首页|New Machine Learning Research Reported from University of los Andes (Compatibili ty Model between Encapsulant Compounds and Antioxidants by the Implementation of Machine Learning)
New Machine Learning Research Reported from University of los Andes (Compatibili ty Model between Encapsulant Compounds and Antioxidants by the Implementation of Machine Learning)
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Investigators publish new report on ar tificial intelligence. According to news reporting out of Bogota, Colombia, by N ewsRx editors, research stated, "The compatibility between antioxidant compounds (ACs) and wall materials (WMs) is one of the most crucial aspects of the encaps ulation process, as the encapsulated compounds' stability depends on the affinit y between the compounds, which is influenced by their chemical properties." The news correspondents obtained a quote from the research from University of lo s Andes: "A compatibility model between the encapsulant and antioxidant chemical s was built using machine learning (ML) to discover optimal matches without cost ly and time-consuming trial-and-error experiments. The attributes of the require d antioxidant and wall material components were recollected, and two datasets we re constructed. As a result, a tying process was performed to connect both datas ets and identify significant relationships between parameters of ACs and WMs to define the compatibility or incompatibility of the compounds, as this was necess ary to enrich the dataset by incorporating decoys. As a result, a simple statist ical analysis was conducted to examine the indicated correlations between variab les, and a Principal Component Analysis (PCA) was performed to reduce the dimens ionality of the dataset without sacrificing essential information. The K-nearest neighbor (KNN) algorithm was used and designed to handle the classification pro blems of the compatibility of the combinations to integrate ML in the model."
University of los AndesBogotaColombi aSouth AmericaCyborgsEmerging TechnologiesMachine Learning
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