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Using hybrid systems in the construction of expert systems in the identification of cognitive and motor problems in children and young people

机译:在专家系统的构建中使用混合系统来识别儿童和年轻人的认知和运动问题

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This paper proposes the use of intelligent hybrid systems based on the concepts of artificial neural networks and fuzzy systems to assist in the identification of children who have a problem that may impair their motor or cognitive development. Research on children seeking to identify diseases that are listed in the International Classification of Functioning, Disability, and Health (ICF-CY) are the targets of this research. To assist in the disease identification studies, a database was provided for researchers from all over the world to develop techniques to aid in the creation of specialist systems based on fuzzy rules to assist in the detection of healthy children with psychological or motor dysfunction. This paper used a smart model capable of generating fuzzy rules to construct a predictor model that helps to diagnose some of these problems in children or adolescents. The results obtained were promising, obtaining better accuracy indexes than the initial studies, confirming that the approach is feasible to identify children with ICF-CY.
机译:本文提出了基于人工神经网络和模糊系统概念的智能混合系统的使用,以帮助识别可能会损害其运动或认知发展的儿童。本研究的目标是对寻求识别《国际功能,残疾与健康分类》(ICF-CY)中所列疾病的儿童进行的研究。为了协助进行疾病识别研究,为来自世界各地的研究人员提供了一个数据库,以开发技术,以帮助创建基于模糊规则的专家系统,以帮助发现患有心理或运动功能障碍的健康儿童。本文使用能够生成模糊规则的智能模型来构建预测器模型,以帮助诊断儿童或青少年中的某些问题。获得的结果令人鼓舞,比最初的研究获得了更好的准确性指标,证实了该方法对鉴定患有ICF-CY的儿童是可行的。

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