The performance of factorial designs is still limited due to some uncertainties that usually intensify process complexities, hence, the need for inter-platform auto-correlation analyses. In this study, the auto-correlation capabilities of factorial designs and General Algebraic Modeling System (GAMS) on the effects of some pertinent operating variables in wastewater treatment were compared. Individual and combined models were implemented in GAMS and solved with the trio of BARON, CPLEX and IPOPT solvers. It is revealed that adsorbent dosage had the highest effect on the process. It contributed the most effect toward obtaining the minimum silica and TDS contents of 13 mg/L and 814 mg/L, and 13.6 mg/L and 815 mg/L from factorial design and GAMS platforms, respectively. This indicates a concurrence between the results from the two platforms with percentage errors of 4.4% and 0.2% for silica and TDS, respectively. The effects of the mixing speed and contact time are negligible.

由于某些不确定性通常会加剧工艺复杂性，因此析因设计的性能仍然受到限制，因此需要进行平台间自相关分析。在这项研究中，比较了因子设计和通用代数建模系统（GAMS）对废水处理中某些相关操作变量的影响的自相关能力。单个模型和组合模型在GAMS中实现，并由BARON，CPLEX和IPOPT求解器三者解决。结果表明，吸附剂用量对该工艺影响最大。它对通过析因设计平台和GAMS平台获得的最低二氧化硅和TDS最低含量分别为13 mg / L和814 mg / L，13.6 mg / L和815 mg / L的影响最大。这表明两个平台的结果之间存在一致性，而二氧化硅和TDS的百分比误差分别为4.4％和0.2％。混合速度和接触时间的影响可以忽略不计。