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Artificial Neural Network What-lf Theory

机译:人工神经网络理论

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摘要

Data sets collected independently using the same variables can be compared using a new artificial neural network called Artificial neural network What If Theory, AWIT. Given a data set that is deemed the standard reference for some object, i.e. a flower, industry, disease, or galaxy, other data sets can be compared against it to identify its proximity to the standard. Thus, data that might not lend itself well to traditional methods of analysis could identify new perspectives or views of the data and thus, potentially new perceptions of novel and innovative solutions. This method comes out of the field of artificial intelligence, particularly artificial neural networks, and utilizes both machine learning and pattern recognition to display an innovative analysis.
机译:使用相同的变量独立收集的数据集可以使用一种新的人工神经网络(称为人工神经网络What If Theory,AWIT)进行比较。给定被认为是某个对象(例如花朵,工业,疾病或星系)的标准参考的数据集,可以将其与其他数据集进行比较,以识别其与标准的接近程度。因此,可能无法很好地采用传统分析方法的数据可能会识别出数据的新观点或观点,从而可能识别出新颖而创新的解决方案。这种方法来自人工智能领域,尤其是人工神经网络,它利用机器学习和模式识别来显示创新的分析。

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