Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Researchers detail new data in chemical engineeri ng. According to news originating from Ghent,Belgium,by NewsRx correspondents,research stated,"By combining machine learning with the design of experiments,thereby achieving so-called active machine learning,more efficient and cheaper research can be conducted." Financial supporters for this research include European Research Council; Fonds Wetenschappelijk Onderzoek; Horizon 2020; Horizon 2020 Framework Programme. Our news editors obtained a quote from the research from Ghent University: "Mach ine learning algorithms are more flexible and are better than traditional design of experiment algorithms at investigating processes spanning all length scales of chemical engineering. While active machine learning algorithms are maturing,their applications are falling behind. In this article,three types of challenge s presented by active machine learning-namely,convincing the experimental resea rcher,the flexibility of data creation,and the robustness of active machine le arning algorithms-are identified,and ways to overcome them are discussed." According to the news editors,the research concluded: "A bright future lies ahe ad for active machine learning in chemical engineering,thanks to increasing aut omation and more efficient algorithms that can drive novel discoveries."
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