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tsekm鐵蟲 (初入文壇)
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[交流]
澳大利亞Swinburne University of Technology招收全獎碩士/博士生一名
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研究問題： 將機(jī)器學(xué)習(xí)技術(shù)納入有限元損傷模擬中是否會將現(xiàn)實(shí)世界中的損傷預(yù)測能力提高到一個新水平。 項(xiàng)目簡介: 該研究計(jì)劃旨在開發(fā)一種新的新穎計(jì)算技術(shù)，運(yùn)用遺傳和機(jī)器學(xué)習(xí)算法，并探索與有限元分析協(xié)同的人工神經(jīng)網(wǎng)絡(luò)（ANN）的巧妙特征，從而確定高度非線性的機(jī)械特性和響應(yīng)具有奇異材料特性的結(jié)構(gòu)和材料。 Research Question: Whether the incorporation of machine learning techniques into the finite element injury simulations will enhance the real-world injury prediction capacity to a new level. Project Description: This research proposal aims to develop a new novel computational techniques, employing genetic and machine learning algorithms, and exploring the ingenious features of artificial neural networks (ANN) synergistic to the FE analysis, in order to determine the mechanical properties and responses of the highly nonlinear structures and materials that possess exotic material properties. If you are interested in this position, please send an email to Dr Kwong Ming TSE (ktse@swin.edu.au), with the email subject“EOI-Machine Learning”. Please also include a copy of your CV (with your current residential location), academic UG & PG transcripts, English test results (IELTS or TOEFL or equivalent) and copies of journal publications (if applicable). Thank you. |
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