Search results for "Multiple discriminant analysis"

showing 4 items of 4 documents

Analysis of compatibility between lighting devices and descriptive features using Parzen’s kernel: application to flaw inspection by artificial vision

2000

We present a supervised method, developed for industrial inspections by artificial vision, to obtain an adapted combination of descriptive features and a lighting device. This method must be implemented under real-time constraints and therefore a minimal number of features must be selected. The method is based on the assessment of the discrimination power of many descriptive features. The objective is to select the combination of descriptive features and lighting system best able to discriminate flawed classes from defect-free classes. In the first step, probability densities are computed for flawed and defect-free classes and for each tested combination. The discrimination power of the fea…

Multiple discriminant analysisbusiness.industryMachine visionComputer scienceGeneral EngineeringImage processingPattern recognitionFeature selectionMachine learningcomputer.software_genreAtomic and Molecular Physics and OpticsKernel (image processing)Compatibility (mechanics)Principal component analysisArtificial intelligencebusinesscomputerOptical Engineering
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CORPORATE BANKRUPTCY AND INSOLVENCY PREDICTION MODEL

2021

In any competitive economy, the risk of bankruptcy is pervasive. The research aims to contribute in improving the predictive power of bankruptcy and insolvency risk among companies by introducing new methods of processing and validation. This paper investigates the extensive application of the Z score model for predicting the economic-financial stability of Romanian companies in the manufacturing and extractive industries. A list of 37 financial indicators determined on the basis of the balance sheet data of 80 companies for the period 2015–2018 was used. Stepwise Least Squares Estimation through the Forward method allowed the identification of the most relevant ones. Canonical discriminant…

Multiple discriminant analysisInsolvencyHF5001-6182insolvencyComputer scienceStability (learning theory)Economic growth development planningmultiple discriminant analysisprediction modelbankruptcyDiscriminant function analysisBankruptcyHD72-88EconometricsPredictive powerBusinessBalance sheetRobustness (economics)FinanceriskTechnological and Economic Development of Economy
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The Influence of Intangible Assets in the Company Performance: The Case of the World’s Most Profitable Corporations

2020

Intangible assets are no longer a competitive advantage, but a must if a company wants to create value for the long-term and maintain performance at a high level compared with its peers. Due to the various factors that contribute to the performance of a company, there are a plethora of methods to measure the impact of each one. This paper’s objective is to measure the performance of the company, with a focus on the contribution of the intangible assets. To fulfil this objective, financial ratios will be used, and a method (‘Calculated Intangible Value’) to quantify the impact of intangible assets. By applying a multiple discriminant analysis, two functions will result, a general one, and an…

Multiple discriminant analysisMeasure (data warehouse)Value (economics)Financial ratioBusinessCorporationCompetitive advantageIndustrial organization
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Distinctive attributes for predicted secondary structures at terminal sequences of non-classically secreted proteins from proteobacteria

2008

Abstract C- and N-terminal sequences (64 amino acid residues each) of 89 non-classically secreted type I, type III and type IV proteins (Swiss-Prot/TrEMBL) from proteobacteria were transformed into predicted secondary structures. Multivariate analysis of variance (MANOVA) confirmed the significance of location (C- or N-termini) and secretion type as essential factors in respect of quantitative representations of structured (a-helices, b-strands) and unstructured (coils) elements. The profiles of secondary structures were transcripted using unequal property values for helices, strands and coils and corresponding numerical vectors (independent variables) were subjected to multiple discriminan…

terminal sequencesMultiple discriminant analysisGeneral Immunology and MicrobiologybiologyQH301-705.5General Neurosciencesecondary structureComputational biologyLinear discriminant analysisbiology.organism_classificationBioinformaticsdiscriminant analysisGeneral Biochemistry Genetics and Molecular BiologyCross-validationSecretory proteinDiscriminantprotein secretionSecretionProteobacteriaBiology (General)General Agricultural and Biological SciencesProtein secondary structureproteobacteriaOpen Life Sciences
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