Data stream classification with ant colony optimisation
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22809
Abstract: Data stream mining has recently emerged in response to the rapidly increasing continuous data generation. While the majority of Ant Colony Optimisation (ACO) rule induction algorithms have proved to be successful in producing both accurate… read more here.
Keywords: stream classification; colony optimisation; stream; data stream ... See more keywords
Impacts from assimilation of one data stream of AMSU‐A and MHS radiances on quantitative precipitation forecasts
Sign Up to like & getrecommendations! Published in 2017 at "Quarterly Journal of the Royal Meteorological Society"
DOI: 10.1002/qj.2960
Abstract: Since the launch of the NOAA-15 satellite in 1998, the observations from microwave temperature and humidity sounders have been routinely disseminated to user communities through two separate data streams. In the Advanced Microwave Sounding Unit-A… read more here.
Keywords: one data; mhs; amsu mhs; data stream ... See more keywords
Predicting home sale prices: A review of existing methods and illustration of data stream methods for improved performance
Sign Up to like & getrecommendations! Published in 2022 at "Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery"
DOI: 10.1002/widm.1435
Abstract: The need for accurate and unbiased assessment of residential real property has always been important not only to financial institutions lending on or holding such assets but also to municipalities that rely on property taxes… read more here.
Keywords: review existing; data stream; residential property; sale ... See more keywords
Minimal weighted infrequent itemset mining-based outlier detection approach on uncertain data stream
Sign Up to like & getrecommendations! Published in 2018 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3876-4
Abstract: Outliers are a critical factor that affects the accuracy of data-based predictions and some other data-based processing; thus, outliers must be effectively detected as soon as possible to improve the credibility of the data. In… read more here.
Keywords: detection; minimal weighted; outlier detection; data stream ... See more keywords
A utility based approach for data stream anonymization
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Intelligent Information Systems"
DOI: 10.1007/s10844-019-00577-6
Abstract: Data streams are good models to characterize dynamic, on-line, fast and high-volume data requirements of today’s businesses. However, sensitivity of data is usually an obstacle for deployment of many data streams applications. To address this… read more here.
Keywords: utility; quality; stream anonymization; data stream ... See more keywords
Analyzing and repairing concept drift adaptation in data stream classification
Sign Up to like & getrecommendations! Published in 2021 at "Machine Learning"
DOI: 10.1007/s10994-021-05993-w
Abstract: Data collected over time often exhibit changes in distribution, or concept drift, caused by changes in factors relevant to the classification task, e.g. weather conditions. Incorporating all relevant factors into the model may be able… read more here.
Keywords: drift adaptation; data stream; concept drift; drift ... See more keywords
Big data and stream processing platforms for Industry 4.0 requirements mapping for a predictive maintenance use case
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Manufacturing Systems"
DOI: 10.1016/j.jmsy.2019.11.004
Abstract: Abstract Industry 4.0 is considered to be the fourth industrial revolution introducing a new paradigm of digital, autonomous, and decentralized control for manufacturing systems. Two key objectives for Industry 4.0 applications are to guarantee maximum… read more here.
Keywords: big data; use; predictive maintenance; industry ... See more keywords
Supervised Adaptive Incremental Clustering for data stream of chunks
Sign Up to like & getrecommendations! Published in 2017 at "Neurocomputing"
DOI: 10.1016/j.neucom.2016.09.054
Abstract: Many supervised clustering algorithms have been developed to find the optimal clusters for static datasets by presetting some parameters, but they are seldom suitable for dynamic datasets, such as the data stream of chunks. To… read more here.
Keywords: adaptive incremental; stream chunks; supervised adaptive; data stream ... See more keywords
Dynamic extreme learning machine for data stream classification
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DOI: 10.1016/j.neucom.2016.12.078
Abstract: In our society, many fields have produced a large number of data streams. How to mining the interesting knowledge and patterns from continuous data stream becomes a problem which we have to solve. Different from… read more here.
Keywords: stream classification; classification; extreme learning; dynamic extreme ... See more keywords
A survey on data preprocessing for data stream mining: Current status and future directions
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DOI: 10.1016/j.neucom.2017.01.078
Abstract: Data preprocessing and reduction have become essential techniques in current knowledge discovery scenarios, dominated by increasingly large datasets. These methods aim at reducing the complexity inherent to real-world datasets, so that they can be easily… read more here.
Keywords: data preprocessing; mining; survey data; data stream ... See more keywords
Complex industrial automation data stream mining algorithm based on random Internet of robotic things
Sign Up to like & getrecommendations! Published in 2019 at "Automatika"
DOI: 10.1080/00051144.2019.1683287
Abstract: ABSTRACT In recent years, with the continuous development of computer application technology, network technology, data storage technology, and the large amount of investment in information technology, enterprises have accumulated a large amount of data while… read more here.
Keywords: mining; algorithm; complex industrial; automation data ... See more keywords