@article{MotawaAnumbaElHamalawi2004,
  author    = {Motawa, Ibrahim and Anumba, Chimay and El-Hamalawi, A.},
  title     = {Development of a Fuzzy System for Change Prediction in Construction Projects},
  doi       = {10.25643/bauhaus-universitaet.218},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20111215-2180},
  year      = {2004},
  abstract  = {Change management has been the focus of different IT systems. These IT systems were developed to represent design information, record design rationale, facilitate design coordination and changes. They are largely based on managing reactive changes, particularly design changes, in which changes are recorded and then propagated to the relevant project members. However, proactive changes are hardly dealt with in IT systems. Proactive changes require estimating the likelihood of occurrence of a change event as well as estimating the degree of change impacts on project parameters. Changes in construction projects often result from the uncertainty associated with the imprecise and vague knowledge of much project information at the early stages of projects. This is a major outcome of the case studies carried out as part of this research. Therefore, the proposed model considers that incomplete knowledge and certain project characteristics are always behind change causes. For proactive changes, predicting a change event is the main task for modelling. The prediction model should strive to integrate these main elements: 1) project characteristics that lead to change 2) causes of change, 3) the likelihood of change occurrence, and 4) the change consequences. It should also define the dependency relationships between these elements. However, limited data (documented) are only available from previous projects for change cases and many of the above elements can only be expressed in linguistic terms. This means that the model will simulate the uncertainty and subjectivity associated with these sets of elements. Therefore, a fuzzy model is proposed in this research to capture these elements. The model analyses the impact of each set of elements on the other by assigning fuzzy values for these elements that express the uncertainty and subjectivity of their impact. The main aim is to predict change events and evaluate change effects on project parameters. The fuzzy model described above was developed in an IT system for operational purposes and was designed as a Java package of components with their supporting classes, beans, and files. This paper describes the development and the architecture of the proposed IT system to achieve these requirements. The system is intended to help project teams in dealing with change causes and then the change consequences in construction projects.},
  subject      = {Mehragentensystem},
  language  = {en}
}
@article{AzizAnumbaMiles2004,
  author    = {Aziz, Zeeshan and Anumba, Chimay and Miles, John},
  title     = {Towards a Semantic Grid Computing Platform for Disaster Management in Built Environment},
  doi       = {10.25643/bauhaus-universitaet.208},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20111215-2084},
  year      = {2004},
  abstract  = {Current disaster management procedures rely primarily on heuristics which result in their strategies being very cautious and sub-optimum in terms of saving life, minimising damage and returning the building to its normal function. Also effective disaster management demands decentralized, dynamic, flexible, short term and across domain resource sharing, which is not well supported by existing distributing computing infrastructres. The paper proposes a conceptual framework for emergency management in the built environment, using Semantic Grid as an integrating platform for different technologies. The framework supports a distributed network of specialists in built environment, including structural engineers, building technologists, decision analysts etc. It brings together the necessary technology threads, including the Semantic Web (to provide a framework for shared definitions of terms, resources and relationships), Web Services (to provide dynamic discovery and integration) and Grid Computing (for enhanced computational power, high speed access, collaboration and security control) to support rapid formation of virtual teams for disaster management. The proposed framework also make an extensive use of modelling and simulation (both numerical and using visualisations), data mining (to find resources in legacy data sets) and visualisation. It also include a variety of hardware instruments with access to real time data. Furthermore the whole framework is centred on collaborative working by the virtual team. Although focus of this paper is on disaster management, many aspects of the discussed Grid and Visualisation technologies will be useful for any other forms of collaboration. Conclusions are drawn about the possible future impact on the built environment.},
  subject      = {Mehragentensystem},
  language  = {en}
}