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Machine learning in aerodynamic shape optimization

Jichao Li, Xiaosong Du, Joaquim R. R. A. Martins • Progress in Aerospace Sciences (2022)

Machine learning (ML) has been increasingly used to aid aerodynamic shape optimization (ASO), thanks to the availability of aerodynamic data and continued developments in deep learning. We review the applications of ML in ASO to date and pr...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.paerosci.2022.100849

Machine Learning in Chemical Engineering: A Perspective

Artur M. Schweidtmann, Erik Esche, Asja Fischer, Marius Kloft et al. • Chemie Ingenieur Technik (2021)

Abstract The transformation of the chemical industry to renewable energy and feedstock supply requires new paradigms for the design of flexible plants, (bio‐)catalysts, and functional materials. Recent breakthroughs in machine learning (ML)...

OPENALEX cc-by DOI: https://doi.org/10.1002/cite.202100083

Machine learning for renewable energy materials

Geun Ho Gu, Juhwan Noh, I. P. Kim, Yousung Jung • Journal of Materials Chemistry A (2019)

Achieving the 2016 Paris agreement goal of limiting global warming below 2 °C and securing a sustainable energy future require materials innovations in renewable energy technologies. Machine learning has demonstrated many successes to accel...

OPENALEX DOI: https://doi.org/10.1039/c9ta02356a

Machine Learning and AI for Risk Management

Saqib Aziz, Michael Dowling • Palgrave studies in digital business & enabling technologies (2018)

We explore how machine learning and artificial intelligence (AI) solutions are transforming risk management. A non-technical overview is first given of the main machine learning and AI techniques of benefit to risk managementRisk management...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1007/978-3-030-02330-0_3

Predicting Stock Price Movements with Combined Deep Learning Models and Two-Tier Metaheuristic Optimization Algorithm

Khalil A. Alruwaitee • Journal of Radiation Research and Applied Sciences (2024)

Predictions on stock market prices are a noble task owing to huge complex, dynamic, and chaotic surroundings. Fast ups and downs arise in the stock market due to influences from foreign merchandise, such as sensitive political, stockholder,...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jrras.2024.101172

Using Network-Based Machine Learning to Predict Transcription Factors Involved in Drought Resistance

Chirag Gupta, Venkategowda Ramegowda, Supratim Basu, Andy Pereira • Frontiers in Genetics (2021)

Gene regulatory networks underpin stress response pathways in plants. However, parsing these networks to prioritize key genes underlying a particular trait is challenging. Here, we have built the Gene Regulation and Association Network (GRA...

DOAJ Open Access (DOAJ) DOI: 10.3389/fgene.2021.652189

Learning metal microstructural heterogeneity through spatial mapping of diffraction latent space features

Mathieu Calvat, Chris Bean, Dhruv Anjaria, Hyoungryul Park et al. • npj Computational Materials (2025)

Abstract To leverage advancements in machine learning for metallic materials design and property prediction, it is crucial to develop a data-reduced representation of metal microstructures that surpasses the limitations of current physics-b...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41524-025-01770-8

Machine learning insight in quality control and maintenance management of drilling mud pumps

Xiaoming Wu, Jingxuan Chang, Chengcheng Long, Hamzeh Ghorbani • Journal of Big Data (2026)

Abstract This study proposes a machine learning-based framework for predictive maintenance and quality control of drilling mud pumps, targeting critical operational challenges such as equipment failure, downtime, and high maintenance costs....

DOAJ Open Access (DOAJ) DOI: 10.1186/s40537-026-01475-9

On the use of aspect-based sentiment analysis of Twitter data to explore the experiences of African Americans during COVID-19

Meghna Chaudhary, Kristin Kosyluk, Sylvia Thomas, Tempestt Neal • Scientific Reports (2023)

Abstract According to data from the U.S. Center for Disease Control and Prevention, as of June 2020, a significant number of African Americans had been infected with the coronavirus disease, experiencing disproportionately higher death rate...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-023-37592-1

Unraveling the relationship between key aroma components and sensory properties of fragrant peanut oils based on flavoromics and machine learning

Binfang Hu, Chunhua Zhang, Baijun Chu, Peishan Gu et al. • Food Chemistry: X (2023)

Key aroma components of 33 fragrant peanut oils with different aroma types were screened by combined using flavoromics and machine learning. A total of 108 volatile compounds were identified and 100 kinds of them were accurately quantified,...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.fochx.2023.100880