1 Ocak 2020 Dergi makalesi Açık Erişim

Sezer, Alper; Sezer, Gozde Inan; Mardani-Aghabaglou, Ali; Altun, Selim

Citation Style Language JSON

{
  "DOI": "10.1007/s00521-020-04972-x", 
  "abstract": "Similar to its effects on any type of cementitious composite, it is a well-known fact that sulfate attack has also a negative influence on engineering behavior of cement-stabilized soils. However, the level of degradation in engineering properties of the cement-stabilized soils still needs more scientific attention. In the light of this, a database including a total of 260 unconfined compression and chloride ion penetration tests on cement-stabilized kaolin specimens exposed to sulfate attack was constituted. The data include information about cement type (sulfate resistant-SR; normal portland (N) and pozzolanic-P), and its content (0, 5, 10 and 15%), sulfate type (sodium or magnesium sulfate) as well as its concentration (0.3, 0.5, 1%) and curing period (1, 7, 28 and 90 days). Using this database, linear and nonlinear regression analysis (RA), backpropagation neural networks and adaptive neuro-fuzzy inference techniques were employed to question whether these methods are capable of predicting unconfined compressive strength and chloride ion penetration of cement-stabilized clay exposed to sulfate attack. The results revealed that these methods have a great potential in modeling the strength and penetrability properties of cement-stabilized clays exposed to sulfate attack. While the performance of regression method is at an acceptable level, results show that adaptive neuro-fuzzy inference systems and backpropagation neural networks are superior in modeling.", 
  "author": [
    {
      "family": "Sezer", 
      "given": " Alper"
    }, 
    {
      "family": "Sezer", 
      "given": " Gozde Inan"
    }, 
    {
      "family": "Mardani-Aghabaglou", 
      "given": " Ali"
    }, 
    {
      "family": "Altun", 
      "given": " Selim"
    }
  ], 
  "container_title": "NEURAL COMPUTING & APPLICATIONS", 
  "id": "7817", 
  "issue": "21", 
  "issued": {
    "date-parts": [
      [
        2020, 
        1, 
        1
      ]
    ]
  }, 
  "page": "16707-16722", 
  "title": "Prediction of mechanical and penetrability properties of cement-stabilized clay exposed to sulfate attack by use of soft computing methods", 
  "type": "article-journal", 
  "volume": "32"
}