Short-Term Load Forecasting Model Based on the Fusion of PSRT and QCNN

المؤلف

Zhang, Zhisheng

المصدر

Mathematical Problems in Engineering

العدد

المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-7، 7ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2017-10-03

دولة النشر

مصر

عدد الصفحات

7

التخصصات الرئيسية

هندسة مدنية

الملخص EN

Short-term load forecasting (STLF) model based on the fusion of Phase Space Reconstruction Theory (PSRT) and Quantum Chaotic Neural Networks (QCNN) was proposed.

The quantum computation and chaotic mechanism were integrated into QCNN, which was composed of quantum neurons and chaotic neurons.

QCNN has four layers, and they are the input layer, the first hidden layer of quantum hidden nodes, the second hidden layer of chaotic hidden nodes, and the output layer.

The theoretical basis of constructing QCNN is Phase Space Reconstruction Theory (PSRT).

Through the actual example simulation, the simulation results show that proposed model has good forecasting precision and stability.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Zhang, Zhisheng. 2017. Short-Term Load Forecasting Model Based on the Fusion of PSRT and QCNN. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1190183

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Zhang, Zhisheng. Short-Term Load Forecasting Model Based on the Fusion of PSRT and QCNN. Mathematical Problems in Engineering No. 2017 (2017), pp.1-7.
https://search.emarefa.net/detail/BIM-1190183

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Zhang, Zhisheng. Short-Term Load Forecasting Model Based on the Fusion of PSRT and QCNN. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1190183

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1190183