• Türkçe
    • English
  • English 
    • Türkçe
    • English
  • Login
View Item 
  •   RTEÜ
  • Araştırma Çıktıları | TR-Dizin | WoS | Scopus | PubMed
  • Scopus İndeksli Yayınlar Koleksiyonu
  • View Item
  •   RTEÜ
  • Araştırma Çıktıları | TR-Dizin | WoS | Scopus | PubMed
  • Scopus İndeksli Yayınlar Koleksiyonu
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

The SVM-ARIMA fusion approach for forecasting the structural integrity of obsidian substitution mortars

View/Open

Tam Metin / Full Text (449.0Kb)

Access

info:eu-repo/semantics/closedAccess

Date

2024

Author

Çakmak, Talip
Yılmaz, Yıldıran
Ustabaş, İlker

Metadata

Show full item record

Citation

Çakmak, T., Yilmaz, Y., & Ustabas, İ. (2024). The SVM-ARIMA Fusion Approach for Forecasting the Structural Integrity of Obsidian Substitution Mortars. In 2024 Innovations in Intelligent Systems and Applications Conference (ASYU) (pp. 1–7). IEEE. https://doi.org/10.1109/asyu62119.2024.10757110

Abstract

The construction materials used in building design have changed over time, and their properties continue to evolve. Concrete possesses important characteristics such as high strength, durability, low cost, and easy accessibility. However, the preparation and consumption of cement, which is the primary basic material for concrete, contributes to CO2 emissions, accounting for 5-8% of total emissions. In recent years, researchers have been conducting various research to lower the ratio. One of alternatives is the utility of binders with pozzolanic properties alongside cement. In this study, mortar specimens were produced using different proportions of obsidian powder with pozzolanic properties, ranging from 0% to 30%, in conjunction with cement. The compressive strengths of mortar specimens were measured by subjecting them to technical examines for different time such as 3, 7, 14, 28, and 56 days. However, one of the significant challenges concerns the direction and rate of change in compressive strengths of concrete at later ages. To overcome this challenge, the SVM-ARIMA fusion forecasting model is used in this paper for predicting short-term compressive strengths of mortar specimens. Using this model, compressive strength values for the next 30 days were predicted based on the 90-day compressive strength data. Evaluation results indicate that the use of SVM-ARIMA fusion statistical model is appropriate for predicting the compressive strengths of mortar specimens.

Source

2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024

URI

https://doi.org/10.1109/asyu62119.2024.10757110
https://hdl.handle.net/11436/9913

Collections

  • Bilgisayar Mühendisliği Bölümü Koleksiyonu [47]
  • İnşaat Mühendisliği Bölümü Koleksiyonu [260]
  • Scopus İndeksli Yayınlar Koleksiyonu [5931]



DSpace software copyright © 2002-2015  DuraSpace
Contact Us | Send Feedback
Theme by 
@mire NV
 

 




| Instruction | Guide | Contact |

DSpace@RTEÜ

by OpenAIRE
Advanced Search

sherpa/romeo

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsTypeLanguageDepartmentCategoryPublisherAccess TypeInstitution AuthorThis CollectionBy Issue DateAuthorsTitlesSubjectsTypeLanguageDepartmentCategoryPublisherAccess TypeInstitution Author

My Account

LoginRegister

Statistics

View Google Analytics Statistics

DSpace software copyright © 2002-2015  DuraSpace
Contact Us | Send Feedback
Theme by 
@mire NV
 

 


|| Guide|| Instruction || Library || Recep Tayyip Erdoğan University || OAI-PMH ||

Recep Tayyip Erdoğan University, Rize, Turkey
If you find any errors in content, please contact:

Creative Commons License
Recep Tayyip Erdoğan University Institutional Repository is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License..

DSpace@RTEÜ:


DSpace 6.2

tarafından İdeal DSpace hizmetleri çerçevesinde özelleştirilerek kurulmuştur.