Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 26 for “"Forest classification"”.
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Crystallisation thermodynamics and random forest classification for the prediction of crystallisation outcomes
… outcomes, the result showed that random forest classification models using solvent physical property descriptors can reliably predict crystal morphologies for MFA crystals grown in 20 out of the 28 solvents included in this work. Further characterization of the crystals grown in the …
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The Many Types of Churn and Their Predictive Models
… model. Furthermore, the various supervised classification methods of logistic regression, linear discriminant analysis (LDA), decision trees (DTs) and random forests (RF) are applied and compared in terms of multiple predictive performance measures. The random forest classification measures …
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Measuring Trace Element Concentrations in Artiodactyl Cannonbones using Portable X-Ray Fluorescence
… identified to species. I used a Random Forest classification analysis to predict the family and species of modern comparative and archaeological specimens based on collected trace element data. Species identification accuracy was 70% for modern specimens and 22% for archaeological …
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Detection of Tornado Damage via Convolutional Neural Networks and Unmanned Aerial System Photogrammetry
… a CNN that can classify tornado damage in forests using SfM-derived orthophotos and digital surface models. The findings indicate that a CNN approach provides a higher accuracy than random forest classification, and that DSM-based derivatives add predictive value over the use of the …
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Automatic land-cover-classification derived from high-resolution Ikonos satellite image in the urban atlantic forest in Rio de Janeiro, Brasil by means of an objects-oriented approach
… city of Rio de Janeiro carried out a Land-cover forest classification with visual interpretation using SPOT data. This work produced a compatible thematic map in the scale 1:50,000. The scale of these maps permit to have a global vision of the land change cover but unfortunately do not correspond …
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ARTIFICIAL INTELLIGENCE (AI) APPROACHES IN DRUG DISCOVERY: DEVELOPMENT AND VALIDATION OF NEW STRATEGIES IN VIRTUAL SCREENING CAMPAIGNS
… of a single metabolic reaction with Random Forest classification models. Later, a new tool (MetaSpot) able to predict the site of metabolism for most metabolic reactions was presented, as the natural extension of the previously published MetaClass, since they demonstrated synergistic and …
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Design and development of an electrochemical and infrared spectroscopic medical device for serum-based cancer diagnostics
… ± 6.6% and specificity of 85.3± 8.1% with Random Forest classification, highlighting differences in proteinsecondary structures within clinical serum samples. The integrated diagnostic platformfurther demonstrated the ability to electrochemically detect IDH1-R132H proteins inspiked buffer samples …
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Design and implementation of a cyberinfrastructure for RNA motif search, prediction and analysis
… for motif prediction, including a random forest classification algorithm, a pseudoknot removal algorithm, and a feature ranking algorithm based on the gini impurity measure. A series of experiments including 10-fold cross- validation has been conducted to evaluate the performance of the …
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Development of novel computational techniques for phase identification and thermodynamic modeling, and a case study of contact metamorphism in the Triassic Culpeper Basin of Virginia
… spectra (EDS) in concert with a Random Forest Classification algorithm. This methodology allows for phase identification that it is insensitive to overfitting and noisy spectra. However, this tool is limited by the amount of reference spectra available in the dataset on which the ML …
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Seasonal trends in separability of leaf reflectance spectra for Ailanthus altissima and four other tree species
… least angle regression (LARS) and random forest classification were used to identify a single set of optimal wavelengths across all sampled dates, a set of optimal wavelengths for each date, and the dates for which Ailanthus is most separable from other species. It was found that …
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Development of Machine Learning Models for Generation and Activity Prediction of the Protein Tyrosine Kinase Inhibitors
… inhibitor molecules. We utilized a binary Random Forest classification model to develop a Machine Learning based scoring function to evaluate the generated molecules on Kinase Inhibition Likelihood. By training the model on several chemical features of each known kinase inhibitor, we were able to …
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Entanglement of Cape Fur Seals (Arctocephalus pusillus pusillus) in South Africa
… and welfare of affected individuals. Random Forest classification analysis identified the item of entangling material as an important predictor variable in terms of the severity level of the entanglement. The most common entangling material color was white (35%, n=82) followed by green (13%, …
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Extent And Distribution Of Montane Riparian Zone Vegetation And Representation In Protected Areas In The Sky Island Region Of The Southwestern United States
… has not been quantified. I developed a Random Forest classification model of riparian vegetation for all three types of riparian areas, mapped this vegetation for each of the 25 mountain ranges, described the spatial distribution and connectivity of the vegetation among and between mountain …
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Remote sensing evaluation of Cape parrot habitat in the Eastern Cape: implications for conservation
… the past and present degradation of indigenous forest. The Amathole Mistbelt Forest in the Eastern Cape is the primary habitat for Cape parrot and has historically been heavily degraded. In order to conserve the Cape parrot effectively, there is a need to understand the spatial distribution of …
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Development and Characterization of an Inexpensive Single-Particle Fluorescence Spectrometer for Detection and Classification of Pollen and Other Bioaerosols
… to bridge gaps in bioaerosol detection and classification, though this instrumentation suffers from prohibitively high cost or analysis barriers.</p> <p>This thesis describes the development, characterization, and preliminary application of a new single-particle fluorescence spectrometer …
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Interpretation, Identification and Reuse of Models. Theory and algorithms with applications in predictive toxicology.
… an approach for interpretation of a random forest classification model. This approach allows for the determination of the influence (called feature contribution) of each variable on the model prediction for an individual data. In this part, there are three methods proposed that allow …
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Interpretation, Identification and Reuse of Models. Theory and algorithms with applications in predictive toxicology.
… an approach for interpretation of a random forest classification model. This approach allows for the determination of the influence (called feature contribution) of each variable on the model prediction for an individual data. In this part, there are three methods proposed that allow …
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Classification of Arabic extremist web content through Arabic textual analysis
… in this regard will be made.The division and classification of texts is an important science of linguistics, whether Arabic or otherwise, it summarizes the effort and time consuming of humans to classify these language texts. The importance of this research stems from not only the importance …
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The impacts of voluntary private lands programs on stream fish diversity in the Kaskaskia River Basin, Illinois
… across the Kaskaskia River basin using random forest classification. Of the 64 modeled species, 52 SDMs met my model performance requirements (TSS>0.2). These 52 SDMs were then stacked to obtain an index of species richness across the basin, and then the species richness values were compared …
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Tidal Wetland Inundation and Vegetation Phenology from Space: A Synthesis of Approaches for Characterizing Ecological Status and Inundation Dynamics in Tidal Wetlands with Remote Sensing Observations
… user’s accuracy greater than 83% using a random forest classification. A second classification effort focused on the mapping of wetlands vegetation at the Jug Bay wetlands complex in the Patuxent River. This classification, which also utilized the random forest technique, yielded accuracies of …
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