A mixed-data evaluation in group TOPSIS with differentiated decision power

[[abstract]]This main objective of this paper is to provide decision support for mixed data in group Technique for Order Preference by Similarity to Idea Solution (TOPSIS) with differentiated decision power. We use a signum function to compare the ordinal performance of alternatives on any qualitative criterion, or the partial information provided by decision makers. The proposed process for ordinal information is uniformly coherent with the traditional TOPSIS steps, preserving the characteristic of distance-based utilities. Ordinal weights are also considered herein, and the decision power of the group members is formulated by their weights under an agreement in the group. Two examples demonstrate that the proposed approach has some benefits and achieves robustness with two types of sensitivity analyses. Some discussions and their limitations to the approach are also provided.[[notice]]補正完

Un cadre de référence pour le choix d'une procédure d'agrégation multicritère

info:eu-repo/semantics/publishe

Algorithme d'apprentissage pour inf\ue9rer les param\ue8tres de proaftn

PROAFTN is a multicriteria classification method that makes it possible to directly assign potential actions to different classes. In this work, we suggest a training algorithm that can be used to automatically adjust the parameters of the method. This algorithm utilizes local search and meta-heuristic tools to minimize the difference between the classification results obtained by the PROAFTN method and the a priori results in the training set.PROAFTN est une proc\ue9dure de classification multicrit\ue8re qui permet d'affecter directement les actions potentielles aux diff\ue9rentes classes. Dans ce travail nous proposons un algorithme d'apprentissage qui permettra d'ajuster automatiquement les param\ue8tres de cette m\ue9thode. Cet algorithme fait appel aux outils de recherche locale et de m\ue9ta-heuristique pour minimiser l'\ue9cart entre les r\ue9sultats de classification obtenus par la m\ue9thode PROAFTN et ceux donn\ue9s \ue0 priori dans l'ensemble d'apprentissage.NRC publication: Ye

Author

Military organizations have to deal with an increasing number of documents coming from different sources and in various formats (paper, fax, e-mails, electronic documents, etc.) The documents have to be screened, analyzed and categorized in order to interpret their contents and gain situation awareness. These documents should be categorized according to their contents to enable efficient storage and retrieval. In this context, intelligent techniques and tools should be provided to support this information management process that is currently partially manual. Integrating the recently acquired knowledge in different fields in a system for analyzing, diagnosing, filtering, classifying and clustering documents with a limited human intervention would improve efficiently the quality of information management with reduced human resources. A better categorization and management of information would facilitate correlation of information from different sources, avoid information redundancy, improve access to relevant information, and thus better support decision-making processes. DRDC Valcartier’s ADAC system (Automatic Document Analyzer and Classifier) incorporates several techniques and tools for document summarization and semantic analysi

Approved for release by

© Sa majesté la reine, représentée par le ministre de la Défense nationale, 2006 Future military operations will still rely on increasingly complex joint and multinational operations. Thus, innovative concepts, doctrine and technologies are required to support the emergence of new planning and execution systems, ones that are more flexible, adaptive, interoperable and responsive to a changing and uncertain environment. The ability to conduct joint and multinational operations imposes shared information and systems interoperability requirements, as well as common standards to operate among coalition members. Growing global complexity and the rapid pace of current and future military operations call for a transition from the rigid vertical organizational structure of the past to the more integrated, modular and tailored decision support required by today’s demand. The recently proposed Network Centric Operations (NCO) framework offers a unique setting to take on emerging challenges. Even though recent attempts in deliberate planning tools focus on providing “on the fly ” precise tailoring and time phasing of force deployment in crisis situations, suitabl

Automatic Documents Analyzer and Classifier

Military organizations have to deal with an increasing number of documents coming from different sources and in various formats (paper, fax, e-mail messages, electronic documents). These documents have to be screened, analyzed and categorized in order to interpret their content and gain situation awareness. These documents should be categorized according to their content to enable efficient storage and retrieval. In this context, intelligent techniques and tools should be provided to support this information management process that is currently partly manual. Integrating the recently acquired knowledge in different fields in a system for analyzing, diagnosing, filtering, classifying and clustering documents with a limited human intervention would improve efficiently the quality of information management with reduced human resources. A better categorization and management of information would facilitate correlation of information from different sources, avoid information redundancy, improve access to relevant information, and thus better support decision-making processes. The RDDC-Valcartier's ADAC system (Automatic Documents Analyzer and Classifier) incorporates several techniques and tools for document summarizing and semantic analysis based on ontology of a certain domain (e.g. terrorism), and algorithms of diagnostic, classification and clustering. In this paper, we describe the architecture of the system and the techniques and tools used at each step of the document processing. For the first prototype implementation, the focus has been concentrated on the terrorism domain to develop document corpus and related ontology.Les organisations militaires doivent faire face \ue0 un nombre croissant de documents provenant de diverses sources et dans divers formats (papier, t\ue9l\ue9copies, courriels, documents \ue9lectroniques). Ces documents doivent \ueatre v\ue9rifi\ue9s, analys\ue9s et cat\ue9goris\ue9s afin d'en interpr\ue9ter le contenu et de prendre connaissance de la situation. Ils devraient \ueatre cat\ue9goris\ue9s selon leur contenu pour permettre un entreposage et une r\ue9cup\ue9ration efficaces. Dans cette optique, des technologies et outils intelligents devraient \ueatre fournis afin de soutenir la gestion de l'information qui se fait en partie manuellement. En int\ue9grant les connaissances r\ue9cemment acquises dans divers domaines \ue0 un syst\ue8me qui analyse, diagnostique, filtre, classifie et regroupe les documents avec une intervention humaine limit\ue9e, on am\ue9liorerait convenablement la qualit\ue9 de la gestion de l'information avec moins d'effectifs. Une meilleure cat\ue9gorisation et gestion de l'information faciliteraient la corr\ue9lation de l'information issue de diff\ue9rentes sources, \ue9viteraient la redondance, am\ue9lioreraient l'acc\ue8s \ue0 de l'information pertinente et permettraient donc de mieux soutenir les processus d\ue9cisionnels. Le syst\ue8me ADAC (Analyseur et classificateur automatiques pour les documents) de RDDC Valcartier comprend plusieurs techniques et outils pour r\ue9sumer les documents et effectuer des analyses s\ue9mantiques qui se basent sur l'ontologie d'un domaine particulier (p. ex. le terrorisme) ainsi que les algorythmes de diagnostic, de classification et de regroupement. Dans ce document, nous d\ue9crivons l'architecture du syst\ue8me ainsi que les techniques et outils utilis\ue9s \ue0 chaque \ue9tape du traitement des documents. Pour la r\ue9alisation du premier prototype, nous nous sommes concentr\ue9s sur le domaine du terrorisme pour \ue9laborer le corps du document et l'ontologie qui s'y rattache.NRC publication: Ye