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Quantum-Based Feature Selection for Multiclassification Problem in Complex Systems with Edge Computing
المؤلفون المشاركون
Liu, Wenjie
Chen, Junxiu
Wang, Yuxiang
Gao, Peipei
Lei, Zhibin
Ma, Xu
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-03-31
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
The complex systems with edge computing require a huge amount of multifeature data to extract appropriate insights for their decision making, so it is important to find a feasible feature selection method to improve the computational efficiency and save the resource consumption.
In this paper, a quantum-based feature selection algorithm for the multiclassification problem, namely, QReliefF, is proposed, which can effectively reduce the complexity of algorithm and improve its computational efficiency.
First, all features of each sample are encoded into a quantum state by performing operations CMP and Ry, and then the amplitude estimation is applied to calculate the similarity between any two quantum states (i.e., two samples).
According to the similarities, the Grover–Long method is utilized to find the nearest k neighbor samples, and then the weight vector is updated.
After a certain number of iterations through the above process, the desired features can be selected with regards to the final weight vector and the threshold τ.
Compared with the classical ReliefF algorithm, our algorithm reduces the complexity of similarity calculation from O(MN) to O(M), the complexity of finding the nearest neighbor from O(M) to OM, and resource consumption from O(MN) to O(MlogN).
Meanwhile, compared with the quantum Relief algorithm, our algorithm is superior in finding the nearest neighbor, reducing the complexity from O(M) to OM.
Finally, in order to verify the feasibility of our algorithm, a simulation experiment based on Rigetti with a simple example is performed.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Liu, Wenjie& Chen, Junxiu& Wang, Yuxiang& Gao, Peipei& Lei, Zhibin& Ma, Xu. 2020. Quantum-Based Feature Selection for Multiclassification Problem in Complex Systems with Edge Computing. Complexity،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1144148
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Liu, Wenjie…[et al.]. Quantum-Based Feature Selection for Multiclassification Problem in Complex Systems with Edge Computing. Complexity No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1144148
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Liu, Wenjie& Chen, Junxiu& Wang, Yuxiang& Gao, Peipei& Lei, Zhibin& Ma, Xu. Quantum-Based Feature Selection for Multiclassification Problem in Complex Systems with Edge Computing. Complexity. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1144148
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1144148
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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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
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