[HTML][HTML] Deakin microgrid digital twin and analysis of AI models for power generation prediction
To achieve carbon neutral by 2025, Deakin University launched a AUD 23 million
Renewable Energy Microgrid in 2020 with a 7-megawatt solar farm, the largest at an …
Renewable Energy Microgrid in 2020 with a 7-megawatt solar farm, the largest at an …
A novel insider attack and machine learning based detection for the internet of things
Due to the widespread functional benefits, such as supporting internet connectivity, having
high visibility and enabling easy connectivity between sensors, the Internet of Things (IoT) …
high visibility and enabling easy connectivity between sensors, the Internet of Things (IoT) …
Streaming data analysis: Clustering or classification?
This article is a position paper about models and algorithms that are generally called
“stream clustering.” Semantics and methods used in this field are often co-opted from static …
“stream clustering.” Semantics and methods used in this field are often co-opted from static …
Im-iad: Industrial image anomaly detection benchmark in manufacturing
Image anomaly detection (IAD) is an emerging and vital computer vision task in industrial
manufacturing (IM). Recently, many advanced algorithms have been reported, but their …
manufacturing (IM). Recently, many advanced algorithms have been reported, but their …
[图书][B] Elementary Cluster Analysis: Four Basic Methods that (Usually) Work
JC Bezdek - 2022 - taylorfrancis.com
The availability of packaged clustering programs means that anyone with data can easily do
cluster analysis on it. But many users of this technology don't fully appreciate its many …
cluster analysis on it. But many users of this technology don't fully appreciate its many …
ML-aVAT: A Novel 2-Stage Machine-Learning Approach for Automatic Clustering Tendency Assessment
H Mittal, JS Laxman, D Kumar - Big Data Research, 2023 - Elsevier
Clustering tendency assessment, which aims to deduce if a dataset contains any cluster
structure, and, if it does, how many clusters it has, is a critical problem in exploratory data …
structure, and, if it does, how many clusters it has, is a critical problem in exploratory data …
Time and memory scalable algorithms for clustering tendency assessment of big data
KV Deshpande, D Kumar - Information Sciences, 2024 - Elsevier
Large-volume and high-dimensional big datasets are being generated quickly. They are
expected to provide data-driven solutions for various pressing challenges such as …
expected to provide data-driven solutions for various pressing challenges such as …
A novel algorithm for evaluating clustering propensity of IoT-generated spatio-temporal data geared for distributed systems
KV Deshpande, D Kumar - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
Spatio-temporal (ST) data generated by Internet of Things (IoT) devices is expected to grow
exponentially in the future on a massive scale. The clustering of this massive amount of …
exponentially in the future on a massive scale. The clustering of this massive amount of …
Scalable Cluster Tendency Assessment for Streaming Activity Data using Recurring Shapelets
Automatic interpretation of cluster structure in rapidly arriving data streams is essential for
timely detection of interesting events. Human activities often contain bursts of repeating …
timely detection of interesting events. Human activities often contain bursts of repeating …
An Improved Visual Assessment with Data-Dependent Kernel for Stream Clustering
The advances of 5G and the Internet of Things enable more devices and sensors to be
interconnected. Unlike traditional data, the large amount of data generated from various …
interconnected. Unlike traditional data, the large amount of data generated from various …