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  • Comparison of Unsupervised Anomaly Detection Methods

    A Publication, Ashok Srivastava's Collection - 11 years, 2 months ago

    Shared By: Ashok Srivastava

    Several different unsupervised anomaly detection algorithms have been applied to Space Shuttle Main Engine (SSME) data to serve the purpose of developing a comprehensive suite ...

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  • Comparative Analysis of Data-Driven Anomaly Detection Methods

    A Publication, Ashok Srivastava's Collection - 11 years, 2 months ago

    Shared By: Ashok Srivastava

    This paper provides a review of three different advanced machine learning algorithms for anomaly detection in continuous data streams from a ground-test firing of a ...

    meatball
  • Novel Methods for Predicting Photometric Redshifts

    A Publication, Ashok Srivastava's Collection - 11 years, 2 months ago

    Shared By: Ashok Srivastava

    We calculate photometric redshifts from the Sloan Digital Sky Survey Main Galaxy Sample, The Galaxy Evolution Explorer All Sky Survey, and The Two Micron All ...

    meatball
  • Algorithms for Spectral Decomposition with Applications

    A Publication, Ashok Srivastava's Collection - 11 years, 2 months ago

    Shared By: Ashok Srivastava

    The analysis of spectral signals for features that represent physical phenomenon is ubiquitous in the science and engineering communities. There are two main approaches that ...

    meatball
  • Detection and Prognostics on Low Dimensional Systems

    A Publication, Ashok Srivastava's Collection - 11 years, 2 months ago

    Shared By: Ashok Srivastava

    This paper describes the application of known and novel prognostic algorithms on systems that can be described by low dimensional, potentially nonlinear dynamics. The methods ...

    meatball
  • Anomaly Detection and Diagnosis Algorithms for Discrete Symbols

    A Publication, Ashok Srivastava's Collection - 11 years, 2 months ago

    Shared By: Ashok Srivastava

    We present a set of novel algorithms which we call sequenceMiner that detect and characterize anomalies in large sets of high-dimensional symbol sequences that arise ...

    meatball
  • Discovering System Health Anomalies using Data Mining Techniques

    A Publication, Ashok Srivastava's Collection - 11 years, 2 months ago

    Shared By: Ashok Srivastava

    We discuss a statistical framework that underlies envelope detection schemes as well as dynamical models based on Hidden Markov Models (HMM) that can encompass both ...

    meatball
  • Multiple Kernel Learning for Heterogeneous Anomaly Detection: Algorithm and Aviation Safety Case Study

    A Publication, Multiple Kernel Learning based Heterogeneous Algorithm (MKAD) - 14 years, 6 months ago

    Shared By: Bryan Matthews

    The world-wide aviation system is one of the most complex dynamical systems ever developed and is generating data at an extremely rapid rate. Most modern ...

    meatball
  • Multiple Kernel Learning based Heterogeneous Algorithm

    A Publication, Santanu Das's Collection - 14 years, 5 months ago

    Shared By: Santanu Das

    Paper on this topic has been submitted to KDD 2010.

    meatball
  • Methods for Probabilistic Fault Diagnosis: An EPS Case Study

    A Publication, Ole Mengshoel's Collection - 14 years, 5 months ago

    Shared By: Ole Mengshoel

    Health management systems that more accurately and quickly diagnose faults that may occur in different technical systems on-board a vehicle will play a key role ...

  • Probabilistic Model-Based Diagnosis for Electrical Power Systems

    A Publication, Ole Mengshoel's Collection - 14 years, 5 months ago

    Shared By: Ole Mengshoel

    We present in this article a case study of the probabilistic approach to model-based diagnosis. Here, the diagnosed system is a real-world electrical power system, ...

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  • Developing Large-Scale Bayesian Networks by Composition

    A Publication, Ole Mengshoel's Collection - 14 years, 5 months ago

    Shared By: Ole Mengshoel

    In this paper, we investigate the use of Bayesian networks to construct large-scale diagnostic systems. In particular, we consider the development of large-scale Bayesian networks ...

  • The ProADAPT System in the 2009 Diagnostic Challenge Competition

    A Publication, Ole Mengshoel's Collection - 14 years, 5 months ago

    Shared By: Ole Mengshoel

    Reliable systems health management is an important research area of NASA. A health management system that can accurately and quickly diagnose faults in various on-board ...

  • Designing Resource-Bounded Reasoners using Bayesian Networks

    A Publication, Ole Mengshoel's Collection - 14 years, 5 months ago

    Shared By: Ole Mengshoel

    In this work we are concerned with the conceptual design of large-scale diagnostic and health management systems that use Bayesian networks. While they are potentially ...

  • Macroscopic Models of Clique Tree Growth for Bayesian Networks

    A Publication, Ole Mengshoel's Collection - 14 years, 5 months ago

    Shared By: Ole Mengshoel

    In clique tree clustering, inference consists of propagation in a clique tree compiled from a Bayesian network. In this paper, we develop an analytical approach ...