[PDF] Top 20 A novel approach to parameter uncertainty analysis of hydrological models using neural networks
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A novel approach to parameter uncertainty analysis of hydrological models using neural networks
... version of the MC simulation method was introduced under the term “generalised likelihood uncertainty estima- tion” (GLUE) by Beven and Binley ...one of the popular methods for analysing ... See full document
14
An ensemble approach to assess hydrological models' contribution to uncertainties in the analysis of climate change impact on water resources
... impact of climate change on water resources for different regions of the ...projection of future river flows is affected by different sources of uncertainty in the hydro-climatic ... See full document
14
VOICE RECOGNITION USING ARTIFICIAL NEURAL NETWORKS AND GAUSSIAN MIXTURE MODELS
... suppression of all the irrelevant information in the voice signals, the clean speech is then converted into streams of feature vectors coefficients containing only the information about the spoken utterance ... See full document
10
Analysis of parameter uncertainty in hydrological modeling using GLUE method: a case study of SWAT model applied to Three Gorges Reservoir Region, China
... validated using the highly efficient Sequential Uncertainty Fitting version-2 (SUFI-2) procedure (Abbaspour et ...initial parameter range was recommended from SWAT ...optimization approach ... See full document
27
Artificial neural networks: A novel approach to analysing the nutritional ecology of a blowfly species, Chrysomya megacephala
... ecology of blowflies. Nevertheless it is important to note that larval density and amount of food (two of the input variables) provided the multiple regression model with few distinct values ... See full document
19
Projected impacts of climate change on groundwater and stormflow in a humid, tropical catchment in the Ugandan Upper Nile Basin
... choice of GCM, climate sensitivity, and PET ...assessment of model parameter uncertainty has been conducted, so these findings should be taken as indicative rather than defini- ...aim ... See full document
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Comparisons of forecasting for hepatitis in Guangxi Province, China by using three neural networks models
... Prediction of incidences of hepatitis diseases has been an ongoing effort and several complex statistical models have been ...(1,1) to forecast the incidence of hepatitis B in Xinjiang, ... See full document
16
Lat. Am. j. solids struct. vol.9 número4
... intends to introduce the novel and efficient exact equivalent function (EF) for well-known deadzone nonlinear- ...ity. To indicate the effectiveness of this EF, the nonlinear vibration ... See full document
10
Probabilistic Artificial Neural Network For Recognizing the Arabic Hand Written Characters
... aimed to document a frame work for giving good recognition accuracy to off-line hand written Arabic characters ...used to train a document-specific OCR system to perform character recognition ... See full document
6
Detection of neovascularization based on fractal and texture analysis with interaction effects in diabetic retinopathy.
... types of features) and vessel segmentation on ROI by adaptive vessel segmentation (consecutive level for ...This approach only detected new vessels on the optic disc (NVD) and the number of samples ... See full document
9
A Novel Approach for Inflation Analysis Using Hidden Markov Model
... (intended to mitigate recessions), and encouraging investment in non- monetary capital ...rates of inflation and hyperinflation are caused by an excessive growth of the money ...low to ... See full document
5
A subsystems approach for parameter estimation of ODE models of hybrid systems
... output of the model compared to the true data, while Table 1 shows the results of the parameter ...thing to note is that we do not obtain unique estimates for each parameter, as ... See full document
12
Calculating the uncertainty associated to the forecast of species dispersals: Stochastic Flow Connectivity
... kind of model. Uncertainty about the individuation of biotic corridors has never been ...2013 to forecast biotic flows over real landscapes, alternative to both circuit theory and ... See full document
9
Evaluation of deciduous broadleaf forests mountain using satellite data using neural network method near Caspian Sea in North of Iran
... diversity of valuable forest products have led to increased population density, creating new residential areas and deforestation ...one of the fundamental methods in management and assessment ... See full document
6
A hybrid end-to-end approach integrating conditional random fields into CNNs for prostate cancer detection on MRI
... Deep Neural Network architecture is developed for the task of classifying clinically significant PCa on non-contrast-enhanced MR ...use of Conditional Random Fields as a Recurrent Neural ... See full document
19
Mat. Res. vol.10 número1
... the Neural Network was trained only by the experimental data (448 input vectors and target ...the Neural Network was very small, indicating that the Neural Network describes the experimental data ... See full document
6
Parameter uncertainty and sensitivity analysis in sediment flux calculation
... usgs.gov/. The selected stations (Table 1) cover a wide range of basin sizes, dis- charge values and suspended sediment concentrations, disregarding intermittent or ephemeral streams that require specific ... See full document
38
Sign Language Recognition using Neural Networks
... gloves to archive the accurate position of hand gestures as its positions are directly ...experience to the users However, vision based system uses camera for data acquisition and it possesses a ... See full document
6
Extração de características de imagens de faces humanas através de wavelets, PCA...
... [GROHMAN, W. M. & DHAWAN, A. P. (2001)] GROHMAN, W. M. and DHAWAN, A. P. (2001). Fuzzy convex set-based pattern classification for analysis of mammographic microcalcifications. Elsevier Science on ... See full document
7
Feasibility of using neural networks to obtain simplified capacity curves for seismic assessment
... region of possible solutions is not well covered by the training vectors, because there are many possible solutions that fit those ...spite of the evidence that an appropriated training of the ANN ... See full document
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