Some views on information fusion and logic based approaches in decision making under uncertainty

Decision making under uncertainty is a key issue in information fusion and logic based reasoning approaches. The aim of this paper is to show noteworthy theoretical and applicational issues in the area of decision making under uncertainty that have been already done and raise new open research related to these topics pointing out promising and challenging research gaps that should be addressed in the coming future in order to improve the resolution of decision making problems under uncertainty

Ordering based decision making: a survey

Decision making is the crucial step in many real applications such as organization management, financial planning, products evaluation and recommendation. Rational decision making is to select an alternative from a set of different ones which has the best utility (i.e., maximally satisfies given criteria, objectives, or preferences). In many cases, decision making is to order alternatives and select one or a few among the top of the ranking. Orderings provide a natural and effective way for representing indeterminate situations which are pervasive in commonsense reasoning. Ordering based decision making is then to find the suitable method for evaluating candidates or ranking alternatives based on provided ordinal information and criteria, and this in many cases is to rank alternatives based on qualitative ordering information. In this paper, we discuss the importance and research aspects of ordering based decision making, and review the existing ordering based decision making theories and methods along with some future research directions

An approach for linguistic multi-attribute decision making based on linguistic many-valued logic

There are various types of multi-attribute decision-making (MADM) problems in our daily lives and decision-making problems under uncertain environments with vague and imprecise information involved. Therefore, linguistic multi-attribute decision-making problems are an important type studied extensively. Besides, it is easier for decision-makers to use linguistic terms to evaluate/choose among alternatives in real life. Based on the theoretical foundation of the Hedge algebra and linguistic many-valued logic, this study aims to address multi-attribute decision-making problems by linguistic valued qualitative aggregation and reasoning method. In this paper, we construct a finite monotonous Hedge algebra for modeling the linguistic information related to MADM problems and use linguistic many-valued logic for deducing the outcome of decision making. Our method computes directly on linguistic terms without numerical approximation. This method takes advantage of linguistic information processing and shows the benefit of Hedge algebra

Orderings of fuzzy sets based on fuzzy orderings. Part I: the basic approach

The aim of this paper is to present a general framework for comparing fuzzy sets with respect to a general class of fuzzy orderings. This approach includes known techniques based on generalizing the crisp linear ordering of real numbers by means of the extension principle, however, in its general form, it is applicable to any fuzzy subsets of any kind of universe for which a fuzzy ordering is known|no matter whether linear or partialPeer Reviewe

Corporate Social Responsbility in Business Courses: How Can Generation Y Learn?

This paper deals with the teaching of Corporate Social Responsibility (CSR) in Business courses to Generation Y Business students in Australian universities. Generation Y students embody particular characteristics that may seem paradoxical, such as placing an increased emphasis on an improved materialistic lifestyle alongside green marketing or climate change issues. Generation Ys also highly value a balanced work-leisure environment but are comfortable with living on high levels of debt and expenses. The question then emerges: what is the most effective method of educating Generation Y Business students about CSR? A three-fold approach is proposed: a foundation of life-long learning about the theory and principles of how one goes about making intrinsic decisions in life and business, incorporating concepts of CSR into Business units, and then applying these concepts in Business Internships

The Unbalanced Linguistic Aggregation Operator in Group Decision Making

Published version of an article in the journal: Mathematical problems in engineering. Also available from Hindawi: http://dx.doi.org/10.1155/2012/619162Many linguistic aggregation methods have been proposed and applied in the linguistic decision- making problems. In practice, experts need to assess a number of values in a side of reference domain higher than in the other one; that is, experts use unbalanced linguistic values to express their evaluation for problems. In this paper, we propose a new linguistic aggregation operator to deal with unbalanced linguistic values in group decision making, we adopt 2-tuple representation model of linguistic values and linguistic hierarchies to express unbalanced linguistic values, and moreover,we present the unbalanced linguistic ordered weighted geometric operator to aggregate unbalanced linguistic evaluation values; a comparison example is given to show the advantage of ourmethod

SO SÁNH CÁC BỘ ĐIỀU KHIỂN MỜ VỚI BỘ ĐIỀU KHIỂN SỬ DỤNG ĐẠI SỐ GIA TỬ ĐỐI VỚI LÒ NHIỆT

SUMMARYIn this paper, two controllers such as FLC (Fuzzy Logic Controller) and HAC (Hedge Algebras – Based Controller) are simulated in MATLAB SIMULINK. All the successfully designed controllers were compared. The responses of each controller were plotted in one window to verify the performance of each control algorithm. Simulation study has been done in MATLAB SIMULINK shows that the new controller – HAC produced better response and better performance compared to FLC   strategies for controlling the temperature plant.SUMMARYIn this paper, two controllers such as FLC (Fuzzy Logic Controller) and HAC (Hedge Algebras – Based Controller) are simulated in MATLAB SIMULINK. All the successfully designed controllers were compared. The responses of each controller were plotted in one window to verify the performance of each control algorithm. Simulation study has been done in MATLAB SIMULINK shows that the new controller – HAC produced better response and better performance compared to FLC   strategies for controlling the temperature plant

HEDGE ALGEBRAS, THE SEMANTICS OF VAGUE LINGUISTIC INFORMATION AND APPLICATION PROSPECTIVE

The report aims to show that hedge algebras model actually the proper qualitative semantics of words of linguistic variables based on the argument that the inherent qualitative semantics of words should be expressed through the order relationships, induced by the word semantics, between the words in their respective variable domains, as required by decision making of human daily lives. This makes the hedge algebra based approach to the word semantics quite different from the existing approaches and become the only approach that can immediately deal with the natural qualitative semantics of words. We explain clearly and systematically distinguished features and properties of this approach to show that these seem to make the approach to be sound and ensure its effectiveness in applications. This approach seems to be promising for development of hedge algebra-based method to solve problems in various application fields. For illustration, we will give a short overview of effective results some of the initial applications of hedge algebras in the fields of knowledge based systems and in fuzzy control