Modeling Decisions for Artificial Intelligence: Second人工智能建模决策/2005年国际会议录 word 下载地址 百度云 2025 极速 在线

　　This book constitutes the refereed proceedings of the Second International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2005, held in Tsukuba, Japan in July 2005.

The 40 revised full papers presented together with an introduction by the editors and 4 invited lectures were thoroughly reviewed and selected from 118 submissions. The papers are devoted to theory and tools for modeling decisions, as well as applications that encompass decision making processes and information fusion techniques. Special focus is given to applications related with risk, security and safety.

Introduction

Modeling Decisions for Artificial Intelligence: Theory,Tools and Applications

Invited Talks

Capacities and Games on Lattices:A Survey of Results

Cryptosystems Based on Elliptic Curve Paiting

Building a Braing-Informatics Portal on the Wisdom Web with a Multi-layer Grid: A New Challenge for Web Intelligence Research

Soft Computing in Human Centered Systems Thinking

Regular Papers

Qualitative Model of Game Theory

Regularity Properties of Null-Additive Fuzzy Measure on Metric Spaces

A Statistical Criterion of Consistency in the Analytic Hierarchy Process

Evaluating the Airline Service Quality by Fuzzy OWA Operators

An Adaptive Module for the Consensus Reaching Process in Group Decision Making Problems

Qualitative Reasoning Model for Tradeoff Analysis

Evaluation of Control Performance of Multi-stage Fuzzy Reasoning in Anti-lock Braking System for Railways Using Fuzzy Reasoning

One-Way and Two-Party Authenticated ID-Based Key Agreement Protocols Using Pairing

Noise-Robust Watermarking for Numerical Datasets

Possibilistic Approach to Kernel-Based Fuzzy c-Means Clustering with Entropy Regularization

Fuzzy c-Means Clustering in the Presence of Noise Cluster for Time Series Analysis

Quantification of Multivariate Categorical Data Considering Clusters of Items and Individuals

A New Approach to Fuzzification of Memberships in Cluster Analysis

Dynamic Clustering Based on Universal Gravitation Model

Extracting Classification Rules with Support Rough Neual Networks

……

Author Index

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