Abstract：
:The aim of this study is to identify the optimum thermal conversion of Chlorella vulgaris with neuro-evolutionary approach. A Progressive Depth Swarm-Evolution (PDSE) neuro-evolutionary approach is proposed to model the Thermogravimetric analysis (TGA) data of catalytic thermal degradation of Chlorella vulgaris. Results showed that the proposed method can generate predictions which are more accurate compared to other conventional approaches (>90% lower in Root Mean Square Error (RMSE) and Mean Bias Error (MBE)). In addition, Simulated Annealing is proposed to determine the optimal operating conditions for microalgae conversion from multiple trained ANN. The predicted optimum conditions were reaction temperature of 900.0 °C, heating rate of 5.0 °C/min with the presence of HZSM-5 zeolite catalyst to obtain 88.3% of Chlorella vulgaris conversion.
journal_name
Bioresour Technoljournal_title
Bioresource technologyauthors
Teng SY,Loy ACM,Leong WD,How BS,Chin BLF,Máša Vdoi
10.1016/j.biortech.2019.121971subject
Has Abstractpub_date
2019-11-01 00:00:00pages
121971eissn
0960-8524issn
1873-2976pii
S0960-8524(19)31201-5journal_volume
292pub_type
杂志文章abstract：:A two-stage membrane process for the separation of galactose, 5-hydroxymethylfurfural (5-HMF) and levulinic acid (LA) has been proposed. The first step of nanofiltration (NF) is to remove 5-HMF and LA from galactose solution obtained by the hydrolysis of agarose, the main component of red algal galactan for the reduct...
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