{"title":"人工神经网络假设理论","authors":"P. Buscema, W. J. Tastle","doi":"10.4018/IJISSC.2015100104","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":371573,"journal":{"name":"Int. J. Inf. Syst. Soc. Chang.","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Artificial Neural Network What-If Theory\",\"authors\":\"P. Buscema, W. J. Tastle\",\"doi\":\"10.4018/IJISSC.2015100104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":371573,\"journal\":{\"name\":\"Int. J. Inf. Syst. Soc. Chang.\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Inf. Syst. Soc. Chang.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/IJISSC.2015100104\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Inf. Syst. Soc. Chang.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/IJISSC.2015100104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
摘要
使用相同变量独立收集的数据集可以使用一种新的人工神经网络进行比较,称为人工神经网络What If Theory, AWIT。给定一个数据集,该数据集被认为是某一对象(即一朵花、一种工业、一种疾病或一个星系)的标准参考,可以将其他数据集与之进行比较,以确定其与标准的接近程度。因此,可能不适合传统分析方法的数据可以识别数据的新视角或观点,从而可能产生对新颖和创新解决方案的新看法。该方法来源于人工智能领域,特别是人工神经网络,并利用机器学习和模式识别来进行创新分析。
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.