Application of ANFIS and LSSVM strategies for estimating thermal conductivity enhancement of metal and metal oxide based nanofluids

Razieh Razavi, Aida Sabaghmoghadam, Amin Bemani, Alireza Baghban, Kwok wing Chau, Ely Salwana

Research output: Journal article publicationJournal articleAcademic researchpeer-review

55 Citations (Scopus)


An extensive variety of chemical engineering processes include the transfer of heat energy. Since increasing the effective contact surface is known as one of the popular manners to improve the efficiency of heat transfer, the attention to the nanofluids has been attracted. Due to the difficulty and high cost of an experimental study, researchers have been attracted to fast computational methods. In this work, Adaptive neuro-fuzzy inference system and least square support vector machine algorithms have been applied as a comprehensive predictive tool to forecast the nanofluids thermal conductivity in terms of diameter, temperature, the thermal conductivity of the base fluid, the thermal conductivity of nanoparticle and volume fraction. To this end, a large and comprehensive experimental databank contains 1109 data points have been collected from reliable sources. The particle swarm optimization is utilized to reach the best structures of the proposed algorithms. A comprehensive statistical and graphical investigations are carried out to prove the accuracy and ability of proposed models. In addition, the comparisons outputs indicate that the least square support vector machine algorithm has the best performance among the existing correlations and Adaptive neuro-fuzzy inference system algorithms for forecasting thermal conductivity of different nanofluids.

Original languageEnglish
Pages (from-to)560-578
Number of pages19
JournalEngineering Applications of Computational Fluid Mechanics
Issue number1
Publication statusPublished - 1 Jan 2019


  • Adaptive neuro-fuzzy inference system
  • least square support vector machine algorithm
  • Nanofluid
  • thermal conductivity

ASJC Scopus subject areas

  • General Computer Science
  • Modelling and Simulation


Dive into the research topics of 'Application of ANFIS and LSSVM strategies for estimating thermal conductivity enhancement of metal and metal oxide based nanofluids'. Together they form a unique fingerprint.

Cite this