The development of a fuzzy expert system to help top decision makers in political and investment domains

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel UniversityThe world’s increasing interconnectedness and the recent increase in the number of notable regional and international events pose greater and greater challenges for political decision-making, especially the decision to strengthen bilateral economic relationships between friendly nations. Typically, such critical decisions are influenced by certain factors and variables that are based on heterogeneous and vague information that exists in different domains. A serious problem that the decision-maker faces is the difficulty in building efficient political decision support systems (DSS) with heterogeneous factors. One must take many factors into account, for example, language (natural or human language), the availability, or lack thereof, of precise data (vague information), and possible consequences (rule conclusions). The basic concept is a linguistic variable whose values are words rather than numbers and are therefore closer to human intuition. A common language is thus needed to describe such information which requires human knowledge for interpretation. To achieve robustness and efficiency of interpretation, we need to apply a method that can be used to generate high-level knowledge and information integration. Fuzzy logic is based on natural language and is tolerant of imprecise data. Fuzzy logic’s greatest strength lies in its ability to handle imprecise data, and it is perfectly suited for this situation. In this thesis, we propose to use ontology to integrate the scattered information resources from the political and investment domains. The process started with understanding each concept and extracting key ideas and relationships between sets of information by constructing object paradigm ontology. Re-engineering according to the object-paradigm (OP) provided quality for the developed ontology where conceptualization can provide more expressive, reusable object and temporal ontology. Then fuzzy logic has been integrated with ontology. And a fuzzy ontology membership value that reflects the strength of an inter-concept relationship to represent pairs of concepts across ontology has been consistently used. Each concept is assigned a fixed numerical value representing the concept consistency. Concept consistency is computed as a function of strength of all the relationships associated with the concept. Fuzzy expert systems enable one to weigh the consequences (rule conclusions) of certain choices based on vague information. Rule conclusions follow from rules composed of two parts, the if antecedent (input) and the then consequent (output). With fuzzy expert systems, one uses fuzzy logic toolbox graphical user interface (GUI) tools to build up a fuzzy inference system (FIS) to aid in decision-making. This research includes four main phases to develop a prototype architecture for an intelligent DSS that can help top political decision makers

Laparoscopy Pneumoperitoneum Fuzzy Modeling

Abstract: Gas volume to intra-peritoneal pressure fuzzy modeling for evaluating pneumoperitoneum in videolaparoscopic surgery is proposed in this paper. The proposed approach innovates in using fuzzy logic and fuzzy set theory for evaluating the accuracy of the prognosis value in order to minimize or avoid iatrogenic injuries due to the blind needle puncture. In so doing, it demonstrates the feasibility of fuzzy analysis to contribute to medicine and health care. Fuzzy systems is employed here in synergy with artificial neural network based on backpropaga tion, multilayer perceptron architecture for building up numerical functions. Experimental data employed for analysis were collected in the accomplishment of the pneumoperitoneum in a random population of patients submitted to videolaparoscopic surgeries. Numerical results indicate that the proposed fuzzy mapping for describing the relation from the intra peritoneal pressure measures as function injected gas volumes succeeded in determinining a fuzzy model for this nonlinear system when compared to the statistical model

Do UK universities communicate their brands effectively through their websites?

This paper attempts to explore the effectiveness of UK universities’ websites. The area of branding in higher education has received increasing academic investigation, but little work has researched how universities demonstrate their brand promises through their websites. The quest to differentiate through branding can be challenging in the university context, however. It is argued that those institutions that have a strong distinctive image will be in a better position to face a changing future. Employing a multistage methodology, the web pages of twenty UK universities were investigated by using a combination of content and multivariable analysis. Results indicated ‘traditional values’ such as teaching and research were often well communicated in terms of online brand but ‘emotional values’ like social responsibility and the universities’ environments were less consistently communicated, despite their increased topicality. It is therefore suggested that emotional values may offer a basis for possible future online differentiation

Weighted logics for artificial intelligence : an introductory discussion

International audienceBefore presenting the contents of the special issue, we propose a structured introductory overview of a landscape of the weighted logics (in a general sense) that can be found in the Artificial Intelligence literature, highlighting their fundamental differences and their application areas