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- W4311328704 abstract "In the present study, a fuzzy approach is employed in order to develop a model for the conversion of synthesis gas to valuable hydrocarbon process. The fuzzy rules are extracted by clustering technique in this study. The numbers of fuzzy sets for input and output variables are optimized by genetic algorithm (GA) so that the number of data which follows the inconsistent rules, is minimized. Firstly, the center values of clusters are estimated by a proposed logarithmic distance method and the clusters and their centers are then calculated by k-means method. The prediction of CO conversion and olefin and paraffin selectivities is performed based on five input variables: H2/CO content, Time on Stream (TOS), temperature, Weight Hourly Space Velocity (WHSV) and phosphorous content by the proposed fuzzy model so that the parameters of which are optimized by combination of Differential Elevation and Tabu Search optimization approaches (DETS). The comparison of the performance of the designed approaches with two other models (i.e. fuzzy and GA fuzzy models) is executed and the results clearly demonstrate that the developed DETS- GA clustering fuzzy model can be defined as a powerful tool in modeling of the conversion of synthesis gas to hydrocarbons process with regression analysis (R2) of over 96%." @default.
- W4311328704 created "2022-12-25" @default.
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- W4311328704 date "2023-03-01" @default.
- W4311328704 modified "2023-09-25" @default.
- W4311328704 title "Fuzzy modeling system based on GA fuzzy rule extraction and hybrid of differential evolution and Tabu search approaches: Application in synthesis gas conversion to valuable hydrocarbons process" @default.
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- W4311328704 doi "https://doi.org/10.1016/j.fuel.2022.126980" @default.
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