scholarly journals ANÁLISE MORFOMÉTRICA E PRIORIZAÇÃO DE BACIAS HIDROGRÁFICAS COMO INSTRUMENTO DE PLANEJAMENTO AMBIENTAL INTEGRADO

2016 ◽  
Vol 31 ◽  
pp. 82
Author(s):  
Leonardo Silva Soares ◽  
Wilza Gomes Reis Lopes ◽  
Antonio Carlos Leal Castro ◽  
Gisele Martins Cardoso de Araujo
Keyword(s):  
Weighted Sum ◽  
Weighted Sum Analysis

Este artigo tem como objetivo caracterizar e analisar a morfometria de dez sub-bacias hidrográficas (SBH) do baixo curso do rio Itapecuru, Maranhão, indicando as áreas prioritárias para implementação das ações de conservação e preservação do solo e dos recursos hídricos. Para tanto, foram calculados os parâmetros morfométricos das classes linear, zonal e hipsiométrica. Para a hierarquização e correlação de nove parâmetros morfométricos, foi utilizada a técnica denominada Weighted Sum Analysis (WSA). Foi constatado que as SBHs do Baixo Curso do rio Itapecuru são de pequena dimensão e na rede de drenagem predominam canais intermitentes e de primeira ordem. O escoamento dos canais fluviais apresenta baixa capacidade de transporte e, portanto, de erosão do canal fluvial, sugerindo que os mesmos são susceptíveis a processos de assoreamento, que são potencializados naqueles de menor ordem hierárquica de drenagem. Por outro lado, a baixa declividade das SBH pode atenuar o processo de erosão laminar de suas respectivas áreas de drenagem, uma vez que, o escoamento superficial será mais lento. Observou-se, ainda, que 83,3% da área estudada é zona de média e alta susceptibilidade ambiental, as quais devem ser priorizadas para implementação de ações de gerenciamento dos recursos naturais.

scholarly journals Watershed Prioritization and Decision Making Based On Weighted Sum Analysis, Feature Ranking and Machine Learning Techniques.

2021 ◽  
Author(s):  
Kishanlal Ramlal Darji ◽  
Dhruvesh Prehladbhai Patel ◽  
Vinay Vakharia ◽  
Jaimin Panchal ◽  
Amit Kumar Dubey ◽  
...  
Keyword(s):  
Machine Learning ◽  
Correlation Coefficient ◽  
Cross Validation ◽  
Geographical Information ◽  
Support Vector ◽  
Feature Ranking ◽  
Weighted Sum ◽  
Watershed Prioritization ◽  
Weighted Sum Analysis ◽  
Fold Cross Validation

Abstract Prediction and validation of Compound factors for prioritization of watersheds is an essential application using Machine Learning (ML) Techniques in water resources engineering. In the current paper, a method is proposed to derive 14 morphometric and 3 Topo-hydrological parameters using Remote Sensing (RS) and Geographical Information System (GIS), whereas prediction and validation of compound factor using ML techniques. Compound factor (CF) values are calculated using Weighted Sum Analysis (WSA), ReliefF, correlation coefficient techniques. A ten-fold cross-validation technique is applied to two machine learning models Multi-Layer Perceptron (MLP) and Support Vector Machine (SVM). Predication accuracy of models has been further achieved by feature ranking. The accuracy of ML models is evaluated with three parameters, Mean Absolute Error (MEA), Correlation Coefficient (CC), and Root Mean Square Error (RMSE). With the ranked features and Ten-fold cross-validation, prediction results were found to be better. The methodology will be useful for the accurate prediction of CF values and to reduce the uncertainty in watershed prioritization for conservation techniques for soil and water.

Hypoelliptic Laplacian and Orbital Integrals (AM-177)

2011 ◽  
Author(s):  
Jean-Michel Bismut
Keyword(s):  
Fixed Point ◽  
Symmetric Space ◽  
Heat Kernel ◽  
Geodesic Flow ◽  
Casimir Operator ◽  
Index Theory ◽  
Weighted Sum ◽  
Orbital Integrals ◽  
Hypoelliptic Heat Kernel ◽  
Wave Kernel

This book uses the hypoelliptic Laplacian to evaluate semisimple orbital integrals in a formalism that unifies index theory and the trace formula. The hypoelliptic Laplacian is a family of operators that is supposed to interpolate between the ordinary Laplacian and the geodesic flow. It is essentially the weighted sum of a harmonic oscillator along the fiber of the tangent bundle, and of the generator of the geodesic flow. In this book, semisimple orbital integrals associated with the heat kernel of the Casimir operator are shown to be invariant under a suitable hypoelliptic deformation, which is constructed using the Dirac operator of Kostant. Their explicit evaluation is obtained by localization on geodesics in the symmetric space, in a formula closely related to the Atiyah-Bott fixed point formulas. Orbital integrals associated with the wave kernel are also computed. Estimates on the hypoelliptic heat kernel play a key role in the proofs, and are obtained by combining analytic, geometric, and probabilistic techniques. Analytic techniques emphasize the wavelike aspects of the hypoelliptic heat kernel, while geometrical considerations are needed to obtain proper control of the hypoelliptic heat kernel, especially in the localization process near the geodesics. Probabilistic techniques are especially relevant, because underlying the hypoelliptic deformation is a deformation of dynamical systems on the symmetric space, which interpolates between Brownian motion and the geodesic flow. The Malliavin calculus is used at critical stages of the proof.

COMPUTATION OF A LAMINAR DIFFUSION ETHYLENE/AIR FLAME CONSIDERING SOOT FORMATION AND THE WEIGHTED-SUM-OF-GRAY-GASES MODEL

2018 ◽  
Author(s):  
Luís Gustavo Pires Rodrigues ◽  
Francis França ◽  
Fernando Pereira ◽  
PAULO PAGOT
Keyword(s):  
Soot Formation ◽  
Weighted Sum ◽  
Laminar Diffusion
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