@article{FaizollahzadehArdabiliNajafiAlizamiretal.,
  author    = {Faizollahzadeh Ardabili, Sina and Najafi, Bahman and Alizamir, Meysam and Mosavi, Amir and Shamshirband, Shahaboddin and Rabczuk, Timon},
  title     = {Using SVM-RSM and ELM-RSM Approaches for Optimizing the Production Process of Methyl and Ethyl Esters},
  series = {Energies},
  journal   = {Energies},
  number    = {11, 2889},
  publisher = {MDPI},
  address   = {Basel},
  doi       = {10.3390/en11112889},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20181025-38170},
  pages     = {1 -- 20},
  abstract  = {The production of a desired product needs an effective use of the experimental model. The present study proposes an extreme learning machine (ELM) and a support vector machine (SVM) integrated with the response surface methodology (RSM) to solve the complexity in optimization and prediction of the ethyl ester and methyl ester production process. The novel hybrid models of ELM-RSM and ELM-SVM are further used as a case study to estimate the yield of methyl and ethyl esters through a trans-esterification process from waste cooking oil (WCO) based on American Society for Testing and Materials (ASTM) standards. The results of the prediction phase were also compared with artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS), which were recently developed by the second author of this study. Based on the results, an ELM with a correlation coefficient of 0.9815 and 0.9863 for methyl and ethyl esters, respectively, had a high estimation capability compared with that for SVM, ANNs, and ANFIS. Accordingly, the maximum production yield was obtained in the case of using ELM-RSM of 96.86\% for ethyl ester at a temperature of 68.48 °C, a catalyst value of 1.15 wt. \%, mixing intensity of 650.07 rpm, and an alcohol to oil molar ratio (A/O) of 5.77; for methyl ester, the production yield was 98.46\% at a temperature of 67.62 °C, a catalyst value of 1.1 wt. \%, mixing intensity of 709.42 rpm, and an A/O of 6.09. Therefore, ELM-RSM increased the production yield by 3.6\% for ethyl ester and 3.1\% for methyl ester, compared with those for the experimental data.},
  subject      = {Biodiesel},
  language  = {en}
}
@article{SirtlHadlichKrausetal.,
  author    = {Sirtl, Christin and Hadlich, Christiane and Kraus, Matthias and Osburg, Andrea},
  title     = {Determination of Bonding Failures in Transparent Materials with Non-Destructive Methods - Evaluation of Climatically Stressed Glued and Laminated Glass Compounds},
  series = {World Journal of Engineering and Technology},
  volume    = {2018},
  journal   = {World Journal of Engineering and Technology},
  number    = {Vol. 6, No 2},
  doi       = {10.4236/wjet.2018.62020},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20180606-37526},
  pages     = {315 -- 331},
  abstract  = {As part of an international research project - funded by the European Union - capillary glasses for facades are being developed exploiting storage energy by means of fluids flowing through the capillaries. To meet highest visual demands, acrylate adhesives and EVA films are tested as possible bonding materials for the glass setup. Especially non-destructive methods (visual analysis, analysis of birefringent properties and computed tomographic data) are applied to evaluate failure patterns as well as the long-term behavior considering climatic influences. The experimental investigations are presented after different loading periods, providing information of failure developments. In addition, detailed information and scientific findings on the application of computed tomographic analyses are presented.},
  subject      = {Klebtechnik},
  language  = {en}
}