Management of Complex Assets Using Smart Information Systems. The aim is to develop an integrative framework and a smart system for holistic asset management in order to manage and optimise asset decisions vis-a-vis shifts in customer and market needs. It will develop an advanced conceptual framework, a dedicated smart system that is capable of handling uncertainty often associated with decision making in large complex operations. The benefits of this research are: a more competitive indusry wit ....Management of Complex Assets Using Smart Information Systems. The aim is to develop an integrative framework and a smart system for holistic asset management in order to manage and optimise asset decisions vis-a-vis shifts in customer and market needs. It will develop an advanced conceptual framework, a dedicated smart system that is capable of handling uncertainty often associated with decision making in large complex operations. The benefits of this research are: a more competitive indusry with focus on markets; a smart system to demonstrate business-based decision making and generally a much more sophisticated approach to asset management.Read moreRead less
Emergency Control of Catastrophic Disturbances in a Power System. Following the tragic events of 11 September 2001, there are increased concerns about the security and robustness of power systems to evolving spectra of threats, such as natural disasters (e.g., earthquakes and hurricanes), equipment failure, human error, or deliberate sabotage and attack by terrorists. In this project, pattern recognition of local parameter changes in distributed monitoring systems will be used to identify any th ....Emergency Control of Catastrophic Disturbances in a Power System. Following the tragic events of 11 September 2001, there are increased concerns about the security and robustness of power systems to evolving spectra of threats, such as natural disasters (e.g., earthquakes and hurricanes), equipment failure, human error, or deliberate sabotage and attack by terrorists. In this project, pattern recognition of local parameter changes in distributed monitoring systems will be used to identify any threatened breakdown in the power system. Once identified, methods based on intelligent agents will be used to trigger the appropriate countermeasures to maintain the integrity of transmission grids.Read moreRead less
Special Research Initiatives - Grant ID: SR0567373
Funder
Australian Research Council
Funding Amount
$99,696.00
Summary
Collection, Sharing, Visualisation and Analysis of locally gathered information from geographically remote areas vulnerable to tidal waves. This project will set up a virtual organization for tsunami related data analysis using grid technology. Due to geologically remote areas/countries involved the sharing of seismic, tidal and other locally gathered tsunami related information is critical to issuing a warning. In collaboration with Australian and International partners, this project will explo ....Collection, Sharing, Visualisation and Analysis of locally gathered information from geographically remote areas vulnerable to tidal waves. This project will set up a virtual organization for tsunami related data analysis using grid technology. Due to geologically remote areas/countries involved the sharing of seismic, tidal and other locally gathered tsunami related information is critical to issuing a warning. In collaboration with Australian and International partners, this project will explore: new avenues of tsunami-related data collection, which are currently not available; new data fusion methods; data sharing strategies; visualisation and analysis methods; and develop sensing methods to gather data on animal behaviours often reported as a possible way of identifying similar disasters.Read moreRead less
Effective Fuzzy Systems for Complex Structured Data Using Fuzzy Signatures. We are developing systematic, heuristic and mathematical techniques to produce effective fuzzy systems for complex structured data. Many or most real world problems have data which has interdependent sub-components depending on the context (eg only female patients need be tested for pregnancy), and often has missing components. Our techniques use fuzzy signatures to extend simple fuzzy systems to deal with data with such ....Effective Fuzzy Systems for Complex Structured Data Using Fuzzy Signatures. We are developing systematic, heuristic and mathematical techniques to produce effective fuzzy systems for complex structured data. Many or most real world problems have data which has interdependent sub-components depending on the context (eg only female patients need be tested for pregnancy), and often has missing components. Our techniques use fuzzy signatures to extend simple fuzzy systems to deal with data with such complex (sub-)structure. This produces effective fuzzy systems with wide applicability to real problems, in telecommunications, and petroleum reservoir data.Read moreRead less
Modelling the Development and Evolution of Business Relations and Networks as Complex Adaptive Systems using Agent Based Models. This research develops models that will allow managers and policy makers to play more effective roles in the development and evolution of collaborative business relations and networks that lead to greater efficiency, industry innovation, and firm competitiveness, which is a key focus of corporate management and government trade and industry policy. It will also enhance ....Modelling the Development and Evolution of Business Relations and Networks as Complex Adaptive Systems using Agent Based Models. This research develops models that will allow managers and policy makers to play more effective roles in the development and evolution of collaborative business relations and networks that lead to greater efficiency, industry innovation, and firm competitiveness, which is a key focus of corporate management and government trade and industry policy. It will also enhance Australia's resources and expertise in understanding and modelling complex adaptive systems, help develop education resources and training programs for practitioners and researchers in this fast growing area of theory and research, strengthen links with leading researchers and centres, and produce a doctorate in the area.Read moreRead less
Australian housing market risks: Simulation, modelling and analysis. This project aims to determine whether the Australian housing market is at risk of a collapse. This project aims to model the systemic risks in this market using an agent-based simulation at the individual household and financial decision-maker levels. This will be achieved by combining simulation software with datasets from the Australian Bureau of Statistics, Census data and mortgage markets into a behavioural model of financ ....Australian housing market risks: Simulation, modelling and analysis. This project aims to determine whether the Australian housing market is at risk of a collapse. This project aims to model the systemic risks in this market using an agent-based simulation at the individual household and financial decision-maker levels. This will be achieved by combining simulation software with datasets from the Australian Bureau of Statistics, Census data and mortgage markets into a behavioural model of financial decisions. This is expected to provide an unprecedented ability to economically zoom in and out on different suburbs, cities and regions across Australia to predict, measure and mitigate systemic risks.Read moreRead less
Developing Minimum Message Length and Support Vector Machine methods to predict user behaviour. Predicting and modelling customer behaviour enables considerable savings in the telecommunications industry and elsewhere. The resulting predictive models facilitate identifying novice users, identifying fraud, responding to users' needs, guiding and advising users, and forwarding useful information.
We consider two cutting-edge data mining approaches, Minimum Message Length (developed and led by ....Developing Minimum Message Length and Support Vector Machine methods to predict user behaviour. Predicting and modelling customer behaviour enables considerable savings in the telecommunications industry and elsewhere. The resulting predictive models facilitate identifying novice users, identifying fraud, responding to users' needs, guiding and advising users, and forwarding useful information.
We consider two cutting-edge data mining approaches, Minimum Message Length (developed and led by Monash) and Support Vector Machines, in order to create efficient tailor-made software.
Our software will respond to specific groups of users, and their changes over time, rather than just the average user. Moreover, it will integrate the functionalities of existing individual data mining software.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE130101605
Funder
Australian Research Council
Funding Amount
$289,000.00
Summary
Composing machine learning via market mechanisms. This project aims to better understand connections between learning algorithms and markets as aggregators of information and develop new, principled techniques for combining predictions. This will improve our ability to construct systems that make predictions based on multiple, complex and structured sources of data.
Discovery Early Career Researcher Award - Grant ID: DE190100045
Funder
Australian Research Council
Funding Amount
$377,829.00
Summary
Efficient and effective analytics for real-world time series forecasting. This project aims to create efficient, effective techniques that provide accurate forecasts for heterogeneous sets of time series of varying sizes. Exploiting similarities between time series means using many related series, not larger series when building forecasts. The expected outcomes should be innovative methods that improve accuracy and allow forecasting with shorter time series. The project addresses the need to exp ....Efficient and effective analytics for real-world time series forecasting. This project aims to create efficient, effective techniques that provide accurate forecasts for heterogeneous sets of time series of varying sizes. Exploiting similarities between time series means using many related series, not larger series when building forecasts. The expected outcomes should be innovative methods that improve accuracy and allow forecasting with shorter time series. The project addresses the need to exploit properties of big data accurately in a short time frame, which is transforming many industries. This should enable more accurate and reliable forecasts across industries as diverse as retail, food manufacturing, transport, mining, tourism, energy, and technology.Read moreRead less
DEVELOPING A SMART FIRE RISK ADVISORY SYSTEM USING FIRE MODELLING AND KNOWLEDGE-BASED SYSTEMS TECHNOLOGIES. This project aims to develop a prototype fire risk advisory system for fire prevention and protection. Intelligent knowledge-based systems technologies will be tailored to provide a standardised approach for fire risk analysis by using collective expertise of fire engineers and fire modelling. This project will lead to a significant advancement to the development of intelligent systems tec ....DEVELOPING A SMART FIRE RISK ADVISORY SYSTEM USING FIRE MODELLING AND KNOWLEDGE-BASED SYSTEMS TECHNOLOGIES. This project aims to develop a prototype fire risk advisory system for fire prevention and protection. Intelligent knowledge-based systems technologies will be tailored to provide a standardised approach for fire risk analysis by using collective expertise of fire engineers and fire modelling. This project will lead to a significant advancement to the development of intelligent systems techniques for industrial applications and provide a better fire risk analysis tool for fire protection and preventions with the benefit of reduced risk for buildings.
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