TL;DR: In this article, the fuzzy multi-attribute AD approach is also developed and it is compared by one of fuzzy AHP methods in the literature, and the selection process has been accomplished by aiding a software that includes crisp AD and fuzzy AD.

TL;DR: Experimental results demonstrate that DE/EDA outperforms the DE algorithm and the EDA, and combines global information extracted by EDA with differential information obtained by DE to create promising solutions.

TL;DR: This paper is an introduction of the OAI protocol for metadata harvesting and the main technical idea of OAI-PMH is how to implementing the protocol.

TL;DR: To investigate the performance of the proposed approach for time series forecasting in response to real data, a stock market forecasting system has been implemented and tested on two stock market indexes, and the good forecasting capability of the approach repeatedly outperformed the "Buy and Hold" strategy.

TL;DR: An extension of the classic Yager's approach to involve more sophisticated criteria of goodness, search methods, etc, and shows how fuzzy queries are related to linguistic summaries, which makes it possible to implement such linguistic data summaries.

TL;DR: In this paper, a minimax disparity approach for obtaining OWA operator weights is proposed by minimizing the maximum difference between any two adjacent weights.

TL;DR: The main contribution of this paper is that the definition, conversion, and treatment of vague and complex multi-level criteria as set memberships under the fuzzy set theory are employed to develop a practical model for business purpose.

TL;DR: An efficient distributed model predictive control scheme based on Nash optimality, in which the on-line optimization of the whole system is decomposed into that of several small co-operative agents in distributed structures, thus it can significantly reduce computational complexity in models predictive control of large-scale systems.

TL;DR: For given two digital images both equipped with each digital connectedness, it is shown that the digital fundamental groups of both images do not necessarily lead to thedigital fundamental group of the product image.

TL;DR: An H∞ control design approach is developed using basis-dependent Lyapunov function for a class of discrete-time fuzzy systems with uncertainty that leads to some sufficient results in the form of strict linear matrix inequalities (LMIs).

TL;DR: This paper presents a robust technique embedding the watermark of signature information or textual data around the ROI of a medical image based on genetic algorithms.

TL;DR: The results show that the fuzzy integral is more suitable than a traditional multicriteria evaluation method for human subjective evaluation, or when criteria are not mutually independent.

TL;DR: A tongue-computing model (TCoM) is presented for the diagnosis of appendicitis based on quantitative measurements that include chromatic and textural metrics that are computed from true color tongue images by using appropriate techniques of image processing.

TL;DR: A hybrid search algorithm with heuristics for resource allocation problem encountered in practice is proposed that has both the advantages of genetic algorithm and ant colony optimization that can explore the search space and exploit the best solution.

TL;DR: Simulation and real process testing results show that the proposed MMPC approach is effective in HVAC system control applications.

TL;DR: It is proved that the algebra L/f which is the set of all cosets of f is a BL- algebra, and is isomorphic to the BL-algebra L/ff(1), where ff(1) = {x ∈ L|f(x) =f( 1)}.

TL;DR: A new sufficient condition guaranteeing the H∞ performance of the TS fuzzy systems is first derived, which is expressed by a set of linear matrix inequalities (LMIs), which is less conservative than previous results obtained within the quadratic framework.

TL;DR: By empirical experiments on real-world datasets it is verified that the proposed decision tree learning model has better or equivalent classification accuracy compared to three well known machine learning algorithms.

TL;DR: A neuro-fuzzy hybrid approach is used to design the fuzzy rule base of the intelligent system for control and a Sugeno fuzzy model is built for controlling the stepping motor drive with feedback.

TL;DR: These investigations confirm not only that the results of the proposed fuzzy economic models are consistent with those of the conventional crisp models, but also demonstrate that the proposed methods represent readily implemented possibility analysis tools for use in the arena of uncertain financial decision-making.

TL;DR: This paper underlines the association of two computer go approaches, a domain-dependent knowledge approach and Monte Carlo and sets up experiments demonstrating the relevance of this association, used by Indigo at the 8th computer olympiad.

TL;DR: The paper deals with problems of fuzzy measure restoration from insufficient data on a finite set, and the unique fuzzy subset (fuzzy object) is constructed from the associated probabilities of the restored fuzzy measure.

TL;DR: A new model for unsupervised learning and reasoning on a special type of cognitive maps realized with Petri nets using a Hebbian-type learning algorithm that converges to stable points in both encoding and recall phases is presented.

TL;DR: The role of individual characteristics including: (a) personality variables proposed by the big five theory of personality, (b) cognitive orientation, and (c) math and logic skills on technophobia are investigated.

TL;DR: To establish and run a knowledge management system, it is the precondition that recognizing the conception of data, information, knowledge and wisdom as well as the relation among them is recognized.

TL;DR: This paper proposes structured learning for a partner robot based on the interactive teaching mechanism and is composed of a spiking neural network, self-organizing map, steady-state genetic algorithm, and softmax action selection.

TL;DR: Conventional dynamic systems are converted to different types of LDS for the purpose of verification and comparison to establish a methodology of design, modeling, and analysis of complex decision-making processes bridging the machine world in numbers and the human world in words.

TL;DR: This paper extends the work on discovering fuzzy association rules with degrees of support and implication (ARsi) to discover ARsi with hierarchy so as to express more semantics due to the fact that hierarchical relationships usually exist among fuzzy sets associated with the attribute concerned.

TL;DR: The evolution of agents' beliefs are traced and their consistency with the observed aggregate market behavior is examined to show that the stock price volume relation may be regarded as a generic property of a financial market, when it is correctly represented as an evolving decentralized system of autonomous interacting agents.