The Improved Least Square Support Vector Machine Based on Wolf Pack Algorithm and Data Inconsistency Rate for Cost Prediction of Substation Projects
المؤلفون المشاركون
Niu, Dongxiao
Wang, Haichao
Wang, Fenghua
Li, Si
Ding, Wei
Liang, Yi
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-12-30
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
الملخص EN
Accurate and stable cost forecasting of substation projects is of great significance to ensure the economic construction and sustainable operation of power engineering projects.
In this paper, a forecasting model based on the improved least squares support vector machine (ILSSVM) optimized by wolf pack algorithm (WPA) is proposed to improve the accuracy and stability of the cost forecasting of substation projects.
Firstly, the optimal features are selected through the data inconsistency rate (DIR), which helps reduce redundant input vectors.
Secondly, the wolf pack algorithm is used to optimize the parameters of the improved least square support vector machine.
Lastly, the cost forecasting method of WPA-DIR-ILSSVM is established.
In this paper, 88 substation projects in different regions from 2015 to 2017 are chosen to conduct the training tests to verify the validity of the model.
The results indicate that the new hybrid WPA-DIR-ILSSVM model presents better accuracy, robustness, and generality in cost forecasting of substation projects.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Wang, Haichao& Liang, Yi& Ding, Wei& Niu, Dongxiao& Li, Si& Wang, Fenghua. 2020. The Improved Least Square Support Vector Machine Based on Wolf Pack Algorithm and Data Inconsistency Rate for Cost Prediction of Substation Projects. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1197082
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wang, Haichao…[et al.]. The Improved Least Square Support Vector Machine Based on Wolf Pack Algorithm and Data Inconsistency Rate for Cost Prediction of Substation Projects. Mathematical Problems in Engineering No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1197082
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Wang, Haichao& Liang, Yi& Ding, Wei& Niu, Dongxiao& Li, Si& Wang, Fenghua. The Improved Least Square Support Vector Machine Based on Wolf Pack Algorithm and Data Inconsistency Rate for Cost Prediction of Substation Projects. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1197082
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1197082
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