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dc.contributor.advisorCabrera-Ríos, Mauricio
dc.contributor.authorAcosta Cervantes, Mary Carmen
dc.date.accessioned2018-08-22T18:40:01Z
dc.date.available2018-08-22T18:40:01Z
dc.date.issued2016
dc.identifier.urihttps://hdl.handle.net/20.500.11801/816
dc.description.abstractThis work proposes a method which uses a Window of Maximum Similarity (WMS) to find a region of similarity between two responses, one of them with known and desirable characteristics. The WMS method is one of minimization of squared errors and can be used to explore experimentally or pseudo-experimentally generated data to find at least a WMS. This method is a viable element that will serve for the future development of the Optimization by Similarity method. The progressive development of the WMS method and a series of examples are presented to show its feasibility and capability for generating a two-dimensional WMS. Data from real time series served as a basis to generate a one-dimensional WMS. Given that this work corresponds to the initial development of the proposed method, we believe that the results obtained signals to a useful tool for data exploration of interest to detect zones with distinctive patterns.en_US
dc.description.abstractEste trabajo propone un método que usa una Ventana de Máxima Similaridad (WMS por sus siglas en inglés) para encontrar una región de similaridad entre dos respuestas, una de ellas con características conocidas y deseables. El método de WMS es uno de minimización de errores cuadrados que puede ser usado para explorar datos generados seudo o experimentalmente para encontrar al menos una WMS. Este método es un elemento viable que servirá para el futuro desarrollo del método de Optimización por Similaridad. El desarrollo progresivo del método de WMS y una serie de ejemplos son presentados para mostrar su factibilidad y capacidad generando una WMS de dos dimensiones. Datos provenientes de series de tiempo reales sirvieron como base para generar una WMS de una dimensión. Dado que este trabajo corresponde al desarrollo inicial del método propuesto, creemos que los resultados obtenidos apuntan a una herramienta útil para exploración de datos de interés para detectar zonas con distintos patrones.en_US
dc.language.isoEnglishen_US
dc.subjectWMS methoden
dc.subjectOptimizationen_US
dc.titleTowards optimization by similarity: finding windows of maximal similarityen_US
dc.typeThesisen_US
dc.rights.licenseAll rights reserveden_US
dc.rights.holder(c)2016 Mary Carmen Acosta Cervantesen_US
dc.contributor.committeeCesaní Vázquez, Viviana I.
dc.contributor.committeeRivera Santiago, Roberto
dc.contributor.representativeTorres, Pedro
thesis.degree.levelM.S.en_US
thesis.degree.disciplineIndustrial Engineeringen_US
dc.contributor.collegeCollege of Engineeringen_US
dc.contributor.departmentDepartment of Industrial Engineeringen_US
dc.description.graduationSemesterSpring (2nd semester)en_US
dc.description.graduationYear2016en_US


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    Items included under this collection are theses, dissertations, and project reports submitted as a requirement for completing a degree at UPR-Mayagüez.

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