Results 221 to 230 of about 17,917 (263)

Software Fault Prediction Based on Fault Probability and Impact

2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA), 2019
Nowadays, software tests prioritization is a crucial task. Indeed, testing exhaustively the whole software system can be very difficult, heavily time and resources consuming. Using machine learning algorithms to predict which parts of a software system are fault-prone can help testers to focus on high-risk parts of the code and improve resources ...
Salim Moudache, Mourad Badri
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INCREMENTAL DEVELOPMENT OF FAULT PREDICTION MODELS

International Journal of Software Engineering and Knowledge Engineering, 2013
The identification of fault-prone modules has a significant impact on software quality assurance. In addition to prediction accuracy, one of the most important goals is to detect fault prone modules as early as possible in the development lifecycle. Requirements, design, and code metrics have been successfully used for predicting fault-prone modules ...
Yue Jiang 0001, Bojan Cukic, Tim Menzies, Jie Lin   +3 more
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Early Prediction of System Faults

2016
A system will produce massive status data during its runtime, which contains rich status information. In this work, we target at detecting system faults as early as possible based on the system status data sequences. Firstly, we formalized the system fault detection into classification problem, in which different types of status data were integrated to
You Li 0007, Yuming Lin 0001
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Fault-tolerant model predictive control with active fault isolation

2013 Conference on Control and Fault-Tolerant Systems (SysTol), 2013
A robust control method is presented for linear systems subject to input and state constraints, bounded disturbances and measurement noise, and discrete faults in sensors, actuators, and system dynamics. The approach uses set-based fault detection and isolation techniques to coordinate switching between controllers designed for each fault scenario.
RAIMONDO, DAVIDE MARTINO, G. R. Marseglia, R. D. Braatz, J. K. Scott   +3 more
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Alarm processing for predictive fault diagnosis

Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA), 2014
This work proposes a methodology based on online processing of alarms with the objective of identifying proactively possible failures of industrial processes operation. For this, a knowledge base that relates failure scenarios previously registered is used then the feasibility of each failure scenario is continuously assessed based on the possibility ...
Gustavo Bezerra Paz Leitao, Luiz Affonso Guedes, Allan Venceslau   +2 more
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Fault prediction and modelling in transport networks

2018 IEEE International Symposium on Circuits and Systems (ISCAS), 2018
Engineered transport networks occur in many domains: road networks, power grids, the internet and utility distribution. Such networks present a generic problem — how does one model and predict failure of components within them? In this paper we will use the example of a metropolitan water distribution network to model and predict failure based on ...
Ashleigh Ballantyne, Nicholas Lawrance 0001, Michael Small, Melinda Hodkiewicz, David Burton   +4 more
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An IoT Application for Fault Diagnosis and Prediction

2015 IEEE International Conference on Data Science and Data Intensive Systems, 2015
Internet of Things (IoT) has become an important topic in both industry and academia for the recent years as it offers great potentials in numerous real world applications. This paper considers the problem of fault diagnosis and prediction from IoT data collected in the process industry.
Chen Wang, Hoang Tam Vo, Peng Ni
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Research on Fault Prediction of Aircraft Engine

2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), 2018
To improve the flight efficiency and ensure the flight reliability of the aircraft, a data mining model for aero engine fault prediction based on fuzzy clustering is presented. On the basis of data acquisition and analysis, the engine data mining model is constructed, and the maintenance data of a certain type of aero engine is clustered by using fuzzy
Chang-Bin Xu, Xiang-Ming Zhou, Zhen-hua Zhang, You-Yuan Wang   +3 more
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A practical method for the software fault-prediction

2007 IEEE International Conference on Information Reuse and Integration, 2007
In the paper, a novel machine learning method, SimBoost, is proposed to handle the software fault-prediction problem when highly skewed datasets are used. Although the method, proved by empirical results, can make the datasets much more balanced, the accuracy of the prediction is still not satisfactory.
Zhan Li, Marek Z. Reformat
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Preventive Diagnosis: A Task for Predicting Faults

IFAC Proceedings Volumes, 1997
Abstract This paper addresses the topic of an actually predictive task called preventive diagnosis, for foreseeing faults in physical systems. The rationale behind the proposal of a logical model of the task is that, since the causes of faults in physical systems are wear phenomena, knowledge about these phenomena could be used for forecasting the ...
GUIDA, Giovanni, LAMPERTI, Gian Franco, ZANELLA, Marina   +2 more
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