QUANTITATIVE LANDSLIDE HAZARD ASSESSMENT IN
... landslide location‖ elements. This model makes us able to evaluate the conditional probability of occurrence of a landslide with a magnitude larger than an arbitrarily amount within a specific time period and at a given location. Part of the Seattle, WA area was selected to evaluate the competence o ...
... landslide location‖ elements. This model makes us able to evaluate the conditional probability of occurrence of a landslide with a magnitude larger than an arbitrarily amount within a specific time period and at a given location. Part of the Seattle, WA area was selected to evaluate the competence o ...
Bayesian Algorithmic Modeling in Cognitive Science
... and their application to other layers of Marr’s hierarchy are in order, but reserved for a later portion of this document (Chapter 5). In the subjectivist approach to probabilities, probabilities are considered as an extension of logic calculus for uncertain knowledge representation and manipulation ...
... and their application to other layers of Marr’s hierarchy are in order, but reserved for a later portion of this document (Chapter 5). In the subjectivist approach to probabilities, probabilities are considered as an extension of logic calculus for uncertain knowledge representation and manipulation ...
fulltext
... This thesis considers computer-assisted troubleshooting of heavy vehicles such as trucks and buses. In this setting, the person that is troubleshooting a vehicle problem is assisted by a computer that is capable of listing possible faults that can explain the problem and gives recommendations of whi ...
... This thesis considers computer-assisted troubleshooting of heavy vehicles such as trucks and buses. In this setting, the person that is troubleshooting a vehicle problem is assisted by a computer that is capable of listing possible faults that can explain the problem and gives recommendations of whi ...
Disregarding Duration Uncertainty in Partial Order - LIA
... which is an approximation for the expected value E[τ ]. We simulated each of our POSs 10,000 times (i.e. |∆| = 10, 000). We have considered two types of distribution for the δi variables, namely 1) a uniform distribution and 2) a discrete distribution where the duration can be either αDi with probab ...
... which is an approximation for the expected value E[τ ]. We simulated each of our POSs 10,000 times (i.e. |∆| = 10, 000). We have considered two types of distribution for the δi variables, namely 1) a uniform distribution and 2) a discrete distribution where the duration can be either αDi with probab ...
Brief Survey on Computational Solutions for Bayesian Inference
... From 2006 to 2011, the research group lead by Professor Viktor Prasanna at the University of Southern California produced a vast body of work contributing with solutions for the implementation of exact inference in multi/manycore CPUs and GPUs. Starting in 2006, Namasivayam et al. presented a study ...
... From 2006 to 2011, the research group lead by Professor Viktor Prasanna at the University of Southern California produced a vast body of work contributing with solutions for the implementation of exact inference in multi/manycore CPUs and GPUs. Starting in 2006, Namasivayam et al. presented a study ...
Oracle Data Mining Programmer`s Guide
... Oracle Corporation; they are provided under a license agreement containing restrictions on use and disclosure and are also protected by copyright, patent and other intellectual and industrial property laws. Reverse engineering, disassembly or decompilation of the Programs, except to the extent requi ...
... Oracle Corporation; they are provided under a license agreement containing restrictions on use and disclosure and are also protected by copyright, patent and other intellectual and industrial property laws. Reverse engineering, disassembly or decompilation of the Programs, except to the extent requi ...
Feature Selection for Unsupervised Learning
... are given class labels, it is natural that we want to keep only the features that are related to or lead to these classes. But in unsupervised learning, we are not given class labels. Which features should we keep? Why not use all the information we have? The problem is that not all features are imp ...
... are given class labels, it is natural that we want to keep only the features that are related to or lead to these classes. But in unsupervised learning, we are not given class labels. Which features should we keep? Why not use all the information we have? The problem is that not all features are imp ...
Continuous Cast Width Prediction Using a Data Mining Approach
... casting machine cast slabs of constant thickness with varying width. One important aspect of the continuously cast strand that must be controlled, is the strand width. The strand width exiting from the casting machine, has a direct influence on the product yield which in turn influences the profitab ...
... casting machine cast slabs of constant thickness with varying width. One important aspect of the continuously cast strand that must be controlled, is the strand width. The strand width exiting from the casting machine, has a direct influence on the product yield which in turn influences the profitab ...
A Visual Framework Invites Human into the Clustering
... Clustering is a basic technique commonly used in data analysis tasks, where there is little prior information (e.g. statistical models) available about the data. In the past few decades, researchers have provided hundreds of clustering algorithms. Most of the researches have been focused on the effi ...
... Clustering is a basic technique commonly used in data analysis tasks, where there is little prior information (e.g. statistical models) available about the data. In the past few decades, researchers have provided hundreds of clustering algorithms. Most of the researches have been focused on the effi ...
Scalar utility theory and proportional processing_ What does it
... That is, if a just noticeable difference between a 10 kg weight and another weight is 10γ kg, where γ is a positive constant, then only differences exceeding 20γ kg can be detected when comparing a weight to a 20 kg weight. Drawing on a body of previous theory (e.g., Gibbon, 1977; Gibbon, Church, Fa ...
... That is, if a just noticeable difference between a 10 kg weight and another weight is 10γ kg, where γ is a positive constant, then only differences exceeding 20γ kg can be detected when comparing a weight to a 20 kg weight. Drawing on a body of previous theory (e.g., Gibbon, 1977; Gibbon, Church, Fa ...
