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this research is that it should be possible to significantly improve the performance of extreme learning and assure safe and reliable maintenance operation by integrating this prior knowledge into the learning
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should have a strong foundation in artificial intelligence, machine learning, and multi-agent systems, along with experience in programming, data analysis, and model development. Knowledge
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diagnosis and prognosis technologies, and, consequently, improve maintenance decision making. Currently, machine learning exists as the most promising technologies of big data analytics in industrial problems
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biodiversity support, cooling, air quality regulation and access to nature. By integrating Earth observation, spatial AI, machine learning and socio-environmental datasets, the project will reveal where blue