Πλοήγηση ανά Θέμα "K-means clustering"
Αποτελέσματα 1-9 από 9
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Calculating material properties with purely data-driven methods
(2022)Unsupervised machine learning (ML) methods are incorporated in this work to depict correlations and investigate hidden relations between data points that refer to a diffusion coefficient dataset for the Lennard-Jones (LJ) ... -
Clustering Informed MLP Models for Fast and Accurate Short-Term Load Forecasting
(2022)The stable and efficient operation of power systems requires them to be optimized, which, given the growing availability of load data, relies on load forecasting methods. Fast and highly accurate Short-Term Load Forecasting ... -
Evaluating the Effects of Modern Storage Devices on the Efficiency of Parallel Machine Learning Algorithms
(2020)Big Data analytics is presently one of the most emerging areas of research for both organizations and enterprises. The requirement for deployment of efficient machine learning algorithms over huge amounts of data led to ... -
High Performance Clustering Techniques: A Survey
(2020)We are living in a world of heavy data bombing and the term Big Data is a key issue these days. The variety of applications, where huge amounts of data are produced (can be expressed in PBs and more), is great in many areas ... -
Improving Multiclass Classification of Cybersecurity Breaches in Railway Infrastructure using Imbalanced Learning
(2021)Machine learning approaches and algorithms are spreading in wide areas in research and technology. Cybersecurity breaches are the common anomalies for networked and distributed infrastructures which are monitored, registered, ... -
A machine-learning clustering approach for intrusion detection to IoT devices
(2019)Nowadays we see the sharp increase in smart devices on the internet and in the network of things. An ever increasing problem with these devices is their protection against malware and internet attacks because of their ... -
A New Topology-Preserving Distance Metric with Applications to Multi-dimensional Data Clustering
(2019)In many cases of high dimensional data analysis, data points may lie on manifolds of very complex shapes/geometries. Thus, the usual Euclidean distance may lead to suboptimal results when utilized in clustering or visualization ... -
Optimized Data-Driven Models for Short-Term Electricity Price Forecasting Based on Signal Decomposition and Clustering Techniques
(2022)In recent decades, the traditional monopolistic energy exchange market has been replaced by deregulated, competitive marketplaces in which electricity may be purchased and sold at market prices like any other commodity. ... -
Visual exploration of energy use in eu 28: Dynamics, patterns, policies
(2021)The paper places emphasis on primary energy resources, their covariation, and their correlation with socioeconomic factors and aims to provide a systematic analysis of their development over time. The analysis uses evidence ...