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Status : Active
Research Topic : Fuzzy computation
Australian State/Territory : NSW
Australian State/Territory : SA
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  • Active Funded Activity

    Linkage Projects - Grant ID: LP200200881

    Funder
    Australian Research Council
    Funding Amount
    $643,565.00
    Summary
    Collaborative Sensing and Learning for Maritime Situational Awareness. We aim to demonstrate coordinated autonomous sensing of naval assets in dynamic maritime environments, reducing the operational load required to deliver a high quality maritime situational awareness. A realistic simulation based approach will help us develop novel artificial intelligence technology including: self-adaptive strategies for dynamic asset allocation, embedded smart sensing capabilities for naval observation syste .... Collaborative Sensing and Learning for Maritime Situational Awareness. We aim to demonstrate coordinated autonomous sensing of naval assets in dynamic maritime environments, reducing the operational load required to deliver a high quality maritime situational awareness. A realistic simulation based approach will help us develop novel artificial intelligence technology including: self-adaptive strategies for dynamic asset allocation, embedded smart sensing capabilities for naval observation systems and novel approaches to continuous collaborative learning from multi-spectral media. In addition to the emerging partnership between participants, the project will advance sovereign capability to develop maritime intelligence gathering technology for the Royal Australian Navy to underpin stability in our region.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP200101197

    Funder
    Australian Research Council
    Funding Amount
    $420,000.00
    Summary
    Switching Dynamics Approach for Distributed Global Optimisation . This project aims to create a breakthrough switching dynamics approach and new technology to speed up finding optimal solutions. It will develop a distributed switching dynamics based optimisation scheme for global optimisation problems in industrial big-data environments where timely decision making is required. It will result in a practical technology for industry optimisation problems such as economic energy dispatch in smart g .... Switching Dynamics Approach for Distributed Global Optimisation . This project aims to create a breakthrough switching dynamics approach and new technology to speed up finding optimal solutions. It will develop a distributed switching dynamics based optimisation scheme for global optimisation problems in industrial big-data environments where timely decision making is required. It will result in a practical technology for industry optimisation problems such as economic energy dispatch in smart grids and optimal charging and discharging tasks in a large network of electric vehicles, helping Australian power industry improve efficiency and security, as well as training the next generation scientists and engineers for Australia in this emerging field.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP200102364

    Funder
    Australian Research Council
    Funding Amount
    $518,000.00
    Summary
    Multiobjective Memetic Algorithms for Multi-task Symbolic Regression. This project aims at developing the new generation of symbolic regression methods using a yet unexplored way to represent mathematical functions. We will use memetic algorithms to create mathematical models for symbolic regression. Our memetic computing approach will be data-driven and will use multi-objective optimization and multi-task evolutionary computation for symbolic regression, addressing a core need of many areas of .... Multiobjective Memetic Algorithms for Multi-task Symbolic Regression. This project aims at developing the new generation of symbolic regression methods using a yet unexplored way to represent mathematical functions. We will use memetic algorithms to create mathematical models for symbolic regression. Our memetic computing approach will be data-driven and will use multi-objective optimization and multi-task evolutionary computation for symbolic regression, addressing a core need of many areas of science and technology. A large number of datasets will be investigated to benchmark the new methods. The expected outcomes will help support our national priorities with new data analytic capabilities. With a strong and interdisciplinary team in three continents, the project will attract international collaboration.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP200100406

    Funder
    Australian Research Council
    Funding Amount
    $1,161,512.00
    Summary
    Building Australia's next-generation ocean-sea ice model. Ocean and sea ice models are used for predicting future ocean and climate states, and for climate process research. This project aims to bring the next generation of ocean-sea ice models to Australia and configure the models for our local priorities. The ultimate goal is to create a new coupled ocean-sea ice model for Australia that includes surface waves and biogeochemistry. The model will be optimised and evaluated on Australian facilit .... Building Australia's next-generation ocean-sea ice model. Ocean and sea ice models are used for predicting future ocean and climate states, and for climate process research. This project aims to bring the next generation of ocean-sea ice models to Australia and configure the models for our local priorities. The ultimate goal is to create a new coupled ocean-sea ice model for Australia that includes surface waves and biogeochemistry. The model will be optimised and evaluated on Australian facilities, and released for community use. These developments underpin future ocean state forecasts, sea ice forecasts, wave forecasts, decadal climate prediction and climate process studies. The project will benefit search and rescue, Defence and shipping operations, and will enhance future climate projections.
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