Results 51 to 60 of about 80,307 (206)
IEEE AccessArtificial Intelligence (AI) is a transformative force driving innovation, yet tracking AI-related advancements remains challenging due to the rapid pace of development and unstructured data from platforms like GitHub.
Inna Novalija +13 more
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All-chain Sets Mining Algorithm for Multi-scale Nearest Time Series [PDF]
Jisuanji kexueMining all-chain set in the time series is an emerging area.To the best of our knowledge,no method has been proposed to mining all-chain sets over multi-scale nearest time series.In this paper,the problem of mining all-chain sets over multi-scale nearest
WANG Shaopeng, FENG Chunkai
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Visual Mining of Spatial Time Series Data [PDF]
, 2004 CommonGIS is a system comprising a number of tools for visual data analysis. In this paper we demonstrate our recent developments for analysis of spatial time series data.
Gennady L. Andrienko +2 more
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Power Transformer Failure Prediction: Classification in Imbalanced Time Series
U.Porto Journal of Engineering, 2017 This paper describes a study on applying data mining techniques to power transformer failure prediction. The data set used consisted not only on DGA tests, but also in other tests done to the transformer’s insulating oil.
Eduardo e Oliveira +3 more
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Mining the past to forecast the future: comments [PDF]
, 2009 In forecasting, data mining is frequently perceived as a distinct technological discipline without immediate relevance to the challenges of time series prediction.
Crone, S
core
A literature survey of shapelet quality measures for time series classification [PDF]
PeerJ Computer ScienceWith the rapid development of the Internet of Things, time series classification (TSC) has gained significant attention from researchers due to its applications in various real-world fields, including electroencephalogram/electrocardiogram classification,
Teng Li, Xiaodong Guo, Cun Ji
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catch22: CAnonical time-series CHaracteristics [PDF]
, 2019 Capturing the dynamical properties of time series concisely as interpretable feature vectors can enable efficient clustering and classification for time-series applications across science and industry.
Knaute, Philip +5 more
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Understanding Open Source Software Evolution Using Fuzzy Data Mining Algorithm for Time Series Data
Advances in Fuzzy Systems, 2016 Source code management systems (such as Concurrent Versions System (CVS), Subversion, and git) record changes to code repositories of open source software projects.
Munish Saini +2 more
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Recent Advances in Mining Time Series Data [PDF]
, 2005 Much of the world’s supply of data is in the form of time series. Furthermore, as we shall see, many types of data can be meaningfully converted into ”time series”, including text, DNA, video, images etc. The last decade has seen an explosion of interest in mining time series data from the academic community.
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Time Series Optimization on Data Mining
Journal of Physics: Conference Series, 2019 Abstract Forecasting is one of the important topics in the data mining field, such as, predictions, weather forecasting, predictions of academic achievement. Another topic associated with forecasting through a series of data that depends on the time period is called time series.
Relita Buaton +7 more
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