Displaying similar documents to “A tutorial on nonlinear time-series data mining in engineering asset health and reliability prediction: concepts, models, and algorithms.”

A rainfall forecasting method using machine learning models and its application to the Fukuoka city case

S. Monira Sumi, M. Faisal Zaman, Hideo Hirose (2012)

International Journal of Applied Mathematics and Computer Science

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In the present article, an attempt is made to derive optimal data-driven machine learning methods for forecasting an average daily and monthly rainfall of the Fukuoka city in Japan. This comparative study is conducted concentrating on three aspects: modelling inputs, modelling methods and pre-processing techniques. A comparison between linear correlation analysis and average mutual information is made to find an optimal input technique. For the modelling of the rainfall, a novel hybrid...

Bayesian reliability models of Weibull systems: State of the art

Abdelaziz Zaidi, Belkacem Ould Bouamama, Moncef Tagina (2012)

International Journal of Applied Mathematics and Computer Science

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In the reliability modeling field, we sometimes encounter systems with uncertain structures, and the use of fault trees and reliability diagrams is not possible. To overcome this problem, Bayesian approaches offer a considerable efficiency in this context. This paper introduces recent contributions in the field of reliability modeling with the Bayesian network approach. Bayesian reliability models are applied to systems with Weibull distribution of failure. To achieve the formulation...

On naive Bayes in speech recognition

László Tóth, András Kocsor, János Csirik (2005)

International Journal of Applied Mathematics and Computer Science

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The currently dominant speech recognition technology, hidden Mar-kov modeling, has long been criticized for its simplistic assumptions about speech, and especially for the naive Bayes combination rule inherent in it. Many sophisticated alternative models have been suggested over the last decade. These, however, have demonstrated only modest improvements and brought no paradigm shift in technology. The goal of this paper is to examine why HMM performs so well in spite of its incorrect...

Classification Trees as a Technique for Creating Anomaly-Based Intrusion Detection Systems

Jecheva, Veselina, Nikolova, Evgeniya (2009)

Serdica Journal of Computing

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Intrusion detection is a critical component of security information systems. The intrusion detection process attempts to detect malicious attacks by examining various data collected during processes on the protected system. This paper examines the anomaly-based intrusion detection based on sequences of system calls. The point is to construct a model that describes normal or acceptable system activity using the classification trees approach. The created database is utilized as a basis...