Mould Risk Assessment Based on RST-BN Approach

2012 ◽  
Vol 601 ◽  
pp. 611-617
Author(s):  
Yong Quan Zhou ◽  
Xu Tan
Keyword(s):  
Risk Assessment ◽  
Rough Set ◽  
Rough Set Theory ◽  
Research Result ◽  
Research Work ◽  
Attribute Selection ◽  
Quantitative Risk Assessment ◽  
Project Risks ◽  
Core Reduction

Mould industry is crucial to all manufacturing fields, but there has been very little research work of mould project risk assessment in the world so far, it doesn’t match with mould’s important role in all industries. Mould project risks often became issues, made over 8% rework rate after mould delivery and 20% process rework rate in average. This paper summarized the disadvantage of FTA-BN approach to quantitative risk assessment of mould project, which is widely used in other industry fields, and proposed RST-BN approach instead, The attribute selection and fault diagnosis was developed based on the advantage of rough set theory (RST), to deal with the incomplete, vague and ambivalent data by the innovation algorithms of Core reduction and Unred reduction of attributes. The rough set approach enables one to discover the minimal subsets of condition attributes associated with risk events of mould project, to make BN modeling simpler and effective for quantitative risk assessment. Through a case study, our research result shows that the RST-BN is a promising approach for quantitative risk assessment of mould project development for mould-maker to rank risks and make mitigation plan in advance.

Fuzzy Miner

2011 ◽  
pp. 299-321 ◽  
Author(s):  
Nikos Pelekis ◽  
Babis Theodoulidis ◽  
Ioannis Kopanakis ◽  
Yannis Theodoridis
Keyword(s):  
Data Mining ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Attribute Selection ◽  
Internet Routing ◽  
Data Mining Approach ◽  
New Information

QOSP Quality of Service Open Shortest Path First based on QoS routing has been recognized as a missing piece in the evolution of QoS-based services in the Internet. Data mining has emerged as a tool for data analysis, discovery of new information, and autonomous decision-making. This paper focuses on routing algorithms and their appli-cations for computing QoS routes in OSPF protocol. The proposed approach is based on a data mining approach using rough set theory, for which the attribute-value system about links of networks is created from network topology. Rough set theory offers a knowledge discovery approach to extracting routing-decisions from attribute set. The extracted rules can then be used to select significant routing-attributes and make routing-selections in routers. A case study is conducted to demonstrate that rough set theory is effective in finding the most significant attribute set. It is shown that the algorithm based on data mining and rough set offers a promising approach to the attribute-selection prob-lem in internet routing.

Routing Attribute Data Mining Based on Rough Set Theory

2008 ◽  
pp. 3033-3048 ◽  
Author(s):  
Yanbing Liu ◽  
Shixin Sun ◽  
Menghao Wang ◽  
Hong Tang
Keyword(s):  
Data Mining ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Attribute Selection ◽  
Attribute Data ◽  
Data Mining Approach ◽  
New Information

QOSPF(Quality of Service Open Shortest Path First)based on QoS routing has been recognized as a missing piece in the evolution of QoS-based services in the Internet. Data mining has emerged as a tool for data analysis, discovery of new information, and autonomous decision-making. This paper focuses on routing algorithms and their applications for computing QoS routes in OSPF protocol. The proposed approach is based on a data mining approach using rough set theory, for which the attribute-value system about links of networks is created from network topology. Rough set theory of-fers a knowledge discovery approach to extracting routing-decisions from attribute set. The extracted rules can then be used to select significant routing-attributes and make routing-selections in routers. A case study is conducted to demonstrate that rough set theory is effective in finding the most significant attribute set. It is shown that the algo-rithm based on data mining and rough set offers a promising approach to the attribute-selection problem in internet routing.

Routing Attribute Data Mining Based on Rough Set Theory

2011 ◽  
pp. 322-337
Author(s):  
Yanbing Liu ◽  
Menghao Wang ◽  
Jong Tang
Keyword(s):  
Data Mining ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Attribute Selection ◽  
Attribute Data ◽  
Data Mining Approach ◽  
New Information

QOSPF (Quality of Service Open Shortest Path First) based on QoS routing has been recognized as a missing piece in the evolution of QoS-based services on the Internet. Data mining has emerged as a tool for data analysis, discovery of new information, and autonomous decision making. This article focuses on routing algorithms and their applications for computing QoS routes in OSPF protocol. The proposed approach is based on a data mining approach using rough set theory, for which the attribute-value system about links of networks is created from network topology. Rough set theory offers a knowledge discovery approach toextracting routing decisions from attribute set. The extracted rules then can be used to select significant routing attributes and to make routing selections in routers. A case study is conducted in order to demonstrate that rough set theory is effective in finding the most significant attribute set. It is shown that the algorithm based on data mining and rough set offers a promising approach to the attribute selection problem in Internet routing.

Important Attributes Selection Based on Rough Set for Speech Emotion Recognition

2011 ◽  
pp. 262-271
Author(s):  
Jian Zhou ◽  
Guoyin Wang ◽  
Yong Yang
Keyword(s):  
Emotion Recognition ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Recognition Rate ◽  
Feature Selection Method ◽  
Recognition System ◽  
Attribute Selection ◽  
Computer Application ◽  
Speech Emotion Recognition

Speech emotion recognition is becoming more and more important in such computer application fields as health care, children education, etc. In order to improve the prediction performance or providing faster and more cost-effective recognition system, an attribute selection is often carried out beforehand to select the important attributes from the input attribute sets. However, it is time-consuming for traditional feature selection method used in speech emotion recognition to determine an optimum or suboptimum feature subset. Rough set theory offers an alternative, formal and methodology that can be employed to reduce the dimensionality of data. The purpose of this study is to investigate the effectiveness of Rough Set Theory in identifying important features in speech emotion recognition system. The experiments on CLDC emotion speech database clearly show this approach can reduce the calculation cost while retaining a suitable high recognition rate.

Probability risk assessment of landslides: A case study at Finneidfjord

2008 ◽  
Vol 45 (9) ◽  
pp. 1250-1267 ◽  
Author(s):  
Mark J. Cassidy ◽  
Marco Uzielli ◽  
Suzanne Lacasse
Keyword(s):  
Risk Assessment ◽  
Probabilistic Approach ◽  
Quantitative Risk Assessment ◽  
Historical Case Study ◽  
Historical Case ◽  
Second Moment ◽  
Integrated Risk Assessment ◽  
First Order Second Moment ◽  
Probabilistic Risk Assessments

Probabilistic risk assessments are increasingly being considered the most appropriate framework for engineers to systematically base decisions on hazard mitigation issues. This paper aims to show the advantages of a quantitative risk assessment by application to a historical case study. The generalized integrated risk assessment framework has been applied retrospectively to a submarine landslide that occurred in 1996 near the village of Finneidfjord in northern Norway. Over 1 million cubic metres of predominantly quick clay was displaced. Even though it was triggered underwater on the embankment of the Sørfjord, the retrogressive nature of the slide resulted in it encroaching 100–150 m inland. The triggering mechanism is believed to have been the placement of fill, from a nearby tunnelling project, on the foreshore of the embankment. This paper is a retrospective quantitative evaluation of the risk to the neighbouring houses, the persons in those houses, and the persons in open spaces caused by the placement of increasing levels of embankment fill. A probabilistic approach, making use of second-moment modelling and first-order second-moment approximation is adopted. It aims to demonstrate the advantages of this type of risk assessment in understanding complex and integrated hazards, particularly those in populated environments.

scholarly journals Domain-specific risk assessment using integrated simulation: A case study of an onshore wind project

2021 ◽  
Author(s):  
Emad Mohamed ◽  
Nima Gerami Seresht ◽  
Stephen Hague ◽  
Adam Chehouri ◽  
Simaan M. AbouRizk
Keyword(s):  
Risk Assessment ◽  
Wind Farm ◽  
Critical Path ◽  
Quantitative Risk Assessment ◽  
Integrated Simulation ◽  
Domain Specific ◽  
Risk Assessment Models ◽  
First Case ◽  
Assessment Approach

Although many quantitative risk assessment models have been proposed in literature, their use in construction practice remain limited due to a lack of domain-specific models, tools, and application examples. This is especially true in wind farm construction, where the state-of-the-art integrated Monte Carlo simulation and critical path method (MCS-CPM) risk assessment approach has yet to be demonstrated. The present case study is the first reported application of the MCS-CPM method for risk assessment in wind farm construction and is the first case study to consider correlations between cost and schedule impacts of risk factors using copulas. MCS-CPM provided reasonable risk assessment results for a wind farm project, and its use in practice is recommended. Aimed at facilitating the practical application of quantitative risk assessment methods, this case study provides a much-needed analytical generalization of MCS-CPM, offering application examples, discussion of expected results, and recommendations to wind farm construction practitioners.

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