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 …
Internet of things (iot) security intelligence: a comprehensive overview, machine learning solutions and research directions
Abstract The Internet of Things (IoT) is one of the most widely used technologies today, and
it has a significant effect on our lives in a variety of ways, including social, commercial, and …
it has a significant effect on our lives in a variety of ways, including social, commercial, and …
Machine learning: Algorithms, real-world applications and research directions
IH Sarker - SN computer science, 2021 - Springer
In the current age of the Fourth Industrial Revolution (4 IR or Industry 4.0), the digital world
has a wealth of data, such as Internet of Things (IoT) data, cybersecurity data, mobile data …
has a wealth of data, such as Internet of Things (IoT) data, cybersecurity data, mobile data …
Using machine learning approaches for multi-omics data analysis: A review
With the development of modern high-throughput omic measurement platforms, it has
become essential for biomedical studies to undertake an integrative (combined) approach to …
become essential for biomedical studies to undertake an integrative (combined) approach to …
Data science and analytics: an overview from data-driven smart computing, decision-making and applications perspective
IH Sarker - SN Computer Science, 2021 - Springer
The digital world has a wealth of data, such as internet of things (IoT) data, business data,
health data, mobile data, urban data, security data, and many more, in the current age of the …
health data, mobile data, urban data, security data, and many more, in the current age of the …
Machine learning for intelligent data analysis and automation in cybersecurity: current and future prospects
IH Sarker - Annals of Data Science, 2023 - Springer
Due to the digitization and Internet of Things revolutions, the present electronic world has a
wealth of cybersecurity data. Efficiently resolving cyber anomalies and attacks is becoming a …
wealth of cybersecurity data. Efficiently resolving cyber anomalies and attacks is becoming a …
A comprehensive survey on deep clustering: Taxonomy, challenges, and future directions
Clustering is a fundamental machine learning task, which aim at assigning instances into
groups so that similar samples belong to the same cluster while dissimilar samples belong …
groups so that similar samples belong to the same cluster while dissimilar samples belong …
Digital twin: Values, challenges and enablers from a modeling perspective
Digital twin can be defined as a virtual representation of a physical asset enabled through
data and simulators for real-time prediction, optimization, monitoring, controlling, and …
data and simulators for real-time prediction, optimization, monitoring, controlling, and …
A quantitative discriminant method of elbow point for the optimal number of clusters in clustering algorithm
C Shi, B Wei, S Wei, W Wang, H Liu, J Liu - EURASIP journal on wireless …, 2021 - Springer
Clustering, a traditional machine learning method, plays a significant role in data analysis.
Most clustering algorithms depend on a predetermined exact number of clusters, whereas …
Most clustering algorithms depend on a predetermined exact number of clusters, whereas …
A survey of quantum computing for finance
Quantum computers are expected to surpass the computational capabilities of classical
computers during this decade and have transformative impact on numerous industry sectors …
computers during this decade and have transformative impact on numerous industry sectors …