Predicting flow conditions over stepped chutes based on ANFIS

Hanbay D., Baylar A., Ozpolat E.

SOFT COMPUTING, cilt.13, sa.7, ss.701-707, 2009 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 13 Sayı: 7
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1007/s00500-008-0343-7
  • Dergi Adı: SOFT COMPUTING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.701-707
  • Anahtar Kelimeler: ANFIS, Fuzzy membership function, Stepped chute, Flow conditions, Cross validation, PRODUCT-MIX DECISION, S-CURVE MF, SKIMMING FLOW, AERATION EFFICIENCY, NEURAL-NETWORKS, MCDM MODEL, SPILLWAYS, NAPPE, SATISFACTION, PERFORMANCE
  • İnönü Üniversitesi Adresli: Hayır

Özet

Chute flow may be either smooth or stepped. The flow conditions in stepped chutes have been classified into nappe, transition and skimming flows. In this paper, characteristics of flow conditions are presented systematically under a wide range of critical flow depth, step height and chute slope. The Adaptive Network Based Fuzzy Inference System (ANFIS) is used to predict flow conditions in stepped chutes using critical flow depth, step height and chute slope information. The proposed model performance is determined by threefold cross validation method. The evaluated classification accuracy of ANFIS model is 99.01%. The test results showed that the proposed ANFIS model can be used successfully for complex process control in hydraulic systems.