Titlebook: Intelligent Decision Technologies; Proceedings of the 4 Junzo Watada,Toyohide Watanabe,Lakhmi C. Jain Conference proceedings 2012 Springer-

概觀

A Stackelberg Location on a Network with Fuzzy Random Demand Quantities Using Possibility Measurer finding Stackelberg equilibrium. For solving the problem, it is reformulated as the problem to find the optimal solutions maximizing a degree of possibility under some chance constraint for the leader. Theorems for its complexity are shown based upon the characteristics of the facility location.

lattice

A Study of Maslow’s Hierarchy of Needs and Decision-Makingsion-making that is composed of two systems. One system is value judgment pressure expressed by value judgment distance (ego-involvement scale), and the other system is decisions made from value selection pressure expressed by distance among basic needs. (basic needs [1][2] ) This is a view of the basic structure of values and decision-making.

stress-test

An Alternative View of Uncertainty in Bilateral Bargaining Models with Incomplete Informationtes. This is done by postulating an alternative view of uncertainty in decision making in economic interactions. Thus an alternative model of bilateral bargaining with incomplete information is formulated.

圣人

APEX

Classifying Attributes with Game-Theoretic Rough Setsbute as a decision problem within a game. In particular, multiple measures representing importance levels for an attribute are incorporated into a unified framework to obtain an effective attribute classification mechanism. Demonstrative example suggests that the method may be efficient in classifying different types of attributes.

Thyroxine

認(rèn)為

Intellectual

色情

Building a Type II Fuzzy Qualitative Regression Model use type II fuzzy set as well as type II fuzzy data in this paper). Here, qualitative values are assumed to be fuzzy degree of membership in qualitative categories and qualitative change in the objective external criterion is given as the fuzziness of the output.

FLAX

Building Fuzzy Random Autoregression Model and Its Applicationom autoregression model is introduced and to solve the problem, we resort to some heuristic solution based on .-confidence intervals. Finally, a numerical example of Shanghai Composite Index is provided.