A New Fuzzy Logic-Based Similarity Measure Applied to Large Gap Imputation for Uncorrelated Multivariate Time Series
المؤلفون المشاركون
Phan, Thi-Thu-Hong
Bigand, André
Caillault, Émilie Poisson
المصدر
Applied Computational Intelligence and Soft Computing
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-08-09
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
The completion of missing values is a prevalent problem in many domains of pattern recognition and signal processing.
Analyzing data with incompleteness may lead to a loss of power and unreliable results, especially for large missing subsequence(s).
Therefore, this paper aims to introduce a new approach for filling successive missing values in low/uncorrelated multivariate time series which allows managing a high level of uncertainty.
In this way, we propose using a novel fuzzy weighting-based similarity measure.
The proposed method involves three main steps.
Firstly, for each incomplete signal, the data before a gap and the data after this gap are considered as two separated reference time series with their respective query windows Q b and Q a .
We then find the most similar subsequence ( Q b s ) to the subsequence before this gap Q b and the most similar one ( Q a s ) to the subsequence after the gap Q a .
To find these similar windows, we build a new similarity measure based on fuzzy grades of basic similarity measures and on fuzzy logic rules.
Finally, we fill in the gap with average values of the window following Q b s and the one preceding Q a s .
The experimental results have demonstrated that the proposed approach outperforms the state-of-the-art methods in case of multivariate time series having low/noncorrelated data but effective information on each signal.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Phan, Thi-Thu-Hong& Bigand, André& Caillault, Émilie Poisson. 2018. A New Fuzzy Logic-Based Similarity Measure Applied to Large Gap Imputation for Uncorrelated Multivariate Time Series. Applied Computational Intelligence and Soft Computing،Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1117067
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Phan, Thi-Thu-Hong…[et al.]. A New Fuzzy Logic-Based Similarity Measure Applied to Large Gap Imputation for Uncorrelated Multivariate Time Series. Applied Computational Intelligence and Soft Computing No. 2018 (2018), pp.1-15.
https://search.emarefa.net/detail/BIM-1117067
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Phan, Thi-Thu-Hong& Bigand, André& Caillault, Émilie Poisson. A New Fuzzy Logic-Based Similarity Measure Applied to Large Gap Imputation for Uncorrelated Multivariate Time Series. Applied Computational Intelligence and Soft Computing. 2018. Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1117067
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1117067
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