Comparing results in all but the most cursory way necessitates comparison of the models themselves.
A comparison of the models and a comparison of the models with empirical knowledge further reveal the general needs for further field and validation studies to advance our ecological understanding and management of mangrove wetlands.
In addition, the particle swarm optimization (PSO) learning algorithm is extended to GMDH for a better comparison of the models.
Comparison of the models revealed that the FG models generally performed better than the ANFIS, ANN and SS models.
For comparison of the models, a powerful tool, the artificial neural network (ANN) is used for modelling incipient deposition of sediment in rigid boundary channels.
For comparison of the models, the upper tail asymptotic approximations of their cumulative probability distribution functions of yearly maxima are obtained.
Comparison of the models predictions with experimental and FE data shows that the proposed models accurately predict the connection and the column flange load-deformation response.
This study demonstrates the performance comparison of the models to estimate monthly mean diffuse solar radiation on a horizontal surface for Humid-Subtropical Climatic Region of India.
The focus of this work is the comparison of the models and the analysis of the failure surface these models predict.
We provide a qualitative comparison of the models and then we compare the results of the different models for various Kn for flow past a plate.
The comparison of the models demonstrates that the underlying assumptions regarding the pressure area relationship, ice edge spalling characteristics, dynamic viscosity and strength of the crushed ice are the most important assumptions, although they are highly contentious.
