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Prediction of pattern recognition using neruofuzzy with equivalently reduced dimension systems

机译:用等效减少维度使用Neruofuzzy预测模式识别

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Equivalently reduced dimension systems of various data sets for pattern recognition are simulated. Various multivariate analyses are adapted to extract the precise, meaningful, embedded data from the original data which are large, noisy and imprecise system. Using the equivalently extracted data, the predicted pattern recognition of forensic glasses is performed using the neurofuzzy systems as a case study. The performance and its accuracy using the proposed approach with forensic glasses data are examined by four different measurements using statistical analysis such as correlation (CORR), total root mean square (TRMS), standard deviation (STD), mean of absolute distance (MAD), and equally weighted index (EWI).
机译:模拟等效地减少了用于模式识别的各种数据集的维度系统。各种多变量分析适于从大型,嘈杂和不精确系统的原始数据中提取精确的,有意义的嵌入数据。使用等效提取的数据,使用神经外部系统作为案例研究进行法医玻璃的预测模式识别。使用统计分析的四种不同测量来检查使用拟议方法的性能及其准确性,如相关性(COR),总根均线(TRMS),标准偏差(STD),绝对距离(MAD)的平均值,同样加权指数(EWI)。

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