Mapping Sahelian Ecosystem Vulnerability to Vegetation Collapse: Vegetation Model Optimization

2021 ◽  
Author(s):  
Wim Verbruggen ◽  
Hans Verbeeck ◽  
Stephanie Horion ◽  
Niels Souverijns ◽  
Guy Schurgers
Keyword(s):  
Model Optimization ◽  
Vegetation Model ◽  
Ecosystem Vulnerability

ERROR LOCALIZATION DIAGNOSTIC MODEL OPTIMIZATION IN DIGITAL STATE MACHINES NETWORKS

2019 ◽  
Author(s):  
Irina Bystrova ◽  
E. Danil'chuk ◽  
Boris Podkopaev
Keyword(s):  
Single Component ◽  
Diagnostic Model ◽  
State Machines ◽  
Model Optimization ◽  
Error Localization ◽  
Diagnostic Models

The problem of constructing a diagnostic model for a network S consisting of a number of digital automata is considered, provided that the diagnostic models of all network components are known. It is assumed that these models are given by systems of logical equations, and the errors to be detected are localized in any but a single component of the network.

scholarly journals Sensitivity and Performance Analyses of the Distributed Hydrology–Soil–Vegetation Model Using Geomorphons for Landform Mapping

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2032
Author(s):  
Pâmela A. Melo ◽  
Lívia A. Alvarenga ◽  
Javier Tomasella ◽  
Carlos R. Mello ◽  
Minella A. Martins ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Overland Flow ◽  
Hydrological Model ◽  
Model Performance ◽  
Soil Parameters ◽  
Vegetation Model ◽  
Landform Classification ◽  
Physically Based ◽  
And Performance ◽  
Streamflow Simulation

Landform classification is important for representing soil physical properties varying continuously across the landscape and for understanding many hydrological processes in watersheds. Considering it, this study aims to use a geomorphology map (Geomorphons) as an input to a physically based hydrological model (Distributed Hydrology Soil Vegetation Model (DHSVM)) in a mountainous headwater watershed. A sensitivity analysis of five soil parameters was evaluated for streamflow simulation in each Geomorphons feature. As infiltration and saturation excess overland flow are important mechanisms for streamflow generation in complex terrain watersheds, the model’s input soil parameters were most sensitive in the “slope”, “hollow”, and “valley” features. Thus, the simulated streamflow was compared with observed data for calibration and validation. The model performance was satisfactory and equivalent to previous simulations in the same watershed using pedological survey and moisture zone maps. Therefore, the results from this study indicate that a geomorphologically based map is applicable and representative for spatially distributing hydrological parameters in the DHSVM.

Model Optimization and Stability of Hemoglobin Analysis in Human Soluble Blood Samples by FTIR/ATR Spectroscopy

2011 ◽  
Vol 55-57 ◽  
pp. 1168-1171
Author(s):  
Tao Pan ◽  
Ai Hong Peng ◽  
Wen Jie Huang
Keyword(s):  
Signal To Noise Ratio ◽  
Attenuated Total Reflection ◽  
Partial Least Square ◽  
Least Square ◽  
Model Optimization ◽  
Optimal Model ◽  
Blood Samples ◽  
Quantification Method ◽  
Atr Spectroscopy ◽  
Pls Method

Using Fourier transform infrared spectroscopy (FTIR), attenuated total reflection (ATR) technology and partial least square (PLS) method, the rapid quantification method of hemoglobin (HGB) in human soluble blood samples was established. Based on the distribution of samples’ HGB chemical value and absorbance on 1543 cm-1 which had the highest signal to noise ratio for HGB, all samples were divided into calibration set and prediction set for 50 times. PLS models were established for all divisions, based on the average data RMSEPAve, the stable optimal model was selected, the corresponding PLS factor, RMSEPAve and RP,Ave were 2, 6.81 g/L and 0.943 respectively.

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