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Prediction of Peak Velocity of Blasting Vibration Based on Artificial Neural Network Optimized by Dimensionality Reduction of FA-MIV
المؤلفون المشاركون
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-05-29
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
Blasting vibration is harmful to the nearby habitants and dwellings in diverse geotechnical engineering.
In this paper, a novel scheme based on Artificial Neural Network (ANN) method optimized by dimensionality reduction of Factor Analysis and Mean Impact Value (FA-MIV) is proposed to predict peak particle velocity (PPV) of blasting vibration.
To construct the model, nine parameters of field measurement are taken as undetermined input parameters for research, while peak particle velocity (PPV) is considered as output parameter.
With the application of FA, common factors are extracted from undetermined input parameters.
Then, principal components are defined as a linear combination of common factors.
The weight of each principal components effected on output parameter is ranked according to the calculation of MIV, and two principal components with minimum weight are eliminated.
Ultimately, output parameter (PPV) is explained in a low-dimensional space with four input characteristic parameters.
In the prepared database consisting of 108 datasets, 98 datasets are used for the training of the model, while the rest are used for testing performance.
The performances of the ANN models are compared with regression analysis, in terms of coefficient of determination (R2) and mean absolute error (MAE).
It is found that the performances of ANN models with using FA-MIV are superior to those of models without using FA-MIV in the prediction of PPV.
In addition, the abilities of ANN models are all superior to regression analysis in the prediction of PPV.
The result obtained from ELM is more accurate than BPNN and MVRA models.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhongya, Zhang& Xiaoguang, Jin. 2018. Prediction of Peak Velocity of Blasting Vibration Based on Artificial Neural Network Optimized by Dimensionality Reduction of FA-MIV. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1209345
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zhongya, Zhang& Xiaoguang, Jin. Prediction of Peak Velocity of Blasting Vibration Based on Artificial Neural Network Optimized by Dimensionality Reduction of FA-MIV. Mathematical Problems in Engineering No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1209345
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhongya, Zhang& Xiaoguang, Jin. Prediction of Peak Velocity of Blasting Vibration Based on Artificial Neural Network Optimized by Dimensionality Reduction of FA-MIV. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1209345
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1209345
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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