Closure to "Performance Enhancement of a Conceptual Hydrological Model by Integrating Artificial Intelligence" by Ahmet Ali Kumanlioglu and Okan Fistikoglu

Kumanlioglu A., FISTIKOĞLU O.

JOURNAL OF HYDROLOGIC ENGINEERING, cilt.25, sa.9, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Editöre Mektup
  • Cilt numarası: 25 Sayı: 9
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1061/(asce)he.1943-5584.0001987
  • Dergi Adı: JOURNAL OF HYDROLOGIC ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Agricultural & Environmental Science Database, Applied Science & Technology Source, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Communication Abstracts, Compendex, Computer & Applied Sciences, Environment Index, Geobase, INSPEC, Metadex, Pollution Abstracts, DIALNET, Civil Engineering Abstracts
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Redundancy is related to the amount of functionality that the structure can sustain in the worst-case scenario of structural degradation. This paper proposes a widely-applicable concept of redundancy optimization of finite-dimensional structures. The concept is consistent with the robust structural optimization, as well as the quantitative measure of structural redundancy based on the information-gap theory. A derivative-free algorithm is proposed based on the sequential quadratic programming (SQP) method, where we use the finite-difference method with adaptively varying the difference increment. Preliminary numerical experiments show that an optimal solution of the redundancy optimization problem possibly has multiple worst-case scenarios.