Computational Intelligence Methods for Financial Applications. Complex financial problems can be better addressed with software that can learn from available data and adapt to environmental changes. It is therefore essential to develop technologies that enable prediction and optimisation in constrained and dynamic environments. There are currently some limitations in existing business decision support systems despite their ubiquity providing an opportunity for Australia to be at the forefront as ....Computational Intelligence Methods for Financial Applications. Complex financial problems can be better addressed with software that can learn from available data and adapt to environmental changes. It is therefore essential to develop technologies that enable prediction and optimisation in constrained and dynamic environments. There are currently some limitations in existing business decision support systems despite their ubiquity providing an opportunity for Australia to be at the forefront as new standards in the field are developed. Furthermore, the fund management industry (particularly superannuation) is significant to the Australian economy and development of this technology has the potential to enhance its performance and reputation.Read moreRead less
The Next Step in Intelligent Decision-Support Systems (IDSS): Systems that Learn and Adapt. This project will benefit Australia's scientific knowledge and technology base in the areas of evolutionary computation, business intelligence, and decision management. The outcomes will advance Australian companies and organisations, as many common yet complex business problems can be better addressed with systems that automatically learn and adapt to environmental changes. Such complex business problems ....The Next Step in Intelligent Decision-Support Systems (IDSS): Systems that Learn and Adapt. This project will benefit Australia's scientific knowledge and technology base in the areas of evolutionary computation, business intelligence, and decision management. The outcomes will advance Australian companies and organisations, as many common yet complex business problems can be better addressed with systems that automatically learn and adapt to environmental changes. Such complex business problems include dynamic scheduling (in the manufacturing sector), resource allocation optimisation (in the defence, mining, and agriculture sectors), and network design optimisation (in the telecommunications and energy sectors).Read moreRead less
Improving flow management for the control of blue-green algal blooms. Cyanobacterial (blue-green algal) blooms are a major water quality problem worldwide. They are toxic, produce odours and are estimated to cost around $200 million/year in Australia alone. Flow management is one of the most promising approaches for combating the cyanobacterial bloom problem in rivers. In this research, a new risk-based approach for quantifying the impact of flow management on cyanobacterial blooms is developed, ....Improving flow management for the control of blue-green algal blooms. Cyanobacterial (blue-green algal) blooms are a major water quality problem worldwide. They are toxic, produce odours and are estimated to cost around $200 million/year in Australia alone. Flow management is one of the most promising approaches for combating the cyanobacterial bloom problem in rivers. In this research, a new risk-based approach for quantifying the impact of flow management on cyanobacterial blooms is developed, which can be applied to rivers world wide. The utility of the approach is demonstrated for key sites in the Murray-Darling basin, providing a valuable decision support tool for river managers.Read moreRead less
Adaptive Agents Simulation of Freshwater Ecosystems: Artificial Intelligence Framework to Discover and Forecast Emergent Ecosystem Structures and Behaviours in Response to Environmental Changes. The project aims at intelligent adaptive agent models for lakes and rivers in order to improve understanding and proactive management of these highly complex ecosystems. Little is known about species succession in freshwater ecosystems in response to local and global environmental changes. Evolutionary a ....Adaptive Agents Simulation of Freshwater Ecosystems: Artificial Intelligence Framework to Discover and Forecast Emergent Ecosystem Structures and Behaviours in Response to Environmental Changes. The project aims at intelligent adaptive agent models for lakes and rivers in order to improve understanding and proactive management of these highly complex ecosystems. Little is known about species succession in freshwater ecosystems in response to local and global environmental changes. Evolutionary algorithms embodied in differential equations, neural networks and rules allow adaptive agents to simulate emergent structures and behaviours of algae and zooplankton communities interacting by competition and predation. The agents are trained and tested by ecological time-series of twelve lakes and rivers, and validated for the Mediterranean Myponga Reservoir, South Australia, and the temperate Burrinjuck Reservoir, NSW.Read moreRead less
Intelligent Resource Allocation Techniques for Next Generation Wireless Mobile Communication Networks. The project will develop radio and network resource allocation techniques to maximise network utilisation and to offer guaranteed Quality of Service (QoS) for multimedia traffic in 3G/4G wireless mobile communication networks. In particular, this work will study the problem of radio channel allocation in wireless IP (Internet protocol) multimedia networks. The project will develop resource allo ....Intelligent Resource Allocation Techniques for Next Generation Wireless Mobile Communication Networks. The project will develop radio and network resource allocation techniques to maximise network utilisation and to offer guaranteed Quality of Service (QoS) for multimedia traffic in 3G/4G wireless mobile communication networks. In particular, this work will study the problem of radio channel allocation in wireless IP (Internet protocol) multimedia networks. The project will develop resource allocation algorithms based on traffic conditions, link qualities and service requirements using statistical traffic models, mobile software agents and neural network techniques.
Read moreRead less
New Techniques for Artificial Neural Network Modelling in Hydrology. In recent years, artificial neural networks (ANNs) have demonstrated the potential to provide improved predictions when compared with the more traditional hydrological modelling techniques in a number of areas. These include the prediction of rainfall, streamflow and water quality parameters. However, one of the major difficulties associated with the application of ANNs is the lack of an established methodology for their design ....New Techniques for Artificial Neural Network Modelling in Hydrology. In recent years, artificial neural networks (ANNs) have demonstrated the potential to provide improved predictions when compared with the more traditional hydrological modelling techniques in a number of areas. These include the prediction of rainfall, streamflow and water quality parameters. However, one of the major difficulties associated with the application of ANNs is the lack of an established methodology for their design and implementation. This research will develop new methods for constructing ANN models and test them on a number of case studies so that the full potential and genuine utility of ANNs for solving hydrological problems can be assessed.Read moreRead less
Intelligent and objective measurement of wool fibre diameter. More than a half million tones of wool produced in Australia per year are visually evaluated by human woolclassers. This fibre-classing process is subjective and heavily dependent on the experience of the classers. In this project, we will objectively measure wool fibre diameter by extracting features used by human woolclassers and by combining image processing and artificial intelligence. The fractal dimension calculated by fracta ....Intelligent and objective measurement of wool fibre diameter. More than a half million tones of wool produced in Australia per year are visually evaluated by human woolclassers. This fibre-classing process is subjective and heavily dependent on the experience of the classers. In this project, we will objectively measure wool fibre diameter by extracting features used by human woolclassers and by combining image processing and artificial intelligence. The fractal dimension calculated by fractal based texture analysis will be correlated to fibre diameter. This approach will provide an insight into an on farm and/or in shed objective measurement of wool fibre diameter.Read moreRead less
Bio-inspired Computing for Problems with Dynamically Changing Constraints. The aim of this project is to design bio-inspired computing methods for dynamically changing environments. Dynamic problems arise frequently in the areas of engineering, logistics, and manufacturing. Such problems are usually subject to a large set of constraints that change over time due to changes in resources. Algorithms that can deal with such dynamic changes would benefit decision-makers. The project aims to provide ....Bio-inspired Computing for Problems with Dynamically Changing Constraints. The aim of this project is to design bio-inspired computing methods for dynamically changing environments. Dynamic problems arise frequently in the areas of engineering, logistics, and manufacturing. Such problems are usually subject to a large set of constraints that change over time due to changes in resources. Algorithms that can deal with such dynamic changes would benefit decision-makers. The project aims to provide a foundational theory as the basis for the design of bio-inspired algorithms dealing with dynamically changing constraints and provide approaches for dealing with important industrial problems.Read moreRead less
The Analog Mind: Connectionism, Consciousness and Mental Representation. The aim of our project is to explore novel conjectures about the way information is coded and processed in the brain, and the manner in which the brain manufactures consciousness. This work may eventually pay rich dividends by reducing the incidence of mental illnesses, such as schizophrenia, that disturb conscious experience. It may also lead to the development of more powerful forms of computation in artificial neural ne ....The Analog Mind: Connectionism, Consciousness and Mental Representation. The aim of our project is to explore novel conjectures about the way information is coded and processed in the brain, and the manner in which the brain manufactures consciousness. This work may eventually pay rich dividends by reducing the incidence of mental illnesses, such as schizophrenia, that disturb conscious experience. It may also lead to the development of more powerful forms of computation in artificial neural networks. This will have a significant impact on the artificial intelligence industry, with obvious economic benefits for Australia.
Read moreRead less
Bio-inspired Computing for Problems with Chance Constraints. Bio-inspired algorithms have successfully been applied to a wide range of optimisation problems. Uncertainties in real-world applications can lead to critical failures of production schedules or safe critical systems. Chance constraints model such uncertainties and allow to limit the possibility of such failures. This future fellowship builds up the area of bio-inspired computing for problems with chance constraints. It develops high ....Bio-inspired Computing for Problems with Chance Constraints. Bio-inspired algorithms have successfully been applied to a wide range of optimisation problems. Uncertainties in real-world applications can lead to critical failures of production schedules or safe critical systems. Chance constraints model such uncertainties and allow to limit the possibility of such failures. This future fellowship builds up the area of bio-inspired computing for problems with chance constraints. It develops high performing bio-inspired algorithms for stochastic problems where the constraints can only be violated with a small probability. The outcomes will lead to more effective and reliable optimisation methods for complex planning processes in areas of national priority such as mining and manufacturing.Read moreRead less