應用類神經網路建構學障生判別模型   免費試閱

Employing Artificial Neural Network into Constructing the Discriminant Model Based on Those Students with the Learning Disabilities

學齡階段，學習障礙學生的障礙特徵並不像其他障礙類別那麼明顯，其鑑定之最終目的在於篩選出符合學習障礙標準的學生並使其接受特殊教育（special education）；本研究即著眼於應用類神經網路協助學障生之鑑定，且透過所提出的類神經網路法進行學障生的判定（正確率高達90%）。此鑑定方法的強化將可落實特殊教育的實際應用。

At the school ages, the characteristics of students with learning disabilities are not obvious as those students with other disabilities. Determination of students with learning disabilities aims at selecting those students with learning disabilities and adopting the special education to them. In this study, artificial neural networks (ANNs) is applied to the determination of students with learning disabilities. Those students with learning disabilities can be detected well (the accurate rate is about 90%) by using the proposed approach. This enhancement of determination helps the practice of special education.