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Journals / Eskişehir Osmangazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi / 2008 / Cilt: 21 - Sayı: 1

Determination of swelling potential of Harran clay using artificial neural network and regression models

Harran kili şişme potansiyelinin belirlenmesinde yapay sinir ağları ve çoklu regresyon modellerinin kullanımı

Hasan TOSUN
Murat TÜRKÖZ
Pages
125–140
Publication Date
2022-10-18
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results showed that both MRA and ANN are very efficient in predicting clay swelling potential.

📌 3 Key Takeaways

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Objective & Hypothesis:In this study, the values of swelling potentiall of soils obtained from 33 different locations at the Sanlıurfa and Harran plains in Turkey are estimated by means of different methods.
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Key Findings & Data:Swelling potential of soil samples compacted on the optimum, wet side (+2%) and dry side (-2%) on the compaction curve at the standard compaction effort were determined by using direct methods.
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Conclusion & Impact:The results showed that both MRA and ANN are very efficient in predicting clay swelling potential.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In this study, the values of swelling potentiall of soils obtained from 33 different locations at the Sanlıurfa and Harran plains in Turkey are estimated by means of different methods. Swelling potential of soil samples compacted on the optimum, wet side (+2%) and dry side (-2%) on the compaction curve at the standard compaction effort were determined by using direct methods. The data obtained from direct measurements were evaluated with multiple regression (MRA) and artificial neural network (ANN) analyses. The results showed that both MRA and ANN are very efficient in predicting clay swelling potential. Furthermore, It was noted that the ANN is superior to MRA.

Özet

Bu çalısmada, Sanlıurfa Harran ovasında 33 ayrı lokasyondan elde edilen zemin örneklerinin sisme potansiyeli, farklı yöntemlerle değerlendirilmistir. Standart Proctor enerji seviyesinde her bir numune için ayrı ayrı belirlenen sıkısma eğrisi üzerinde optimum, optimumun ıslak (+%2) ve kuru yönündeki (-%2) su muhtevalarında sıkıstırılarak hazırlanan numunelerin sisme potansiyeli doğrudan deneylerle belirlenmistir. Elde edilen veriler, çoklu regresyon ve yapay sinir ağları (YSA) esasında modeller olusturarak birlikte değerlendirilmistir. Sonuçta, killerin sisme potansiyelinin tahmininde hem YSA hem de regresyon modellerinin oldukça etkili olduğu, özellikle YSA modeli sonuçlarının deney sonuçlarına daha yakın değerler verdiği görülmüstür.

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Cite This Article

TOSUN, H., TÜRKÖZ, M. (2022). Determination of swelling potential of Harran clay using artificial neural network and regression models. Eskişehir Osmangazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, Cilt: 21 - Sayı: 1, 125–140. https://ajindex.com/articles/505855

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References (1)

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