Application of genetic algorithm in calculation of the phase behavior of binary and ternary polymer solutions

Sharifi, Adel; Ghiass, Majid; Moghbeli, Mohammad Reza

doi:10.1007/s13726-012-0121-3

Cited by 1 publication

(2 citation statements)

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“…This technique is widely used in optimizing material and process variables in engineering problems. [14][15][16] Also, in modeling researches, it is used to optimize the ANN and FL model parameters. [17][18][19] Despite the significant role of FT on PVC properties, the studies reported in declaring or characterizing effects of material and processing variables are few.…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy logic model for prediction of fusion characteristics in rigid polyvinyl chloride nanocomposite

Tavana

Moghri

Esmaili

2016

Journal of Elastomers & Plastics

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Fusion is a key parameter in achieving polyvinyl chloride (PVC) nanocomposites with desired properties. In the present research, a fuzzy logic (FL)-based model is developed to predict fusion time (FT) for the contents of nanoclay, processing aid, and calcium stearate in PVC processing. In order to have precise rules for the FL model, data mining algorithm RepTree is employed to detect dominating patterns among experimental data. The model parameters are then well adjusted using genetic algorithm. The modeling results show a correlation of 0.86 between predicted and observed values for FT. So, it proved reliability of the idea of employing the decision tree resulted from a data mining algorithm as the base knowledge of FL models. Also, applying genetic algorithm optimization, the correlation coefficient increased from a value of less than 0.83 to 0.86. The calculated correlation coefficient for the test data was 0.88, which denotes good model universalizing ability.

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Section: Introductionmentioning

confidence: 99%

“…This technique is widely used in optimizing material and process variables in engineering problems. 14 –16 Also, in modeling researches, it is used to optimize the ANN and FL model parameters. 17 –19…”

Section: Introductionmentioning

confidence: 99%