Adaboost.RT Based Soil N-P-K Prediction Model for Soil and Crop Specific Data: A Predictive Modelling Approach

2018 ◽  
pp. 322-331 ◽  
Author(s):  
Rashmi Priya ◽  
Dharavath Ramesh
Keyword(s):  
Prediction Model ◽  
Predictive Modelling ◽  
Soil N ◽  
Specific Data ◽  
Modelling Approach

scholarly journals Mobile applications in government services (mG-App) from user's perspectives: A predictive modelling approach

2018 ◽  
Vol 35 (4) ◽  
pp. 557-568 ◽  
Author(s):  
Sujeet Kumar Sharma ◽  
Ali Al-Badi ◽  
Nripendra P. Rana ◽  
Laila Al-Azizi
Keyword(s):  
Mobile Applications ◽  
Predictive Modelling ◽  
Government Services ◽  
Modelling Approach

scholarly journals Screening ground risk in underground works as part of a predictive modelling approach

2020 ◽  
Vol 173 (5) ◽  
pp. 49-57 ◽  
Author(s):  
Rod Eddies ◽  
Ray Wood ◽  
Asher Haynes ◽  
David Warburton ◽  
Chris Pressdee
Keyword(s):  
Predictive Modelling ◽  
Modelling Approach

scholarly journals Dewetting of patterned solid films: Towards a predictive modelling approach

2017 ◽  
Vol 110 (26) ◽  
pp. 263105 ◽  
Author(s):  
M. Trautmann ◽  
F. Cheynis ◽  
F. Leroy ◽  
S. Curiotto ◽  
O. Pierre-Louis ◽  
...  
Keyword(s):  
Predictive Modelling ◽  
Solid Films ◽  
Modelling Approach

Geography of online network ties: A predictive modelling approach

2017 ◽  
Vol 99 ◽  
pp. 9-17 ◽  
Author(s):  
Swanand J. Deodhar ◽  
Mani Subramani ◽  
Akbar Zaheer
Keyword(s):  
Predictive Modelling ◽  
Network Ties ◽  
Modelling Approach

scholarly journals The Effect of the plant Adiantum philippense Extracts on Biofilms Formation and Adhesion to Shigella flexneri: A Predictive Modelling Approach

2021 ◽  
Vol 9 (2) ◽  
pp. 34-39
Author(s):  
Garba Uba ◽  
Abdulhadi Yakubu ◽  
Abdussamad M. Baba
Keyword(s):  
Confidence Interval ◽  
Bacterial Adhesion ◽  
Biofilm Formation ◽  
Shigella Flexneri ◽  
Predictive Modelling ◽  
Bioactive Metabolites ◽  
Biofilm Inhibition ◽  
A Value ◽  
Phytochemical Constituents ◽  
Modelling Approach

In the quest for novel bioactive metabolites, which can also be used as therapeutic agents, Adiantum philippense (A. philippense), an ethnomedically important fern, has become a fascinating herb. In this study, the predictive mathematical modelling of A. philippense crude extract was tested against Shigella flexneri, a common food pathogen for its phytochemical constituents, antagonistic ability, and effect on bacterial adhesion and biofilm formation was calculated. Various kinetics models such as Von Bertalanffy, Baranyi-Roberts, modified Schnute, Modified Richards, Modified Gompertz, Modified Logistics and latest Huang were used to get values for the above kinetic constants or parameters. modified Gompertz of the entire model was found to be the best model with the highest adjusted R2 value and lowest RMSE value. The accuracy and bias factors values were close to unity (1.0). The maximum specific growth rate (mmax (h-1) for S. flexneri treatment with A. philippense extract was significantly much lower (p<0.05) with a value of 0.292 (95% confidence interval of 0.254 to 0.331) compared to control with a value of 0.540 (95% confidence interval of 0.481 to 0.599) indicating potential biofilm inhibition.

Development and application of a predictive modelling approach for household packaging waste flows in sorting facilities

2021 ◽  
Vol 120 ◽  
pp. 290-302
Author(s):  
Kerstin Kleinhans ◽  
Michelle Hallemans ◽  
Sophie Huysveld ◽  
Gwenny Thomassen ◽  
Kim Ragaert ◽  
...  
Keyword(s):  
Predictive Modelling ◽  
Packaging Waste ◽  
Modelling Approach
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