Fault detection and identification methodology under an incremental learning framework applied to industrial machinery
An industrial machinery condition monitoring methodology based on ensemble novelty
detection and evolving classification is proposed in this study. The methodology contributes …
detection and evolving classification is proposed in this study. The methodology contributes …
Incremental classifiers for data-driven fault diagnosis applied to automotive systems
One of the common ways to perform data-driven fault diagnosis is to employ statistical
models, which can classify the data into nominal (healthy) and a fault class or distinguish …
models, which can classify the data into nominal (healthy) and a fault class or distinguish …
Multi-label incremental learning applied to web page categorization
Multi-label problems are challenging because each instance may be associated with an
unknown number of categories, and the relationship among the categories is not always …
unknown number of categories, and the relationship among the categories is not always …
A fast learning method for streaming and randomly ordered multi-class data chunks by using one-pass-throw-away class-wise learning concept
Presently, the amount of data occurring in several business and academic areas such as
ATM transactions, web searches, and sensor data are tremendously and continuously …
ATM transactions, web searches, and sensor data are tremendously and continuously …
Setting the hidden layer neuron number in feedforward neural network for an image recognition problem under Gaussian noise of distortion
VV Romanuke - 2013 - elar.khmnu.edu.ua
Анотація There is considered an image recognition problem, defined for the single hidden
layer perceptron, fed with 5-by-7 monochrome images on its input under Gaussian noise of …
layer perceptron, fed with 5-by-7 monochrome images on its input under Gaussian noise of …
Electronic nose for on-line quality evaluation of black tea using incremental SOM techniques
The limitations of the classical pattern recognition algorithms may be addressed by an
incremental way of learning, through which the existing knowledge base can be expanded …
incremental way of learning, through which the existing knowledge base can be expanded …
A vector reconstruction based clustering algorithm particularly for large-scale text collection
M Liu, C Wu, L Chen - Neural Networks, 2015 - Elsevier
Along with the fast evolvement of internet technology, internet users have to face the large
amount of textual data every day. Apparently, organizing texts into categories can help users …
amount of textual data every day. Apparently, organizing texts into categories can help users …
Fault detection and identification methodology under an incremental learning framework applied to industrial electromechanical systems
JA Cariño Corrales - 2017 - upcommons.upc.edu
Condition Based Maintenance is a program that recommends actions based on the
information collected and interpreted through condition monitoring and has become …
information collected and interpreted through condition monitoring and has become …
Achieving a compromise between performance and complexity of structure: An incremental approach
In incremental learning techniques, learning occurs continuously over time and does not
cease once available data have been exhausted. Such techniques are useful in cases …
cease once available data have been exhausted. Such techniques are useful in cases …
INNAMP: an incremental neural network architecture with monitor perceptron
S Gupta, S Sanyal - AI communications, 2018 - content.iospress.com
This paper proposes a new architecture for supervised incremental learning using neural
networks. The key feature of this architecture is a special perceptron, called monitor …
networks. The key feature of this architecture is a special perceptron, called monitor …