kulakova

“…The optimization is performed using a constrained Interior-Point algorithm. The model demonstrates high predictive accuracy, with a mean squared error (MSE) below 0.01. …”
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Comparison of Detection and Classification Algorithms Using Boolean and Fuzzy Techniques by Rahul Dixit, Harpreet Singh

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Association of weight-adjusted waist index and body mass index with chronic low back pain in American adults: a retrospective cohort study and predictive model development based on machine learning algorithms (NHANES 2009–2010) by Weiye Zhang, Weiye Zhang, Yan Li, Pengwei Shao, Yuxuan Du, Ke Zhao, Jiawen Zhan, Lee A. Tan

“…Six machine learning algorithms were employed to predict CLBP occurrence and identify the optimal algorithm.ResultsA total of 4,687 participants were included. …”
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Methods and Algorithms for Decision-Making in Agro-Industrial Environmental Management by Olga Ivashchuk, Vyacheslav Fedorov, Zhanat Kenzhebayeva, Oleg Ivashchuk, Moldir Allaniyazova, Kaiyrbek Makulov, Gulnar Kaziyeva

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Predicting Affinity Through Homology (PATH): Interpretable binding affinity prediction with persistent homology. by Yuxi Long, Bruce R Donald

“…Compared to current binding affinity prediction algorithms, PATH+ shows similar or better accuracy and is more generalizable across orthogonal datasets. …”
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The role of artificial intelligence in vascular care by Nehaar Nimmagadda, BS, Edouard Aboian, MD, Sharon Kiang, MD, Uwe Fischer, MD

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