Estimation of optimum design of structural systems via machine learning

BEKDAŞ G., Yucel M., NİGDELİ S. M.

FRONTIERS OF STRUCTURAL AND CIVIL ENGINEERING, cilt.15, sa.6, ss.1441-1452, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 15 Sayı: 6
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1007/s11709-021-0774-0
  • Dergi Adı: FRONTIERS OF STRUCTURAL AND CIVIL ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Agricultural & Environmental Science Database, Art Source, Compendex, INSPEC, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.1441-1452
  • Anahtar Kelimeler: optimization, metaheuristic algorithms, harmony search, structural designs, machine learning, artificial neural networks, TUNED MASS DAMPERS, TRUSS STRUCTURES, DIFFERENTIAL EVOLUTION, OPTIMIZATION, ALGORITHM, SEARCH, BEAMS
  • İstanbul Üniversitesi Adresli: Hayır

Özet

Three different structural engineering designs were investigated to determine optimum design variables, and then to estimate design parameters and the main objective function of designs directly, speedily, and effectively. Two different optimization operations were carried out: One used the harmony search (HS) algorithm, combining different ranges of both HS parameters and iteration with population numbers. The other used an estimation application that was done via artificial neural networks (ANN) to find out the estimated values of parameters. To explore the estimation success of ANN models, different test cases were proposed for the three structural designs. Outcomes of the study suggest that ANN estimation for structures is an effective, successful, and speedy tool to forecast and determine the real optimum results for any design model.