scholarly journals Multiobjective sensitivity analysis to understand the information content in streamflow observations for distributed watershed modeling

2009 ◽  
Vol 45 (2) ◽  
Author(s):  
Thorsten Wagener ◽  
Kathryn van Werkhoven ◽  
Patrick Reed ◽  
Yong Tang
Keyword(s):  
Sensitivity Analysis ◽  
Information Content ◽  
Watershed Modeling ◽  
Distributed Watershed Modeling

APPLICATION OF RELEVANCE VECTOR MACHINE IN SEISMIC ATTENUATION PREDICTION

2007 ◽  
Vol 01 (04) ◽  
pp. 299-309 ◽  
Author(s):  
PIJUSH SAMUI
Keyword(s):  
Sensitivity Analysis ◽  
Information Content ◽  
Relevance Vector Machine ◽  
Seismic Attenuation ◽  
Rock Properties ◽  
Input Parameters ◽  
Practical Tool ◽  
Data Sensitivity

The recently introduced relevance vector machine (RVM) technique is applied to predict seismic attenuation based on rock properties. The RVM provides much sparser regressors without compromising performance, and kernel bases give a small but worthwhile improvement in performance. It evades complexity by producing models that have structure and as a result parameterization process that is appropriate to the information content of the data. Sensitivity analysis has been also performed to investigate the importance of each of the input parameters. The results show that RVM approach has the potential to be a practical tool for determination of seismic attenuation.

scholarly journals A Novel Multi-Criteria Decision Analysis Technique Considering Various Essential Characteristics

2021 ◽  
Author(s):  
Susmita Bandyopadhyay
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Decision Analysis ◽  
Information Content ◽  
Decision Makers ◽  
Multi Criteria Decision Analysis ◽  
Analysis Technique ◽  
Different Types

Abstract This paper has proposed a novel Multi-Criteria Decision Analysis (MCDA) technique that considers relationships among the criteria, relationships among the alternatives, relationships among the criteria and the alternatives, the uncertainty or dilemma that the decision makers face in their decision making, the entropy among the criteria. The dilemma of the decision makers has been captured through the use of Hesitant Fuzzy Elements; the information content among the criteria has been captured by applying the concept of entropy through the application of a technique called IDOCRIW. A kind of sensitivity analysis has been performed to verify the effectiveness of the proposed technique. The proposed method has also been compared with four different types of already existing MCDA techniques, AHP, MAUT, MACBETH and MOORA. Both the sensitivity analysis and the comparison with other methods establish the effectiveness of the proposed technique.

scholarly journals Inverse modelling of atmospheric tracers: non-Gaussian methods and second-order sensitivity analysis

2008 ◽  
Vol 15 (1) ◽  
pp. 127-143 ◽  
Author(s):  
M. Bocquet
Keyword(s):  
Sensitivity Analysis ◽  
Cost Function ◽  
Information Content ◽  
Degrees Of Freedom ◽  
Second Order ◽  
Inverse Modelling ◽  
Cost Functions ◽  
A Posteriori ◽  
Continental Scale ◽  
Non Gaussian

Abstract. For a start, recent techniques devoted to the reconstruction of sources of an atmospheric tracer at continental scale are introduced. A first method is based on the principle of maximum entropy on the mean and is briefly reviewed here. A second approach, which has not been applied in this field yet, is based on an exact Bayesian approach, through a maximum a posteriori estimator. The methods share common grounds, and both perform equally well in practice. When specific prior hypotheses on the sources are taken into account such as positivity, or boundedness, both methods lead to purposefully devised cost-functions. These cost-functions are not necessarily quadratic because the underlying assumptions are not Gaussian. As a consequence, several mathematical tools developed in data assimilation on the basis of quadratic cost-functions in order to establish a posteriori analysis, need to be extended to this non-Gaussian framework. Concomitantly, the second-order sensitivity analysis needs to be adapted, as well as the computations of the averaging kernels of the source and the errors obtained in the reconstruction. All of these developments are applied to a real case of tracer dispersion: the European Tracer Experiment [ETEX]. Comparisons are made between a least squares cost function (similar to the so-called 4D-Var) approach and a cost-function which is not based on Gaussian hypotheses. Besides, the information content of the observations which is used in the reconstruction is computed and studied on the application case. A connection with the degrees of freedom for signal is also established. As a by-product of these methodological developments, conclusions are drawn on the information content of the ETEX dataset as seen from the inverse modelling point of view.

A Novel Multi-Criteria Decision Analysis Technique Incorporating Demanding Essential Characteristics of Existing MCDA Techniques

2021 ◽  
Author(s):  
Susmita Bandyopadhyay
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Decision Analysis ◽  
Information Content ◽  
Decision Makers ◽  
Multi Criteria Decision Analysis ◽  
Rank Reversal ◽  
Analysis Technique ◽  
Different Types

Abstract This paper has proposed a novel Multi-Criteria Decision Analysis (MCDA) technique that considers relationships among the criteria, relationships among the alternatives, relationships among the criteria and the alternatives, the uncertainty or dilemma that the decision makers face in their decision-making, the entropy among the criteria. These characteristics seem to be the essential characteristics of various MCDA techniques as evident from the existing literature. The dilemma of the decision makers have been captured by the use of Hesitant Fuzzy Elements; the information content among the criteria have been captured by applying the concept of entropy through the application of a technique called IDOCRIW. Relationships have been determined by calculating the covariances among the criteria and among the alternatives. A kind of sensitivity analysis, rank reversal method has been performed to verify the effectiveness of the proposed technique. The proposed method has also been compared with four different types of already existing MCDA techniques, AHP, MAUT, MACBETH and MOORA. Both the sensitivity analysis and the comparison with other methods establish the effectiveness of the proposed technique.

Applications of Scanning Microscopy in Biomedical Research

1968 ◽  
Vol 26 ◽  
pp. 354-355
Author(s):  
T. L. Hayes
Keyword(s):  
Information Content ◽  
Biomedical Research ◽  
Biomedical Applications ◽  
Three Dimensional ◽  
Dental Enamel ◽  
Resolving Power ◽  
Whole Mount ◽  
Two Parameters ◽  
Content Information ◽  
Sectioned Tissue

Biomedical applications of the scanning electron microscope (SEM) have increased in number quite rapidly over the last several years. Studies have been made of cells, whole mount tissue, sectioned tissue, particles, human chromosomes, microorganisms, dental enamel and skeletal material. Many of the advantages of using this instrument for such investigations come from its ability to produce images that are high in information content. Information about the chemical make-up of the specimen, its electrical properties and its three dimensional architecture all may be represented in such images. Since the biological system is distinctive in its chemistry and often spatially scaled to the resolving power of the SEM, these images are particularly useful in biomedical research.In any form of microscopy there are two parameters that together determine the usefulness of the image. One parameter is the size of the volume being studied or resolving power of the instrument and the other is the amount of information about this volume that is displayed in the image. Both parameters are important in describing the performance of a microscope. The light microscope image, for example, is rich in information content (chemical, spatial, living specimen, etc.) but is very limited in resolving power.

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