Σκοπός της παρούσας διπλωματικής εργασίας με τίτλο «Εκπαιδευτικό -Υπολογιστικό Πακέτο για Αριθμητική Επίλυση μη Γραμμικών Εξισώσεων, μη Γραμμικών και Γραμμικών συστημάτων και του Προβλήματος της Βελτιστοποίησης», είναι η δημιουργία ενός υπολογιστικού πακέτου για σημαντικά επιλεγμένα θέματα αριθμητικής ανάλυσης, αξιοποιώντας το προγραμματιστικό περιβάλλον της Matlab. Με δεδομένη την ύπαρξη οργανωμένου εργαστηρίου στο Tμήμα Μαθηματικών του Πανεπιστημίου Πατρών και την εύκολη πρόσβαση των φοιτητών σε αυτό, η δημιουργία ενός τέτοιου υπολογιστικού πακέτου θα μπορούσε άμεσα να αξιοποιηθεί από προπτυχιακούς φοιτητές έτσι ώστε: • να αποτελέσει για κάθε φοιτητή ένα συμπληρωματικό εργαλείο, εύκολα προσβάσιμο ακόμα και έξω από την αίθουσα διδασκαλίας, για την ενίσχυση της κατανόησης εννοιών και μεθόδων που δουλεύονται κατά τη διάρκεια της διδασκαλίας, σε χρόνο που θα επιλέξει και με την επανάληψη που επιθυμεί. • να συνδέσει ο φοιτητής τη θεωρία με δικά του παραδείγματα και με άμεσα αποτελέσματα αξιοποιώντας τα υποδείγματα και το βοηθητικό - φιλικό περιβάλλον που έχουμε δημιουργήσει για την υλοποίηση των επιλεγμένων θεμάτων. • να αποτελέσει το κίνητρο για εξάσκηση στον προγραμματισμό μέσω της Matlab, η οποία δεν διδάσκεται και χρησιμοποιείται μόνο προαιρετικά σε επίπεδο εργασιών. / The aim of this work entitled “Educational Software Package for Numerical Solution of Nonlinear Equations, Nonlinear and Linear Systems and for Optimization Problem” is the creation of a software package which could deal with important issues of the field of mathematics called numerical analysis. This is achieved by using the Matlab computational environment. Taking into account the fact that there is a well equipped lab and easily accessible from students, in the Department of Mathematics of the University of Patras, the presented software package could be used by undergraduates students in order to: • be used by each student as a supplemental “tool” which can be easily accessible, even outside the classroom, for the better understanding of meanings and methods which are introduced during of courses, in time that each student may be selected. • combine theory with his examples and have direct results just by using the “models” of the friendly- assistant environment for the specified issues that are analyzed below. • be the motive for exercising the Matlab environment which could be a useful tool for solving many mathematical, and not only, issues.

Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2016-08-08T12:52:58Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) teseCinLeandro.pdf: 1316077 bytes, checksum: 61e762c7526a38a80ecab8f5c7769a47 (MD5) / Made available in DSpace on 2016-08-08T12:52:58Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) teseCinLeandro.pdf: 1316077 bytes, checksum: 61e762c7526a38a80ecab8f5c7769a47 (MD5) Previous issue date: 2016-01-18 / Um intervalo é um tipo de dado complexo usado na agregação de informações ou na representação de dados imprecisos. Este trabalho apresenta duas novas representações para intervalos com o objetivo de se construir novos métodos de agrupamento e regressão linear para este tipo de dado. O agrupamento por nuvens dinâmicas define partições nos dados e associa protótipos a cada uma destas partições. Os protótipos resumem a informação das partições e são usados na minimização de um critério que depende de uma distância, responsável por quantificar a proximidade entre instâncias e protótipos. Neste sentido, propõe-se a formulação de uma nova distância híbrida entre intervalos baseando-se em distâncias para pontos. Os pontos utilizados são obtidos dos intervalos através de um mapeamento. Também são propostas duas versões com pesos para a distância criada: uma com pesos no hibridismo e outra com pesos adaptativos. Na regressão linear, propõe-se a representação dos intervalos através da equação paramétrica da reta. Esta parametrização permite o ajuste dos pontos nas variáveis regressoras que dão as melhores estimativas para os limites da variável resposta. Antes da realização da regressão, um critério é calculado para a verificação da coerência matemática da predição, na qual o limite superior deve ser maior ou igual ao inferior. Se o critério mostra que a coerência não é garantida, propõe-se a aplicação de uma transformação sobre a variável resposta. Assim, este trabalho também propõe algumas transformações que podem ser aplicadas a dados intervalares, no contexto de regressão. Dados sintéticos e reais são utilizados para comparar os métodos provenientes das representações propostas e aqueles presentes na literatura. / An interval is a complex data type used in the information aggregation or in the representation of imprecise data. This work presents two new representations of intervals in order to construct a new cluster method and a new linear regression method for this kind of data. Dynamic clustering defines partitions into the data and it defines prototypes associated with each one of these partitions. The prototypes summarize the information about the partitions and they are used in a minimization criterion which depends on a distance, which is responsible for quantifying the proximity between instances and prototypes. In this way, it is proposed a new hybrid distance between intervals based on a family of distances between points. Points are obtained from the interval through a mapping. Also, it is proposed two versions of the hybrid distance, both with weights: one with weights in hybridism and other with adaptive weights. In linear regression, it is proposed to represent the intervals through the parametric equation of the line. This parametrization allows to find the set of points in the regression variables corresponding to the best estimates for the response variable limits. Before the regression construction, a criterion is computed to verify the mathematical consistency of prediction, where the upper limit must be greater than or equal to the lower. If the test shows that consistency is not guaranteed, then the application proposes a transformation of the response variable. Therefore, this work also proposes some transformations that can be applied to interval data in the regression context. Synthetic and real data are used to compare the proposed methods and those one proposed on literature.