A Hybrid Wi-Fi Fingerprint-Based Localization Scheme Achieved by Combining Fisher Score and Stacked Sparse Autoencoder Algorithms
المؤلفون المشاركون
Wang, Zhongyuan
Wang, Zijian
Fan, Li
Yu, Zhihao
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-04-14
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
الملخص EN
Along with the advancement of wireless technology, indoor localization technology based on Wi-Fi has received considerable attention from academia and industry.
The fingerprint-based method is the mainstream approach for Wi-Fi indoor localization and can be easily implemented without additional hardware.
However, signal fluctuations constitute a critical issue pertaining to the extraction of robust features to achieve the required localization performance.
This study presents a fingerprint feature extraction method commonly referred to as the Fisher score–stacked sparse autoencoder (Fisher–SSAE) method.
Some features with low Fisher scores were eliminated, and the representative features were then extracted by the SSAE.
Furthermore, this study establishes a hybrid localization model constructed with the use of the global model and the submodel to avoid significant coordinate localization errors attributed to subregional localization errors.
Combined with three accessible fingerprint-based positioning methods, namely, the support vector regression, random forest regression, and the multiplayer perceptron classification, the experimental results demonstrate that the proposed methods improve the localization accuracy and response time compared to other feature extraction methods and the single localization model.
Compared with some state-of-the-art methods, the proposed methods have better localization performances when large number of features are used.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Wang, Zhongyuan& Wang, Zijian& Fan, Li& Yu, Zhihao. 2020. A Hybrid Wi-Fi Fingerprint-Based Localization Scheme Achieved by Combining Fisher Score and Stacked Sparse Autoencoder Algorithms. Mobile Information Systems،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1192416
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wang, Zhongyuan…[et al.]. A Hybrid Wi-Fi Fingerprint-Based Localization Scheme Achieved by Combining Fisher Score and Stacked Sparse Autoencoder Algorithms. Mobile Information Systems No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1192416
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Wang, Zhongyuan& Wang, Zijian& Fan, Li& Yu, Zhihao. A Hybrid Wi-Fi Fingerprint-Based Localization Scheme Achieved by Combining Fisher Score and Stacked Sparse Autoencoder Algorithms. Mobile Information Systems. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1192416
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1192416
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