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In the construction industry, the adoption of concurrent engineering principles requires the development of effective enabling IT tools. Such tools need to address specific areas of need in the implementation of concurrent engineering in construction. Collaborative decision-making is an important area in this regard. A review of existing works has shown that none of the existing approaches to collaborative decision-making adequately addresses the needs of distributed construction project teams. The review also reveals that fuzzy logic offers great potential for application to collaborative decision-making. This thesis describes a Web-based collaborative decision-making system for construction project teams using fuzzy logic. Fuzzy logic is applied to tackle uncertainties and imprecision during the decision-making process. The prototype system is designed as Web-based to cope with the difficulty in the case where project team members are geographically distributed and physical meetings are inconvenient/or expensive. The prototype was developed into a Web-based software using Java and allows a virtual meeting to be held within a construction project team via a client-server system. The prototype system also supports objectivity in group decision-making and the approach encapsulated in the prototype system can be used for generic decision-making scenarios. The system implementation revealed that collaborative decision-making within a virtual construction project team can be significantly enhanced by the use of a fuzzybased approach. A generic scenario and a construction scenario were used to evaluate the system and the evaluation confirmed that the system does proffer many benefits in facilitating collaborative decision-making in construction. It is concluded that the prototype decision-making system represents a unique and innovative approach to collaborative decision-making in construction project teams. It not only contributes to the implementation of concurrent engineering in construction, but also it represents a substantial advance over existing approaches.

Risk management is essential for the construction industry to successfully fulfill project objectives. Several studies were conducted in the past decade to support quantitative risk analysis. These studies were based on using some of the commonly used techniques such as risk matrix, decision trees, Monte Carlo, and sensitivity analysis. However, some of these techniques are limited because they either do not support quantitative risk analysis, or are difficult to be utilized due to the required amount of data to support quantitative risk analysis. To address such limitations, a comprehensive framework was developed, based on combining three well-known techniques in reliability engineering, i.e., failure mode and effect analysis, fault trees, and event trees with fuzzy logic. Fuzzy logic and failure mode and effect analysis were first combined to provide an answer to the problem of identifying of critical risk events through the development of a fuzzy expert system software package named Risk Criticality Analyzer. To support quantitative risk analysis in the construction industry, fault tree and event tree were combined, and fuzzy logic is used to solve both of them. Fuzzy arithmetic operations on fuzzy numbers were used to represent logical gates in the fault tree structure, and to conduct event tree analysis. To automate solving both fault trees and event trees, Fuzzy Reliability Analyzer was designed and implemented using Visual Basic.net. Both tools were then validated through case studies. The results indicate that by using the proposed methodology, the risk can be assessed effectively and efficiently. The proposed framework presented in this research provides the contribution of combining fuzzy logic with failure mode and effect analysis, fault trees, and event trees in a comprehensive framework to support risk identification, risk assessment, and risk response. Since the proposed framework is based on using linguistic terms, risk analysts are offered a more convenient and practical framework to conduct risk analysis. The proposed framework was able to address several limitations attributed to the conventional application of failure mode and effect analysis and offered a generic framework that can be adapted to fit any industry or organization. / Construction Engineering and Management

Complex fuzzy logic is a new type of multi-valued logic, in which truth values are drawn from the unit disc of the complex plane; it is thus a generalization of the familiar infinite-valued fuzzy logic. At the present time, all published research on complex fuzzy logic is theoretical in nature, with no practical applications demonstrated. The utility of complex fuzzy logic is thus still very debatable. In this thesis, the performance of ANCFIS is evaluated. ANCFIS is the first machine learning architecture to fully implement the ideas of complex fuzzy logic, and was designed to solve the important machine-learning problem of time-series forecasting. We then explore extensions to the ANCFIS architecture. The basic ANCFIS system uses batch (offline) learning, and was restricted to univariate time series prediction. We have developed both an online version of the univariate ANCFIS system, and a multivariate extension to the batch ANCFIS system. / Software Engineering and Intelligent Systems

There is an increasing pressure on planners to address rapid urbanisation and its impacts on the aesthetic qualities of urban landscape. This is mainly due to the increased sensitivity of the public towards the environment and its greater role, legislatively mandated, in the decision making process. One of the major challenges in land use planning is balancing spatial equity with economic efficiency, where the aspirations and expectations of stakeholders and those of the broader community, in terms of use of the land and its potential, are evaluated and met in a fair manner. The Hills Face Zone (HFZ) of the Adelaide Metropolis in South Australia, currently extending across nine Local Government jurisdictions, is one such example. The HFZ, which provides an important landscape backdrop to the Adelaide Metropolis, has been identified as critically important in the South Australian Planning Strategy and various Development Plans. It is recognised as providing a distinctive visual character to the city and other significant benefits including biodiversity, tourism and recreation. / The HFZ, first introduced in the Adelaide Metropolitan Development Plan in 1962 was endorsed by the South Australian Parliament in 1967 and codified through legislative changes to the Planning Act in 1971 to accommodate the importance of this landscape feature of Adelaide illustrating the strategic intentions of the government. However, despite the best intentions of all the governments since then, the HFZ stil seems to be clouded by confusion and uncertainty four decades on. There are two types of confusion and uncertainty associated with the HFZ landscape. The first, being the clarity of the statutory policy for the HFZ itself, which is the cause of different interpretations of the regulation by the planners, often, leading to lengthy and costly court cases. The second largely ignored so far, is the boundary (spatial) extent of the zone. Within Geographical Information Science these could be termed as the thematic uncertainty and the spatial uncertainty. / Assessment and quantification of the landscape???s thematic and spatial attributes underpinned by a scientific methodology is essential to provide a clear, accountable and sustainable strategic land use plan. This is more important in an urban planning context where planning zone boundaries can have substantial economic impacts, especially if most of the land parcels happen to be under private ownership. / This thesis examined an alternative approach to address the strategic land use planning issues pertaining to delineation of landscape boundaries within the framework of GIS by interpreting the planning policy in a Fuzzy Logic domain. A model for addressing the spatial uncertainty in Landscape Extent Estimation and Mapping (LEEM) using GIS and Fuzzy Logic is discussed and a methodology to establish categorical zone boundaries using fuzzy terms like good view, moderate slope, elevated areas etc. is demonstrated. Boundaries of the HFZ with Adelaide???s Mitcham Local Government Area (LGA) as a case study have been redrawn using various interpretations of visibility, land cover, greenness, slope and elevation of the landscape as a natural backdrop of Adelaide. / Three empirical models, adopting the Modelling View of knowledge engineering to represent a pro-conservation perspective, a pro-development perspective and a planner???s perspective were developed to illustrate the future of the HFZ as aspired to by each group. It was observed that a small difference in linguistic approximation values for the process variables, which translates to slightly differing perceptions in planning terminology, could lead to substantial difference in the outcomes. Thus, in planning terms, this would mean that although both the pro development and the pro conservation lobby are united in their aspirations for a sustainable HFZ, small difference in opinions for the process variables could lead to a substantial difference in the extent of the HFZ zone. / A successful marriage between computer modelling using Fuzzy Logic within Geographic Information Systems and expert opinion is demonstrated and, as such, suggests the suitability of these tools in planning decision making in the future. / Thesis ([PhDPlanning])--University of South Australia, 2005.

Extensive brackishwater aquaculture, which is a dominant land-based aquaculture system in Indonesia, has experienced variable success in most farming locations in the country due to poor understanding of spatial assessment of environmental factors and rudimentary site selection criteria. Despite tremendous potential, the application of GIS and remote sensing in spatial assessment has tended to focus on Boolean (Crisp) logic that is often unable to effectively handle the complexity and spatial variability of key environmental factors for the development of aquaculture. This study explored the possibility of integrating fuzzy logic techniques into GIS and remote sensing technology to generate more robust mapping protocols in aquaculture, compensating for the disadvantages of the Crisp method. Two models were developed in two different provinces in Indonesia to spatially assess soil and hydrological constraints on extensive brackishwater aquaculture. The soil assessment focussed on acid sulfate soils (ASS) and sandy-textured sediments in Aceh, and the hydrological study focused on investigating important wave parameters that influence the suitability of coastal areas for siting extensive pond units in South Sulawesi. The study showed that fuzzy-based classification methods, integrated into the image analysis, was highly effective in identifying existing and potential pond areas for extensive brackishwater aquaculture compared to the best result of the commonly used Crisp method. By addition of one or more key environmental variables of ASS into the fuzzy-classified existing and potential ponds areas, a very robust predictive tool to identify potential ponds areas affected by ASS in Kembang Tanjung, Aceh was developed. A more detailed assessment of ASS developed in this study also successfully highlighted the severity of sandy-soils and identified them as another key soil variable that has and will severely impact on pond productivity. The second model developed by the study enables fuzzy logic to be integrated into GIS to predict the possible areas impacted by moderate to high energy wave conditions and possible ways of minimising their direct and indirect impacts. The models developed in this study were shown to work well in both study sites and can be applied elsewhere. The mapping outputs are easy to interpret even by stakeholders with no prior training in map reading. Overall, the models have the potential to reduce planning errors and to improve decision making in aquaculture provided that quality data sources are used.

There is an increasing pressure on planners to address rapid urbanisation and its impacts on the aesthetic qualities of urban landscape. This is mainly due to the increased sensitivity of the public towards the environment and its greater role, legislatively mandated, in the decision making process. One of the major challenges in land use planning is balancing spatial equity with economic efficiency, where the aspirations and expectations of stakeholders and those of the broader community, in terms of use of the land and its potential, are evaluated and met in a fair manner. The Hills Face Zone (HFZ) of the Adelaide Metropolis in South Australia, currently extending across nine Local Government jurisdictions, is one such example. The HFZ, which provides an important landscape backdrop to the Adelaide Metropolis, has been identified as critically important in the South Australian Planning Strategy and various Development Plans. It is recognised as providing a distinctive visual character to the city and other significant benefits including biodiversity, tourism and recreation. / The HFZ, first introduced in the Adelaide Metropolitan Development Plan in 1962 was endorsed by the South Australian Parliament in 1967 and codified through legislative changes to the Planning Act in 1971 to accommodate the importance of this landscape feature of Adelaide illustrating the strategic intentions of the government. However, despite the best intentions of all the governments since then, the HFZ stil seems to be clouded by confusion and uncertainty four decades on. There are two types of confusion and uncertainty associated with the HFZ landscape. The first, being the clarity of the statutory policy for the HFZ itself, which is the cause of different interpretations of the regulation by the planners, often, leading to lengthy and costly court cases. The second largely ignored so far, is the boundary (spatial) extent of the zone. Within Geographical Information Science these could be termed as the thematic uncertainty and the spatial uncertainty. / Assessment and quantification of the landscape???s thematic and spatial attributes underpinned by a scientific methodology is essential to provide a clear, accountable and sustainable strategic land use plan. This is more important in an urban planning context where planning zone boundaries can have substantial economic impacts, especially if most of the land parcels happen to be under private ownership. / This thesis examined an alternative approach to address the strategic land use planning issues pertaining to delineation of landscape boundaries within the framework of GIS by interpreting the planning policy in a Fuzzy Logic domain. A model for addressing the spatial uncertainty in Landscape Extent Estimation and Mapping (LEEM) using GIS and Fuzzy Logic is discussed and a methodology to establish categorical zone boundaries using fuzzy terms like good view, moderate slope, elevated areas etc. is demonstrated. Boundaries of the HFZ with Adelaide???s Mitcham Local Government Area (LGA) as a case study have been redrawn using various interpretations of visibility, land cover, greenness, slope and elevation of the landscape as a natural backdrop of Adelaide. / Three empirical models, adopting the Modelling View of knowledge engineering to represent a pro-conservation perspective, a pro-development perspective and a planner???s perspective were developed to illustrate the future of the HFZ as aspired to by each group. It was observed that a small difference in linguistic approximation values for the process variables, which translates to slightly differing perceptions in planning terminology, could lead to substantial difference in the outcomes. Thus, in planning terms, this would mean that although both the pro development and the pro conservation lobby are united in their aspirations for a sustainable HFZ, small difference in opinions for the process variables could lead to a substantial difference in the extent of the HFZ zone. / A successful marriage between computer modelling using Fuzzy Logic within Geographic Information Systems and expert opinion is demonstrated and, as such, suggests the suitability of these tools in planning decision making in the future. / Thesis ([PhDPlanning])--University of South Australia, 2005.

Thesis (Ph. D.)--Ohio University, June, 1995. / Title from PDF t.p.

Thesis (Ph.D.)--University of Wollongong, 2005. / Typescript. Includes bibliographical references: leaf 234-249.

Thesis (Ph.D.)--Murdoch University, 2006. / Thesis submitted to the Division of Arts. Includes bibliographical references.