Advanced search
Publication Cover
European Journal of Environmental and Civil Engineering Volume 17, 2013 - Issue 8
Submit an article Journal homepage
304
Views
28
CrossRef citations to date
0
Altmetric
Articles

Modelling dynamic behaviour of sand–waste tires mixtures using Neural Networks and Neuro-Fuzzy

Ayse Edincliler Kandilli Observatory and Earthquake Research Institute, Bogazici University, Istanbul, Turkey
,
Ali Firat Cabalar Department of Civil Engineering, Geotechnical Engineering Division, University of Gaziantep, Gaziantep, TurkeyCorrespondence[email protected]
&
Abdulkadir Cevik Department of Civil Engineering, Mechanics Division, University of Gaziantep, Gaziantep, Turkey
Pages 720-741 | Received 25 Jan 2013, Accepted 10 Jun 2013, Published online: 11 Jul 2013

Citations (28)

Keep up to date with the latest research on this topic with citation updates for this article.

Subscribe to citation updates

Read on this site (7)

Abidhan Bardhan, Abdel Kareem Alzo'ubi, Sangeetha Palanivelu, Pouria Hamidian, Anasua GuhaRay, Gaurav Kumar, Markos Z. Tsoukalas & Panagiotis G. Asteris. (2023) A hybrid approach of ANN and improved PSO for estimating soaked CBR of subgrade soils of heavy-haul railway corridor. International Journal of Pavement Engineering 24:1.
Read now
Sidali Denine, Noureddine Della, Rawaz Dlawar Muhammed, Sadok Feia, Jean Canou & Jean-Claude Dupla. (2022) Triaxial behaviour of geotextile reinforced sand. Geomechanics and Geoengineering 17:6, pages 1973-1983.
Read now
Muhammad Safdar, Tim Newson & Faheem Shah. (2022) Constitutive Model for Fibre Reinforced Cemented Silty Sand. Geomechanics and Geoengineering 17:5, pages 1388-1405.
Read now
Mohsen Abbaspour, Shayan Sheikhi Narani, Esmail Aflaki & Fereidoon Moghadas Nejad. (2022) Dynamic characteristics of a sandy subgrade reinforced by waste tire textile fibres. International Journal of Pavement Engineering 23:7, pages 2293-2308.
Read now
Salman Rouhanifar, Mohammad Afrazi, Ali Fakhimi & Mahmoud Yazdani. (2021) Strength and deformation behaviour of sand-rubber mixture. International Journal of Geotechnical Engineering 15:9, pages 1078-1092.
Read now
Mahdiye Zokaei, Mehran Karimpour-Fard & Reza Rezvani. (2021) Compressibility behavior and lateral earth pressure of a marine soil mixed with tire crumbs. Marine Georesources & Geotechnology 39:5, pages 600-609.
Read now
Alireza Ardakani & Afshin Kordnaeij. (2019) Soil compaction parameters prediction using GMDH-type neural network and genetic algorithm. European Journal of Environmental and Civil Engineering 23:4, pages 449-462.
Read now

Articles from other publishers (21)

Qinghe Zeng, Jin Liao, Xionghui Huang, Jiu Guan, Jingqi Wang, Cuiying Zhou & Zhen Liu. (2024) The sensitivity and timeliness of a variation correlation between structures in close proximity and located in the delta region. Measurement 224, pages 113953.
Crossref
Hossein Moradi Moghaddam, Mohsen Keramati, Ahmad Fahimifar, Taghi Ebadi, Sumi Siddiqua, Ali Reza Ghanizadeh, Amir Tavana Amlashi & Samer Dessouky. (2024) Shear modulus prediction of landfill components using novel machine learners hybridized with forensic-based investigation optimization. Construction and Building Materials 411, pages 134443.
Crossref
Pingbao Yin, Fengqi Shen, Zhaohui “Joey” Yang, Wei WenXianwu Tang. (2023) Dynamic Characteristics of Polyurethane-Bonded Rubber Particle–Sand Mixture Subject to Freeze–Thaw Cycling. Journal of Cold Regions Engineering 37:3.
Crossref
Michael Kazemzadeh, Matin Jalali Moghadam & Amirali Zad. (2023) Influence of Tire-Shred Aspect Ratio on Performance of Mechanically Stabilized Retaining Walls. Arabian Journal for Science and Engineering.
Crossref
Asieh Alidousti Shahraki, Rassoul Ajalloeian & Alireza Hajian. (2023) ANN and MANFIS to predict pressuremeter modulus and limit pressure, case study: Isfahan metro line 2. Arabian Journal of Geosciences 16:2.
Crossref
Huong-Giang Thi Hoang, Thuy-Anh Nguyen, Hoang-Long Nguyen & Hai-Bang Ly. (2022) Neural network approach for GO-modified asphalt properties estimation. Case Studies in Construction Materials 17, pages e01617.
Crossref
Feiyu Liu, Jun Fu & Mengjie Ying. (2022) Experimental study on cyclic shear characteristics of geogrid and rubber–sand mixture interface. Construction and Building Materials 357, pages 129328.
Crossref
Qifei Liu, Haiyang Zhuang, Qi Wu, Kai Zhao & Guoxing Chen. (2022) Experimental Study on Dynamic Modulus and Damping Ratio of Rubber–Sand Mixtures Over a Wide Strain Range. Journal of Earthquake and Tsunami 16:02.
Crossref
Polidor Bratu, Nicușor Drăgan & Cornelia Dobrescu. (2022) Dynamic Performances of Technological Vibrating Machines. Symmetry 14:3, pages 539.
Crossref
Qi Wu, Wei jia Ma, Qifei Liu, Kai Zhao & Guoxing Chen. (2021) Dynamic shear modulus and damping ratio of rubber-sand mixtures with a wide range of rubber content. Materials Today Communications 27, pages 102341.
Crossref
Hüseyin Suha AKSOY, Nichirvan TAHER & Halmat AWLLA. (2021) Shear strength parameters of sand-tire chips mixtures. Gümüşhane Üniversitesi Fen Bilimleri Enstitüsü Dergisi.
Crossref
Beenish Jehan Khan, Irshad Ahmad, Hassan Nasir, Abdullah Abdullah & Qazi Khawar Gohar. (2020) Shear Strength and Pull-Out Response of Tire Shred-Sand Mixture Reinforced with Deformed Steel Bars. Advances in Civil Engineering 2020, pages 1-15.
Crossref
Zhuang Cheng, Jianfeng Wang & Wei Li. (2020) The micro-mechanical behaviour of sand–rubber mixtures under shear: An experimental study based on X-ray micro-tomography. Soils and Foundations 60:5, pages 1251-1268.
Crossref
Engin GÜCÜYEN & Recep Tuğrul ERDEM. (2020) Estimating Fluid Parameters of Submarine Outfall Using Neural Networks. DÜMF Mühendislik Dergisi 11:2, pages 889-898.
Crossref
Ahmet Kuvat & Erol Sadoglu. (2020) Dynamic properties of sand-bitumen mixtures as a geotechnical seismic isolation material. Soil Dynamics and Earthquake Engineering 132, pages 106043.
Crossref
Onur Onat & Burak Yön. (2019) Elimination of a measurement problem: A robust prediction model for missing eigenvector value to assess earthquake induced out-of-plane failure of infill wall. Measurement 144, pages 88-104.
Crossref
Abdolvahed Ghaderi, Abbas Abbaszadeh Shahri & Stefan Larsson. (2018) An artificial neural network based model to predict spatial soil type distribution using piezocone penetration test data (CPTu). Bulletin of Engineering Geology and the Environment 78:6, pages 4579-4588.
Crossref
A. Soltani, A. DengA. TaheriM. Mirzababaei & H. Nikraz. (2019) Interfacial shear strength of rubber-reinforced clays: a dimensional analysis perspective. Geosynthetics International 26:2, pages 164-183.
Crossref
Jin LiuYuxia BaiQiao FengZezhuo SongJihong WeiShaorui SunDebi Prasanna Kanungo. (2018) Strength Properties of Sand Reinforced with a Mixture of Organic Polymer Stabilizer and Polypropylene Fiber. Journal of Materials in Civil Engineering 30:12.
Crossref
J. S. Yadav & S. K. Tiwari. (2017) Influence of crumb rubber on the geotechnical properties of clayey soil. Environment, Development and Sustainability 20:6, pages 2565-2586.
Crossref
Qinglong Zhou, Juan Herrera-Herbert & Arturo Hidalgo. (2017) Predicting the Risk of Fault-Induced Water Inrush Using the Adaptive Neuro-Fuzzy Inference System. Minerals 7:4, pages 55.
Crossref

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Order Reprints Request Corporate Permissions

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

Request Academic Permissions

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.