This paper combines grey model with time series model and then dynamic model for rapid and in-depth fault prediction in chemical processes. Two combination methods are proposed. In one method, historical data is intro...This paper combines grey model with time series model and then dynamic model for rapid and in-depth fault prediction in chemical processes. Two combination methods are proposed. In one method, historical data is introduced into the grey time series model to predict future trend of measurement values in chemical process. These predicted measurements are then used in the dynamic model to retrieve the change of fault parameters by model based diagnosis algorithm. In another method, historical data is introduced directly into the dynamic model to retrieve historical fault parameters by model based diagnosis algorithm. These parameters are then predicted by the grey time series model. The two methods are applied to a gravity tank example. The case study demonstrates that the first method is more accurate for fault prediction.展开更多
In the past fifteen years, the attention of ship safety treatment as an objective rather than a constraint has started to sweep through the whole maritime industry. The risk-based ship design （RBD） methodology, advo...In the past fifteen years, the attention of ship safety treatment as an objective rather than a constraint has started to sweep through the whole maritime industry. The risk-based ship design （RBD） methodology, advocating systematic integration of risk assessment within the conventional design process has started to takeoff. Despite this wide recognition and increasing popularity, important factors that could potentially undermine the quality of the results come from both quantitative and qualitative aspects during the risk assessment process. This paper details a promising solution by developing a formalized methodology for risk assessment through effective storing and processing of historical data combined with data generated through first-principle approaches. This method should help to generate appropriate risk models in the selected platform （Bayesian networks） which can be employed for decision making at design stare.展开更多
The standard software development life cycle heavily depends on requirements elicited from stakeholders. Based on those requirements, software development is planned and managed from its inception phase to closure. Du...The standard software development life cycle heavily depends on requirements elicited from stakeholders. Based on those requirements, software development is planned and managed from its inception phase to closure. Due to time and resource constraints, it is imperative to identify the high-priority requirements that need to be considered first during the software development process. Moreover, existing prioritization frameworks lack a store of historical data useful for selecting the most suitable prioritization technique of any similar project domain. In this paper, we propose a framework for prioritization of software requirements, called Re Pizer, to be used in conjunction with a selected prioritization technique to rank software requirements based on defined criteria such as implementation cost. ReP izer assists requirements engineers in a decision-making process by retrieving historical data from a requirements repository. Re Pizer also provides a panoramic view of the entire project to ensure the judicious use of software development resources. We compared the performance of Re Pizer in terms of expected accuracy and ease of use while separately adopting two different prioritization techniques, planning game（PG） and analytical hierarchy process（AHP）. The results showed that Re Pizer performed better when used in conjunction with the PG technique.展开更多
基金Supported by the Shandong Natural Science Foundation(ZR2013BL008)
文摘This paper combines grey model with time series model and then dynamic model for rapid and in-depth fault prediction in chemical processes. Two combination methods are proposed. In one method, historical data is introduced into the grey time series model to predict future trend of measurement values in chemical process. These predicted measurements are then used in the dynamic model to retrieve the change of fault parameters by model based diagnosis algorithm. In another method, historical data is introduced directly into the dynamic model to retrieve historical fault parameters by model based diagnosis algorithm. These parameters are then predicted by the grey time series model. The two methods are applied to a gravity tank example. The case study demonstrates that the first method is more accurate for fault prediction.
基金the financial support received by the University of Strathclyde in the form of a postgraduate research scholarship for the duration of the second author’s P hD studies
文摘In the past fifteen years, the attention of ship safety treatment as an objective rather than a constraint has started to sweep through the whole maritime industry. The risk-based ship design （RBD） methodology, advocating systematic integration of risk assessment within the conventional design process has started to takeoff. Despite this wide recognition and increasing popularity, important factors that could potentially undermine the quality of the results come from both quantitative and qualitative aspects during the risk assessment process. This paper details a promising solution by developing a formalized methodology for risk assessment through effective storing and processing of historical data combined with data generated through first-principle approaches. This method should help to generate appropriate risk models in the selected platform （Bayesian networks） which can be employed for decision making at design stare.
基金Project supported by the Ministry of Education,Malaysia(No UM.C/625/1/HIR/MOHE/FCSIT/13)the Bright Sparks Program of University of Malaya,Malaysia(No.BSP-151(3)11)
文摘The standard software development life cycle heavily depends on requirements elicited from stakeholders. Based on those requirements, software development is planned and managed from its inception phase to closure. Due to time and resource constraints, it is imperative to identify the high-priority requirements that need to be considered first during the software development process. Moreover, existing prioritization frameworks lack a store of historical data useful for selecting the most suitable prioritization technique of any similar project domain. In this paper, we propose a framework for prioritization of software requirements, called Re Pizer, to be used in conjunction with a selected prioritization technique to rank software requirements based on defined criteria such as implementation cost. ReP izer assists requirements engineers in a decision-making process by retrieving historical data from a requirements repository. Re Pizer also provides a panoramic view of the entire project to ensure the judicious use of software development resources. We compared the performance of Re Pizer in terms of expected accuracy and ease of use while separately adopting two different prioritization techniques, planning game（PG） and analytical hierarchy process（AHP）. The results showed that Re Pizer performed better when used in conjunction with the PG technique.
