The silica content also varies depending on process parameters, the statistical model predicting that the most influential parameters are water-tetraethoxysilane (TEOS) ratio and reaction temperature.
Through this analysis it was determined that the most influential parameter was water depth, followed by soil phosphorus concentration and initial distribution.
The results show that the worst alternating corrosion parameters were: sea water salinity 3.5% × sea water temperature 55 °C + acid rain pH 2.5 × acid rain temperature 55 °C.
The 14 input parameters were the water binder ratio, 4 type mineral admixture quantity, 5 different superplasticizer quantity and 4 viscosity modifying admixture quantity.
With respect to the constructed lake system to which this approach has been applied, three major groups of measurable environmental indicators (parameters) were identified: water quality; flora; and fauna.
The following parameters were used: water temperature, 27.9 ± 1.2°; pH, 7.66 ± 0.11; dissolved oxygen, 6.34 ± 0.15 mg liter−1; and total hardness, 151.8 ± 1.1 mg liter−1 as CaCO3.
{text{WQI}} = mathop sum limits_{i = 1}^{n} W_{i} I_{i} where, ( I_{i} ) is the sub-index of ith water quality parameter, WQI is water quality index and 'n' is the number of water quality parameters considered.
The most important prediction parameters are distinguishable water parameters, for example, water quality, presence of phyto-/zooplankton, vegetation, color (28, 29).
Physical water quality parameters were measured for each water sample on location at the time of sample collection.
The treatment parameters were as follows: water to biomass ratio of 10 1 (w/w dry biomass) and 1.5%H2SO44 (w/w dry biomass).
