摘要 在投資風險的考量下，合併財務報表能提供投資者完整的企業資訊。而合併財務報表的編製，並未隨著資訊科技的發展，仍多仰賴人工編製。可延伸企業報導語言（XBRL）的興起，提供企業一個揭露財務資訊的標準化規範，XBRL規範標準第二版利用可延伸連結語言（XLink）與可延伸路徑語言（XPath），進行科目元素間關連與處理規則的定義，更加了提升XBRL財務報導的彈性，並更利於延伸之應用。 本研究即根據XBRL規範標準第二版，利用XBRL合併財務報表分類標準套件之建立，進行XBRL合併財務報表的自動化編製，並提供XBRL合併財務報表，提升XBRL財務報導之資訊內涵。 本研究首先根據我國財務會計準則公報第七號「合併財務報表」之購買法處理規定，轉化編製準則為「標準等式」以利分類標準之建立與程式之撰寫。根據「標準等式」，進行資訊分類後，本研究依序建立「合併報表編製資訊分類標準架構」與「XBRL合併財務報表分類標準套件」。前者之目的在提供企業進行內部會計資訊的對應(Mapping)，並將合併報表編製所需之所有資訊，轉換為XBRL格式，以利合併報表自動化編製之進行。而「XBRL合併財務報表分類標準套件」則是利用XBRL連結庫與規則庫的規範，進行合併報表編製準則的描述，以利系統之開發。在完成分類標準的建立之後，本研究以一合併報表編製範例，並利用JAVA程式語言，實作合併報表範例編製系統，以驗證本研究建立之分類標準之可行性。 根據本研究實作範例系統之結果，不僅可以自動化編製XBRL合併財務報表，本研究利用XBRL規則庫進行編製準則之描述，亦提昇合併報表編製系統處理邏輯的正確性與維護便利性。此外，本研究擴充了XBRL之應用範圍，而不限於傳統之財務資訊分析，相關之會計領域問題，皆可利用本研究所建立之架構進行應用。 / Abstract Under the consideration of risk, consolidated reports provide a whole picture of a business entity. As the information age comes, consolidate reports are still prepared by hand. Extensible Business Reporting Language (XBRL) provides a standard format for business to disclose their financial information. The specification version 2.0 of XBRL, in which XML Linking Language (XLink) and XML Path Language (XPath) were adopted to define the relationships and processing rules of XBRL elements, increases the flexibility of XBRL reporting and provides an advantage to the development of XBRL application. This study, on the basis of specification version 2.0, focuses on the computerized preparation of consolidated financial reports by building up the “XBRL Consolidated Reports Taxonomy Package.” In addition to general XBRL-based financial information, business is also capable to disclose XBRL-based consolidated reports with this taxonomy package. Firstly, This study converts the accounting standards of purchase method defined by ROC statement of financial accounting standard no.7: “Consolidated Financial Reports” to several “Standard Formula” in order to build the taxonomies and implement the prototype system. After classifying the information of the standard formulae, this study creates the “Consolidated Reports Preparation Information Taxonomy Framework”, which provides a basis for business to map their internal chart of accounts. As the information mapping was done, business transfers all information (needed by preparation) to XBRL documents. After creating the framework, “XBRL Consolidated Financial Reports Taxonomy Package” was built up. According to the “XBRL Link Base” and “XBRL Rule Base”, this taxonomy package addresses the accounting standard of consolidated reports in the form of XBRL (XML) document. At last, this study gives a consolidating example and implements a prototype system by JAVA to verify the feasibility of the taxonomies created in this study. Based on the implementation of the prototype system, it is not only capable to prepare XBRL consolidated reports automatically but enhances the accuracy of the processing logic and the convenience to maintain the system in compliance with XBRL rule base. Moreover, this study extends the application area of XBRL, which focused on traditional financial information analysis. The structure of this study will be suitable for other accounting issues.

Made available in DSpace on 2016-06-02T19:05:54Z (GMT). No. of bitstreams: 1 3998.pdf: 3486824 bytes, checksum: f1c040adfdc7d0672bc93a058f8a413d (MD5) Previous issue date: 2011-06-28 / Financiadora de Estudos e Projetos / The goal of this work is to study, expand and evaluate the use of multiobjective genetic algorithms and the iterative rule learning approach in fuzzy system generation, especially, in fuzzy rule-based systems, both in automatic fuzzy rule generation from datasets and in fuzzy sets optimization. This work investigates the use of multi-objective genetic algorithms with a focus on the trade-off between accuracy and interpretability, considered contradictory objectives in the representation of fuzzy systems. With this purpose, we propose and implement an evolutive multi-objective genetic model composed of three stages. In the first stage uniformly distributed fuzzy sets are created. In the second stage, the rule base is generated by using an iterative rule learning approach and a multiobjective genetic algorithm. Finally the fuzzy sets created in the first stage are optimized through a multi-objective genetic algorithm. The proposed model was evaluated with a number of benchmark datasets and the results were compared to three other methods found in the literature. The results obtained with the optimization of the fuzzy sets were compared to the result of another fuzzy set optimizer found in the literature. Statistical comparison methods usually applied in similar context show that the proposed method has an improved classification rate and interpretability in comparison with the other methods. / O objetivo deste trabalho é estudar, expandir e avaliar o uso dos algoritmos genéticos multiobjetivo e a abordagem iterativa na geração de sistemas fuzzy, mais especificamente para sistemas fuzzy baseados em regras, tanto na geração automática da base de regras fuzzy a partir de conjuntos de dados, como a otimização dos conjuntos fuzzy. Esse trabalho investiga o uso dos algoritmos genéticos multiobjetivo com enfoque na questão de balanceamento entre precisão e interpretabilidade, ambos considerados contraditórios entre si na representação de sistemas fuzzy. Com este intuito, é proposto e implementado um modelo evolutivo multiobjetivo genético composto por três etapas. Na primeira etapa são criados os conjuntos fuzzy uniformemente distribuídos. Na segunda etapa é tratada a geração da base de regras usando a abordagem iterativa e um algoritmo genético multiobjetivo. Por fim, na terceira etapa os conjuntos fuzzy criados na primeira etapa são otimizados mediante um algoritmo genético multiobjetivo. O modelo desenvolvido foi avaliado em diversos conjuntos de dados benchmark e os resultados obtidos foram comparados com outros três métodos, que geram regras de classificação, encontrados na literatura. Os resultados obtidos após a otimização dos conjuntos fuzzy foram comparados com resultados de outro otimizador de conjuntos fuzzy encontrado na literatura. Métodos estatísticos de comparação usualmente aplicados em contextos semelhantes mostram uma melhor taxa de classificação e interpretabilidade do método proposto com relação a outros métodos.

Cette thèse explique et présente notre démarche de la réalisation d’un système à base de règles de reconnaissance et de classification automatique des EN en arabe. C’est un travail qui implique deux disciplines : la linguistique et l’informatique. L’outil informatique et les règles la linguistiques s’accouplent pour donner naissance à une nouvelle discipline ; celle de « traitement automatique des langues », qui opère sur des niveaux différents (morphosyntaxique, syntaxique, sémantique, syntactico-sémantique etc.). Nous avons donc, dans ce qui nous concerne, mis en œuvre des informations et règles linguistiques nécessaires au service du logiciel informatique, qui doit être en mesure de les appliquer, pour extraire et classifier, par des annotations syntaxiques et/ou sémantiques, les différentes classes d’entités nommées.Ce travail de thèse s’inscrit donc dans un cadre général de traitement automatique des langues, mais plus particulièrement dans la continuité des travaux réalisés au niveau de l’analyse morphosyntaxique par la conception et la réalisation des bases des données lexicales SAMIA et ensuite DIINAR avec l’ensemble de résultats de recherches qui en découlent. C’est une tâche qui vise à l’enrichissement lexical par des entités nommées simples et complexes, et qui veut établir la transition de l’analyse morphosyntaxique vers l’analyse syntaxique, et syntatico-sémantique dans une visée plus générale de l’analyse du contenu textuel. Pour comprendre de quoi il s’agit, il nous était important de commencer par la définition de l’entité nommée. Et pour mener à bien notre démarche, nous avons distingué entre deux types principaux : pur nom propre et EN descriptive. Nous avons aussi établi une classification référentielle en se basant sur diverses classes et sous-classes qui constituent la référence de nos annotations sémantiques. Cependant, nous avons dû faire face à deux difficultés majeures : l’ambiguïté lexicale et les frontières des entités nommées complexes. Notre système adopte une approche à base de règles syntactico-sémantiques. Il est constitué, après le Niveau 0 d’analyse morphosyntaxique, de cinq niveaux de construction de patrons syntaxiques et syntactico-sémantiques basés sur les informations linguistique nécessaires (morphosyntaxiques, syntaxiques, sémantique, et syntactico-sémantique). Ce travail, après évaluation en utilisant deux corpus, a abouti à de très bons résultats en précision, en rappel et en F–mesure. Les résultats de notre système ont un apport intéressant dans différents application du traitement automatique des langues notamment les deux tâches de recherche et d’extraction d’informations. En effet, on les a concrètement exploités dans les deux applications (recherche et extraction d’informations). En plus de cette expérience unique, nous envisageons par la suite étendre notre système à l’extraction et la classification des phrases dans lesquelles, les entités classifiées, principalement les entités nommées et les verbes, jouent respectivement le rôle d’arguments et de prédicats. Un deuxième objectif consiste à l’enrichissement des différents types de ressources lexicales à l’instar des ontologies. / This thesis explains and presents our approach of rule-based system of arabic named entity recognition and classification. This work involves two disciplines : linguistics and computer science. Computer tools and linguistic rules are merged to give birth to a new discipline : Natural Languge Processsing, which operates in different levels (morphosyntactic, syntactic, semantic, syntactico-semantic…). So, in our particular case, we have put the necessary linguistic information and rules to software sevice. This later should be able to apply and implement them in order to recognise and classify, by syntactic and semantic annotations, the different named entity classes.This work of thesis is incorporated within the general domain of natural language processing, but it particularly falls within the scope of the continuity of the accomplished work in terms of morphosyntactic analysis and the realisation of lexical data bases of SAMIA and then DIINAR as well as the accompanying scientific recearch. This task aimes at lexical enrichement with simple and complex named entities and at establishing the transition from the morphological analysis into syntactic and syntactico-semantic analysis. The ultimate objective is text analysis. To understand what it is about, it was important to start with named entity definition. To carry out this task, we distinguished between two main named entity types : pur proper name and descriptive named entities. We have also established a referential classification on the basis of different classes and sub-classes which constitue the reference for our semantic annotations. Nevertheless, we are confronted with two major difficulties : lexical ambiguity and the frontiers of complex named entities. Our system adoptes a syntactico-semantic rule-based approach. After Level 0 of morpho-syntactic analysis, the system is made up of five levels of syntactic and syntactico-semantic patterns based on tne necessary linguisic information (i.e. morphosyntactic, syntactic, semantic and syntactico-semantic information).This work has obtained very good results in termes of precision, recall and F-measure. The output of our system has an interesting contribution in different applications of the natural language processing especially in both tasks of information retrieval and information extraction. In fact, we have concretely exploited our system output in both applications (information retrieval and information extraction). In addition to this unique experience, we envisage in the future work to extend our system into the sentence extraction and classification, in which classified entities, mainly named entities and verbs, play respectively the role of arguments and predicates. The second objective consists in the enrichment of different types of lexical resources such as ontologies.

近年來，隨著科技的進步與工商業的發展，預測技術的創新與改進愈來愈受到重視，同樣地，對於預測準確度的要求也愈來愈高。尤其在經濟建設、人口政策、經營規畫、管理控制等問題上，預測更是決策過程中不可或缺的重要資訊。有鑑於此，本論文嘗試應用模糊關係方程式，提出多變量模糊時間數列建構過程及轉折區間檢測模式理論架構。另一方面，多變量模糊時間數列模式建構過程，研究者曾提出很多轉折點之偵測與檢定方法，然而在實際的例子中，時間數列之結構改變所呈現出來的是一種緩慢的改變過程，即轉折點本身就是模糊不確定。這個概念在建構不同模式分析各國經濟活動數據時更顯重要。本論文針對轉折區間之檢測提出一個完整的認定程序。多變量時間數列系統中的隸屬度函數等於在計算成果指標群時的群集中心。應用本論文提出的方法，我們以德國、法國及希臘之總體經濟指標GDP為例，考慮通貨膨脹率、GDP成長率及投資率來進行轉折區間的檢測。 / In recent years, along with the technological advancement and commercial development, the creation and improvement of forecasting techniques have more and more attention. Especially at the economic developments, population policy, management planning and control, forecasting gives necessary and important information in the decision-making process. Regarding stock market as the example, these numerals of closing price are uncertain and indistinct. Again, the factors of influence on quantity are numerous, such as turnover, exchange rate etc. Therefore, if we consider merely the closing price of front day to build and forecast, we will not only misestimate the future trend, but also will cause unnecessary damage. Owing to this reason, we propose the procedure of multivariate fuzzy time series model constructed and theory structure by fuzzy relation equation. Combining closing price with turnover, we apply our methods to build up multivariate fuzzy time series model on Taiwan Weighted Index and predict future trend while examine the predictive results with average forecasting accuracy. A fuzzy time series is defined on averages of cumulative fuzzy entropies of the tree time series. Finally, an empirical study about change periods identification for Germany, France and Greece major macroeconomic indicators are demonstrated.