Browsing by Subject "Clusterings"
Now showing items 1-13 of 13
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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 ... -
A combined clustering/symbolic regression framework for fluid property prediction
(2022)Symbolic regression techniques are constantly gaining ground in materials informatics as the machine learning counterpart capable of providing analytical equations exclusively derived from data. When the feature space is ... -
Convolutional Variational Autoencoders for Image Clustering
(2021)The problem of data clustering is one of the most fundamental and well studied problems of unsupervised learning. Image clustering, refers to one of the most challenging specifications of clustering, concerning image data. ... -
Data and programs in support of network analysis of genes and their association with diseases
(2016)The network-based approaches that were employed in order to depict the relationships between human genetic diseases and their associated genes are described. Towards this direction, monopartite disease-disease and gene-gene ... -
Diagnosis of Induced Resistance State in Tomato Using Artificial Neural Network Models Based on Supervised Self-Organizing Maps and Fluorescence Kinetics
(2022)The aim of this study was to develop three supervised self-organizing map (SOM) models for the automatic recognition of a systemic resistance state in plants after application of a resistance inducer. The pathosystem ... -
A Force Estimation Sensor System TestBed for Geological Phenomena Analysis based on Biomimetic
(2022)Our work focuses, on designing and proposing a force estimation sensor system for Geological phenomena data collection and analysis, based on Biomimetic. In this sense, biomimetic term, is used, as proposed by Schmitt in ... -
A hybrid metaheuristics-based algorithm for electricity load curves profiling
(2021)Clustering-based load profiling utilizes unsupervised machine learning algorithms to form homogenous clusters composed by electricity load curves with similar characteristics. Due to the importance of load profiling in ... -
Improving Hierarchical Short Text Clustering through Dominant Feature Learning
(2022)This paper focuses on the popular problem of short text clustering. Since the short text documents typically exhibit high degrees of data sparseness and dimensionality, the problem in question is generally considered more ... -
On Using Raft Over Networks: Improving Leader Election
(2022)Raft is a state-of-the-art consensus algorithm for state replication over a distributed system of nodes. According to Raft, all state updates occurring anywhere in the system are forwarded to the leader, which is elected ... -
RLAC: Random Line Approximation Clustering
(2021)We explore how Random Projections can be used as an Approximate method for Projection Pursuit Clustering in high dimensional data. Traditional data transformations such as PCA for dimensionality reduction have been shown ... -
A Scalable Short-Text Clustering Algorithm Using Apache Spark
(2021)Short text clustering deals with the problem of grouping together semantically similar documents with small lengths. Nowadays, huge amounts of text data is being generated by numerous applications such as microblogs, ... -
Use of Artificial Neural Networks for Short Term Load Forecasting
(2021)In order to schedule an effective service and economical capital extension of an electric power distribution system, the system administrator must be able to predict the need for power delivery. Short Term Load Forecasting ...