Feature Selection Using Genetic Algorithms for the Generation of a Recognition and Classification of Children Activities Model Using Environmental Sound
المؤلفون المشاركون
Gamboa-Rosales, Hamurabi
Galván-Tejada, Carlos E.
Galván-Tejada, Jorge I.
García-Dominguez, Antonio
Zanella-Calzada, Laura A.
Celaya-Padilla, José M.
Luna-García, Huizilopoztli
Magallanes-Quintanar, Rafael
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-02-13
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
In the area of recognition and classification of children activities, numerous works have been proposed that make use of different data sources.
In most of them, sensors embedded in children’s garments are used.
In this work, the use of environmental sound data is proposed to generate a recognition and classification of children activities model through automatic learning techniques, optimized for application on mobile devices.
Initially, the use of a genetic algorithm for a feature selection is presented, reducing the original size of the dataset used, an important aspect when working with the limited resources of a mobile device.
For the evaluation of this process, five different classification methods are applied, k-nearest neighbor (k-NN), nearest centroid (NC), artificial neural networks (ANNs), random forest (RF), and recursive partitioning trees (Rpart).
Finally, a comparison of the models obtained, based on the accuracy, is performed, in order to identify the classification method that presents the best performance in the development of a model that allows the identification of children activity based on audio signals.
According to the results, the best performance is presented by the five-feature model developed through RF, obtaining an accuracy of 0.92, which allows to conclude that it is possible to automatically classify children activity based on a reduced set of features with significant accuracy.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
García-Dominguez, Antonio& Galván-Tejada, Carlos E.& Zanella-Calzada, Laura A.& Gamboa-Rosales, Hamurabi& Galván-Tejada, Jorge I.& Celaya-Padilla, José M.…[et al.]. 2020. Feature Selection Using Genetic Algorithms for the Generation of a Recognition and Classification of Children Activities Model Using Environmental Sound. Mobile Information Systems،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1192485
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
García-Dominguez, Antonio…[et al.]. Feature Selection Using Genetic Algorithms for the Generation of a Recognition and Classification of Children Activities Model Using Environmental Sound. Mobile Information Systems No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1192485
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
García-Dominguez, Antonio& Galván-Tejada, Carlos E.& Zanella-Calzada, Laura A.& Gamboa-Rosales, Hamurabi& Galván-Tejada, Jorge I.& Celaya-Padilla, José M.…[et al.]. Feature Selection Using Genetic Algorithms for the Generation of a Recognition and Classification of Children Activities Model Using Environmental Sound. Mobile Information Systems. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1192485
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1192485
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر