2019
DOI: 10.1016/j.fuel.2018.11.088
|View full text |Cite
|
Sign up to set email alerts
|

Development of high biomass and lipid yielding medium for newly isolated Rhodotorula mucilaginosa

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
15
0
1

Year Published

2019
2019
2024
2024

Publication Types

Select...
8
2

Relationship

1
9

Authors

Journals

citations
Cited by 26 publications
(16 citation statements)
references
References 44 publications
0
15
0
1
Order By: Relevance
“…During training the data over fits and substantial error will be accumulated on the validation. When the error on the validation reaches the threshold point the weights and biases are adjusted to minimize the error [22,23]. Network topology have a crucial role in predicting results, the input-output neuron of ANN is the resemblance of input and output data used in this study.…”
Section: Optimization Of Process Parameters Using Artificial Neural Nmentioning
confidence: 99%
“…During training the data over fits and substantial error will be accumulated on the validation. When the error on the validation reaches the threshold point the weights and biases are adjusted to minimize the error [22,23]. Network topology have a crucial role in predicting results, the input-output neuron of ANN is the resemblance of input and output data used in this study.…”
Section: Optimization Of Process Parameters Using Artificial Neural Nmentioning
confidence: 99%
“…The regression models accurately described the experimental data, which indicated a correlation among the three factors which affected the three responses as discussed above. This statement is supported by the fact that the values of the correlation coefficient (R 2 ) for cell mass production, lipid concentration, and lipid content were 0.94, 0.92, and 0.95, respectively, which in turn suggests that most of the errors/variation in the model can be explained [47]. It is known that the R 2 value is always between 0 and 1 and that a value closer to 1 indicates stronger models and better predictions of the responses.…”
Section: Optimization Of Lipid Production From Cg In the Second Stagementioning
confidence: 84%
“…During training the data over fits and substantial error will be accumulated on the validation. When the error on the validation reaches the threshold point the weights and biases are adjusted to minimize the error [17,18]. Network topology have a crucial role in predicting results, the input-output neuron of ANN is the resemblance of input and output data used in this study.…”
Section: Optimization Of Process Parameters Using Artificial Neural Nmentioning
confidence: 99%