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K-means clustering algorithms: A comprehensive review, variants analysis, and advances in the era of big data
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 …
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
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 …
complex challenges in recent years in various application areas, such as medical, financial …
Data clustering: application and trends
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 …
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 …
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
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 …
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
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 …
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
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 …
(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
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 …
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
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 …
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
This review paper delves into synergistic integration of artificial intelligence (AI) and
machine learning (ML) with high-throughput experimentation (HTE) in the field of …
machine learning (ML) with high-throughput experimentation (HTE) in the field of …