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991.
We propose a data mining approach to predict human wine taste preferences that is based on easily available analytical tests at the certification step. A large dataset (when compared to other studies in this domain) is considered, with white and red vinho verde samples (from Portugal). Three regression techniques were applied, under a computationally efficient procedure that performs simultaneous variable and model selection. The support vector machine achieved promising results, outperforming the multiple regression and neural network methods. Such model is useful to support the oenologist wine tasting evaluations and improve wine production. Furthermore, similar techniques can help in target marketing by modeling consumer tastes from niche markets. 相似文献
992.
In this paper, the robust fault detection filter design problem for linear time invariant (LTI) systems with unknown inputs and modeling uncertainties is studied. The basic idea of our study is to formulate the robust fault detection filter design as a H∞ model-matching problem. A solution of the optimal problem is then presented via a linear matrix inequality (LMI) formulation. The main results include the formulation of robust fault detection filter design problems, the derivation of a sufficient condition for the existence of a robust fault detection filter and construction of a robust fault detection filter based on the iterative of LMI algorithm. 相似文献
993.
We present a probabilistic model of user affect designed to allow an intelligent agent to recognise multiple user emotions
during the interaction with an educational computer game. Our model is based on a probabilistic framework that deals with
the high level of uncertainty involved in recognizing a variety of user emotions by combining in a Dynamic Bayesian Network
information on both the causes and effects of emotional reactions. The part of the framework that reasons from causes to emotions
(diagnostic model) implements a theoretical model of affect, the OCC model, which accounts for how emotions are caused by one’s appraisal of
the current context in terms of one’s goals and preferences. The advantage of using the OCC model is that it provides an affective
agent with explicit information not only on which emotions a user feels but also why, thus increasing the agent’s capability to effectively respond to the users’ emotions. The challenge is that building the
model requires having mechanisms to assess user goals and how the environment fits them, a form of plan recognition. In this paper, we illustrate how we built the predictive part of the affective model by combining general theories with
empirical studies to adapt the theories to our target application domain. We then present results on the model’s accuracy,
showing that the model achieves good accuracy on several of the target emotions. We also discuss the model’s limitations,
to open the ground for the next stage of the work, i.e., complementing the model with diagnostic information.
相似文献
Heather MaclarenEmail: |
994.
In this paper, the robust synchronization control problem of an array of fuzzy cellular neural networks with uncertain stochastically coupling is investigated, which involves constant coupling, discrete time-varying delay coupling and distributed time-varying delay coupling. By using adaptive feedback control scheme and exploiting some stochastic analysis techniques, several sufficient conditions are developed to ensure the synchronization of stochastically hybrid coupled fuzzy neural networks with all admissible uncertainties in mean square. Finally, a numerical example illustrated by scale-free complex networks is provided to show the effectiveness and the applicability of the proposed method. 相似文献
995.
General Adaptive Neighborhood Choquet Image Filtering 总被引:1,自引:0,他引:1
A novel framework entitled General Adaptive Neighborhood Image Processing (GANIP) has been recently introduced in order to
propose an original image representation and mathematical structure for adaptive image processing and analysis. The central
idea is based on the key notion of adaptivity which is simultaneously associated with the analyzing scales, the spatial structures
and the intensity values of the image to be addressed. In this paper, the GANIP framework is briefly exposed and particularly
studied in the context of Choquet filtering (using fuzzy measures), which generalizes a large class of image filters. The
resulting spatially-adaptive operators are studied with respect to the general GANIP framework and illustrated in both the
biomedical and materials application areas. In addition, the proposed GAN-based filters are practically applied and compared
to several other denoising methods through experiments on image restoration, showing a high performance of the GAN-based Choquet
filters.
相似文献
Jean-Charles PinoliEmail: |
996.
Per Bjesse 《Formal Methods in System Design》2009,35(1):56-72
In this paper we present a word-level model checking method that attempts to speed up safety property checking of industrial
netlists. Our aim is to construct an algorithm that allows us to check both bounded and unbounded properties using standard
bit-level model checking methods as back-end decision procedures, while incurring minimum runtime penalties for designs that
are unsuited to our analysis. We do this by combining modifications of several previously known techniques into a static abstraction
algorithm which is guaranteed to produce bit-level netlists that are as small or smaller than the original bitblasted designs.
We evaluate our algorithm on several challenging hardware components. 相似文献
997.
Yih-Kuen Tsay Yu-Fang Chen Ming-Hsien Tsai Kang-Nien Wu Wen-Chin Chan Chi-Jian Luo Jinn-Shu Chang 《Formal Aspects of Computing》2009,21(3):259-275
We introduce a graphical interactive tool, named GOAL, that can assist the user in understanding Büchi automata, linear temporal
logic, and their relation. Büchi automata and linear temporal logic are closely related and have long served as fundamental
building blocks of linear-time model checking. Understanding their relation is instrumental in discovering algorithmic solutions
to model checking problems or simply in using those solutions, e.g., specifying a temporal property directly by an automaton
rather than a temporal formula so that the property can be verified by an algorithm that operates on automata. One main function
of the GOAL tool is translation of a temporal formula into an equivalent Büchi automaton that can be further manipulated visually.
The user may edit the resulting automaton, attempting to optimize it, or simply run the automaton on some inputs to get a
basic understanding of how it operates. GOAL includes a large number of translation algorithms, most of which support past
temporal operators. With the option of viewing the intermediate steps of a translation, the user can quickly grasp how a translation
algorithm works. The tool also provides various standard operations and tests on Büchi automata, in particular the equivalence
test which is essential for checking if a hand-drawn automaton is correct in the sense that it is equivalent to some intended
temporal formula or reference automaton. Several use cases are elaborated to show how these GOAL functions may be combined
to facilitate the learning and teaching of Büchi automata and linear temporal logic.
This work was partially supported by the National Science Council, Taiwan (R.O.C.) under grants NSC94-2213-E-002-089, NSC95-2221-E-002-127,
NSC95-3114-P-001-001-Y02 (iCAST 2006), NSC96-3114-P-001-002-Y (iCAST 2007), and NSC97-2221-E-002-074-MY3. 相似文献
998.
Mahdi Aliyari Shoorehdeli Mohammad Teshnehlab Ali Khaki Sedigh 《Neural computing & applications》2009,18(2):157-174
This paper suggests novel hybrid learning algorithm with stable learning laws for adaptive network based fuzzy inference system
(ANFIS) as a system identifier and studies the stability of this algorithm. The new hybrid learning algorithm is based on
particle swarm optimization (PSO) for training the antecedent part and gradient descent (GD) for training the conclusion part.
Lyapunov stability theory is used to study the stability of the proposed algorithm. This paper, studies the stability of PSO
as an optimizer in training the identifier, for the first time. Stable learning algorithms for the antecedent and consequent
parts of fuzzy rules are proposed. Some constraints are obtained and simulation results are given to validate the results.
It is shown that instability will not occur for the leaning rate and PSO factors in the presence of constraints. The learning
rate can be calculated on-line and will provide an adaptive learning rate for the ANFIS structure. This new learning scheme
employs adaptive learning rate that is determined by input–output data. 相似文献
999.
This article presents a fast self-localization method based on ZigBee wireless sensor network and laser sensor, an obstacle
avoidance algorithm based on ultrasonic sensors for a mobile robot. The positioning system and positioning theory of ZigBee
which can obtain a rough global localization of the mobile robot are introduced. To realize accurate local positioning, a
laser sensor is used to extract the features from environment, then the environmental features and global reference map can
be matched. From the matched environmental features, the position and orientation of the mobile robot can be obtained. To
enable the mobile robot to avoid obstacle in real-time, a heuristic fuzzy neural network is developed by using heuristic fuzzy
rules and the Kohonen clustering network. The experiment results show the effectiveness of the proposed method. 相似文献
1000.
Despite the importance of knowledge transfer for firms involved in foreign direct investment activities, this area has not
received appropriate attention from the perspectives of both the knowledge transferor (i.e., MNC parent) and the knowledge
recipient. To fill in the gap in the current literature we propose a model to understand the links between criteria complicating
the transfer of knowledge and preferences that the company has to focus. This model is based on both the existing literature
as well as views of company representatives and provides a useful methodology for identifying decision making problems on
the transfer of knowledge. In this paper, we investigate the fuzzy linear programming technique (FLP) to analyze these links
and for multiple attribute group decision making (MAGDM) problems with preference information on criteria. To reflect the
decision maker’s subjective preference information and to determine the weight vector of attributes, the technique for order
preference by similarity to ideal solution (TOPSIS) developed by Hwang and Yoon (1995) and the linear programming technique
for multidimensional analysis of preference (LINMAP) developed by Sirinivasan and Shocker (Psychometrica 38:337–369, 1973)
are used. 相似文献