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A Neural Network Approach To Border Gateway Protocol Peer Failure Detection And Prediction, Cory B. White
A Neural Network Approach To Border Gateway Protocol Peer Failure Detection And Prediction, Cory B. White
Master's Theses
The size and speed of computer networks continue to expand at a rapid pace, as do the corresponding errors, failures, and faults inherent within such extensive networks. This thesis introduces a novel approach to interface Border Gateway Protocol (BGP) computer networks with neural networks to learn the precursor connectivity patterns that emerge prior to a node failure. Details of the design and construction of a framework that utilizes neural networks to learn and monitor BGP connection states as a means of detecting and predicting BGP peer node failure are presented. Moreover, this framework is used to monitor a BGP network …
Designing Short Term Trading Systems With Artificial Neural Networks, Bruce Vanstone, Gavin Finnie, Tobias Hahn
Designing Short Term Trading Systems With Artificial Neural Networks, Bruce Vanstone, Gavin Finnie, Tobias Hahn
Tobias Hahn
There is a long established history of applying Artificial Neural Networks (ANNs) to financial data sets. In this paper, the authors demonstrate the use of this methodology to develop a financially viable, short-term trading system. When developing short-term systems, the authors typically site the neural network within an already existing non-neural trading system. This paper briefly reviews an existing medium-term long-only trading system, and then works through the Vanstone and Finnie methodology to create a short-term focused ANN which will enhance this trading strategy. The initial trading strategy and the ANN enhanced trading strategy are comprehensively benchmarked both in-sample and …
A Modular Approach To Lung Nodule Detection From Computed Tomography Images Using Artificial Neural Networks And Content Based Image Representation, Omer Muhammet Soysal
A Modular Approach To Lung Nodule Detection From Computed Tomography Images Using Artificial Neural Networks And Content Based Image Representation, Omer Muhammet Soysal
LSU Doctoral Dissertations
Lung cancer is one of the most lethal cancer types. Research in computer aided detection (CAD) and diagnosis for lung cancer aims at providing effective tools to assist physicians in cancer diagnosis and treatment to save lives. In this dissertation, we focus on developing a CAD framework for automated lung cancer nodule detection from 3D lung computed tomography (CT) images. Nodule detection is a challenging task that no machine intelligence can surpass human capability to date. In contrast, human recognition power is limited by vision capacity and may suffer from work overload and fatigue, whereas automated nodule detection systems can …
Designing Short Term Trading Systems With Artificial Neural Networks, Bruce Vanstone, Gavin Finnie, Tobias Hahn
Designing Short Term Trading Systems With Artificial Neural Networks, Bruce Vanstone, Gavin Finnie, Tobias Hahn
Bruce Vanstone
There is a long established history of applying Artificial Neural Networks (ANNs) to financial data sets. In this paper, the authors demonstrate the use of this methodology to develop a financially viable, short-term trading system. When developing short-term systems, the authors typically site the neural network within an already existing non-neural trading system. This paper briefly reviews an existing medium-term long-only trading system, and then works through the Vanstone and Finnie methodology to create a short-term focused ANN which will enhance this trading strategy. The initial trading strategy and the ANN enhanced trading strategy are comprehensively benchmarked both in-sample and …