K-means clustering algorithms: A comprehensive review, variants analysis, and advances in the era of big data

AM Ikotun, AE Ezugwu, L Abualigah, B Abuhaija… - Information …, 2023‏ - Elsevier
Advances in recent techniques for scientific data collection in the era of big data allow for the
systematic accumulation of large quantities of data at various data-capturing sites. Similarly …

Machine learning in medical applications: A review of state-of-the-art methods

M Shehab, L Abualigah, Q Shambour… - Computers in Biology …, 2022‏ - Elsevier
Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …

Data clustering: application and trends

GJ Oyewole, GA Thopil - Artificial intelligence review, 2023‏ - Springer
Clustering has primarily been used as an analytical technique to group unlabeled data for
extracting meaningful information. The fact that no clustering algorithm can solve all …

[کتاب][B] Metode Penelitian Berbagai Bidang Keilmuan (Panduan & Referensi)

MB Ibrahim, FP Sari, LPI Kharisma, I Kertati, P Artawan… - 2023‏ - books.google.com
Penelitian merupakan kegiatan yang sangat penting dalam memajukan ilmu pengetahuan
dan teknologi. Oleh karena itu, para peneliti harus memiliki pemahaman yang baik tentang …

Applications of machine learning techniques for enhancing nondestructive food quality and safety detection

Y Lin, J Ma, Q Wang, DW Sun - Critical Reviews in Food Science …, 2023‏ - Taylor & Francis
In considering the need of people all over the world for high-quality food, there has been a
recent increase in interest in the role of nondestructive and rapid detection technologies in …

Application of machine learning in water resources management: a systematic literature review

F Ghobadi, D Kang - Water, 2023‏ - mdpi.com
In accordance with the rapid proliferation of machine learning (ML) and data management,
ML applications have evolved to encompass all engineering disciplines. Owing to the …

[HTML][HTML] Internet of Intelligent Things: A convergence of embedded systems, edge computing and machine learning

F Oliveira, DG Costa, F Assis, I Silva - Internet of Things, 2024‏ - Elsevier
This article comprehensively reviews the emerging concept of Internet of Intelligent Things
(IoIT), adopting an integrated perspective centred on the areas of embedded systems, edge …

Person-centered modeling: Techniques for studying associations between people rather than variables

SE Woo, J Hofmans, B Wille… - Annual Review of …, 2024‏ - annualreviews.org
The goal of person-centered methods is to identify subpopulations of individuals based on
within-group similarity of data relative to between-group variability. In this article, we provide …

Machine learning-assisted self-powered intelligent sensing systems based on triboelectricity

Z Tian, J Li, L Liu, H Wu, X Hu, M **e, Y Zhu, X Chen… - Nano Energy, 2023‏ - Elsevier
The advancement of 5G and the Internet of Things (IoT) has ushered in an era of super-
interconnected intelligence, which promises high-quality social development. Triboelectric …

From characterization to discovery: artificial intelligence, machine learning and high-throughput experiments for heterogeneous catalyst design

J Benavides-Hernández, F Dumeignil - ACS Catalysis, 2024‏ - ACS Publications
This review paper delves into synergistic integration of artificial intelligence (AI) and
machine learning (ML) with high-throughput experimentation (HTE) in the field of …