Realising the promise of neural networks for practical optimisation: improving their efficiency and effectivess through chaotic dynamics and hardware implementation. Combinatorial optimisation problems such as transportation routing and assembly-line scheduling are critical to the efficiency of many industries, but their combinatorial explosion makes rapid solution difficult. Neural networks (NNs) hold much potential for rapid solution though hardware implementation, but we need to improve the q ....Realising the promise of neural networks for practical optimisation: improving their efficiency and effectivess through chaotic dynamics and hardware implementation. Combinatorial optimisation problems such as transportation routing and assembly-line scheduling are critical to the efficiency of many industries, but their combinatorial explosion makes rapid solution difficult. Neural networks (NNs) hold much potential for rapid solution though hardware implementation, but we need to improve the quality of their solutions before developing hardware. We have previously shown that the rich dynamics of chaos can improve the efficiency and effectiveness of NNs. We aim to develop new chaotic NN models, rigorously evaluate them on industrially significant problems such as those arising in manufacturing, logistics and telecommunications, and demonstrate their speed through hardware acceleration.Read moreRead less
Multi-Ontologies meet UML: Improving the Software Engineering of Multi-Agent Systems. Multi-agent systems are a new style of software well suited for open, dynamic, distributed, global, heterogeneous environments such as the Internet. Systematic methods are needed to allow multi-agent systems to reason effectively with high level knowledge. This research draws on software engineering practice to develop a theory and methodology for multi-ontologies for expressing knowledge within multi-agent sys ....Multi-Ontologies meet UML: Improving the Software Engineering of Multi-Agent Systems. Multi-agent systems are a new style of software well suited for open, dynamic, distributed, global, heterogeneous environments such as the Internet. Systematic methods are needed to allow multi-agent systems to reason effectively with high level knowledge. This research draws on software engineering practice to develop a theory and methodology for multi-ontologies for expressing knowledge within multi-agent systems that facilitate adaptation and change.
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Classification and Prediction Modelling for Financial Distress, Tax Debt and Insolvency for ATO Clients. The Australian Taxation Office (ATO) has clients who are not able to meet their taxation debts, resulting in revenue shortfalls for both the State and Federal Governments. Through this project, we will develop predictive models and techniques which identify client classes and clusters in the ATO client population and the defining attributes of these collections - especially those which are a ....Classification and Prediction Modelling for Financial Distress, Tax Debt and Insolvency for ATO Clients. The Australian Taxation Office (ATO) has clients who are not able to meet their taxation debts, resulting in revenue shortfalls for both the State and Federal Governments. Through this project, we will develop predictive models and techniques which identify client classes and clusters in the ATO client population and the defining attributes of these collections - especially those which are at high risk of incurring debt and defaulting on paying taxes. In turn, the early identification of clients in financial distress will allow the ATO to give them assistance so that they can reduce their debts and meet their financial obligations.Read moreRead less
Dynamic Deep Learning for Electricity Demand Forecasting. This project aims at developing a deep learning technology for high resolution electricity demand forecasting and residential demand response modelling. Electricity consumption data are dynamic and highly uncertain. The deep learning technology expects to provide accurate demand forecasting, and thus enabling optimal use of existing
grid assets and guiding future investments. The expected outcome can support data-driven decision-making in ....Dynamic Deep Learning for Electricity Demand Forecasting. This project aims at developing a deep learning technology for high resolution electricity demand forecasting and residential demand response modelling. Electricity consumption data are dynamic and highly uncertain. The deep learning technology expects to provide accurate demand forecasting, and thus enabling optimal use of existing
grid assets and guiding future investments. The expected outcome can support data-driven decision-making in Australia's electricity distribution network planning and operation by considering future challenges such as integrating battery storage and electric vehicles into the grid, and thus providing reliable energy. The project expects to train next generation expert workforce for Australia's future power grid.Read moreRead less
Temporal and spatial Bayesian network modelling for improved fog forecasting. This project aims to improve the accuracy of fog forecasting by explicitly modelling the spatial and temporal uncertainties surrounding fog formation. It is expected weather forecast services will adopt our approach to improve their predictions of fog, which will in turn help transport companies save costs, cut emissions and improve safety.
An Intelligent Flexible Virtual Design System for Jigs in Furniture Manufacturing. The objective of this proposal is to develop an intelligent flexible virtual design support system for powered jigs for timber furniture assembly. Current techniques employ manual techniques with high cost and time for assembly operation. The system will provide a virtual environment to design and measure the performance of the jig considering geometry, material property, manufacturability, quality and cost. The ....An Intelligent Flexible Virtual Design System for Jigs in Furniture Manufacturing. The objective of this proposal is to develop an intelligent flexible virtual design support system for powered jigs for timber furniture assembly. Current techniques employ manual techniques with high cost and time for assembly operation. The system will provide a virtual environment to design and measure the performance of the jig considering geometry, material property, manufacturability, quality and cost. The system will initially be developed to design jigs for assembly of timber bed-heads and will incorporate an advanced feature based design methodology and an expert system to automate, simulate and advise the viability and manufacturability of the jigs.
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An advanced design support system for sofa furniture manufacturing. Moran currently exports its products and has an established brand name in Australia and parts of Asia due to its long-term emphasis on the structure and comfort of its furniture. However it, like the whole of the furniture industry in Australia, faces a growing threat from cheap substitute imports. Lowering the manufacturing cost and lead-time, as well as offering a wide variety of designs, are strategic tools for Moran and othe ....An advanced design support system for sofa furniture manufacturing. Moran currently exports its products and has an established brand name in Australia and parts of Asia due to its long-term emphasis on the structure and comfort of its furniture. However it, like the whole of the furniture industry in Australia, faces a growing threat from cheap substitute imports. Lowering the manufacturing cost and lead-time, as well as offering a wide variety of designs, are strategic tools for Moran and other Australian furniture manufacturing companies. Development of a consolidated design approach to respond rapidly with the needed accuracy, which in turn guarantees the desired results, would greatly benefit Moran and other Australian companies who adopt it.Read moreRead less
A generic decision-making design environment to enable end users in rural industries to develop expert systems. Successful decision support systems developed by end-users has been limited: our proposed approach advances this capability. Using natural representations of industry knowledge, this project will specify a generic design environment in which industry end-users can develop relevant decision support systems. It extends expert systems technologies to overcome known limitations, increasin ....A generic decision-making design environment to enable end users in rural industries to develop expert systems. Successful decision support systems developed by end-users has been limited: our proposed approach advances this capability. Using natural representations of industry knowledge, this project will specify a generic design environment in which industry end-users can develop relevant decision support systems. It extends expert systems technologies to overcome known limitations, increasing context and relevance and encouraging user uptake. Key industry stakeholders will select relevant problems to identify decision categories, leading to specification of the generic design environment. This promises improved decision quality for dairy farmers in the recently deregulated dairy industry; the design environment will be transferable to other rural industries.Read moreRead less
Discovering justified knowledge from data. Knowledge discovery from data has assumed a critical role in numerous areas of science, commerce and public administration. However, its effectiveness is limited by the undesirable propensity of current techniques to make many false, as well as real, discoveries. This research will rectify that problem, a critical outcome given the potential cost of making decisions or setting policy using flawed information. For example, it may prevent the adoption of ....Discovering justified knowledge from data. Knowledge discovery from data has assumed a critical role in numerous areas of science, commerce and public administration. However, its effectiveness is limited by the undesirable propensity of current techniques to make many false, as well as real, discoveries. This research will rectify that problem, a critical outcome given the potential cost of making decisions or setting policy using flawed information. For example, it may prevent the adoption of ineffective strategies for addressing land degradation; inappropriately targeted public health expenditure; expensive development and clinical trialing of drugs which prove ineffective; and wasted police and security investigations into unfounded suspicions of criminal or terrorist activity.Read moreRead less
Mining Distributed, High-Speed, Time-Variant Data Streams. With the high-speed and large volume of data generation, the data mining research community is facing an unprecedented challenge to provide instant data mining outcomes for prompt usage. Getting access to derived information from multiple, dynamically changing data is vital for many business, science and security services. Extended networks of sensors and other devices assist many environments with data collection that should be correlat ....Mining Distributed, High-Speed, Time-Variant Data Streams. With the high-speed and large volume of data generation, the data mining research community is facing an unprecedented challenge to provide instant data mining outcomes for prompt usage. Getting access to derived information from multiple, dynamically changing data is vital for many business, science and security services. Extended networks of sensors and other devices assist many environments with data collection that should be correlated and processed towards discovery of dependencies, regularities and patterns. Data mining tools, especially of this new generation, are capable of dealing with data streams, and they offer great benefits for users from many industry sectors; defence, health management, security, commerce and science.Read moreRead less