This paper introduces the notion of interval migrative functions. Also, we show a necessary and sufficient condition to a interval function to he migrative and that the interval canonical representation of a migrative...
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ISBN:
(纸本)9789814619967
This paper introduces the notion of interval migrative functions. Also, we show a necessary and sufficient condition to a interval function to he migrative and that the interval canonical representation of a migrative function f (in the usual sense) is an interval migrative function and preserves some properties of f,
Evolving Fuzzy Neural Networks (EFuNNs) are dynamic connectionist feed forward networks. Several paper can be found in the literature in which EFuNN reach better results than other methods. However, only one paper was...
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ISBN:
(纸本)9789814619967
Evolving Fuzzy Neural Networks (EFuNNs) are dynamic connectionist feed forward networks. Several paper can be found in the literature in which EFuNN reach better results than other methods. However, only one paper was found in which EFuNN results were analyzed with respect to some statistical distributions of data. This study has as goal to complement the previous study, evaluating the EFuNN performance using four other statistical distributions. Results of assessment are provided and show different accuracy according to the statistical distribution of data.
Instance selection is an important pre-processing step in pattern recognition and machine learning. In this paper, we propose a novel instance selection method based on genetic algorithm for nearest neighbor (AGAIS_NN...
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ISBN:
(纸本)9789814619967
Instance selection is an important pre-processing step in pattern recognition and machine learning. In this paper, we propose a novel instance selection method based on genetic algorithm for nearest neighbor (AGAIS_NN), which compose of three main parts: elitist strategy, adaptive probabilities of crossover and mutation, and fitness function. To validate the proposed algorithm, we compare AGAIS_NN with other classical instance selection methods. The experimental results show that our proposal is more effective and useful than other approaches.
In the present work, we assess the application of the Nash-Particle Swarm Optimization (Nash-PSO) algorithm to the analysis of timber markets in the Amazon forest within a game theoretical framework. The usage of the ...
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ISBN:
(纸本)9789814619967
In the present work, we assess the application of the Nash-Particle Swarm Optimization (Nash-PSO) algorithm to the analysis of timber markets in the Amazon forest within a game theoretical framework. The usage of the PSO algorithm and the game theory's best response concept are the bases of the Nash-PSO algorithm, implemented for such analysis. With the Nash-PSO algorithm it is possible to analyze the interactions of players in a continuous space of strategies, for non-linear objective functions with a fast and accurate convergence. The results also demonstrate the viability of the Nash-PSO algorithm in the estimation of real values for government investment in forest areas.
Hesitant fuzzy sets are used to handle the situations where a set of values are possible in defining membership functions. In urban transformation problems usually there are multiple actors with different perspectives...
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ISBN:
(纸本)9789814619967
Hesitant fuzzy sets are used to handle the situations where a set of values are possible in defining membership functions. In urban transformation problems usually there are multiple actors with different perspectives and they represent hesitant evaluations on subjective criteria. Hesitant fuzzy linguistic term sets (HFLTS) enable aggregating the different linguistic evaluations of different actors without loss of information. This paper proposes a hierarchical multiattribute method based on hesitant fuzzy linguistic term sets for prioritizing the urban transformation projects in Istanbul.
The main goal of this paper is to expose the possibilities for applying of the new fuzzy methods for the evaluational modeling of credit risk, which is in its nature a composite quantity, and as such could be convenie...
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ISBN:
(纸本)9789814619967
The main goal of this paper is to expose the possibilities for applying of the new fuzzy methods for the evaluational modeling of credit risk, which is in its nature a composite quantity, and as such could be conveniently modeled through Interpolative Boolean Algebra. This approach to modeling allows expressing intensity measures of single components/properties of credit risk, as much as complex logical constructions made of basic components and their logical interactions, which altogether increases the possibilities of consistent mathematical articulation of the problem of aggregation of multicriterial aspects of credit risk into a single representative parameter.
This paper presents the graphical illustration of the Boolean consistent real-valued relations on the example of two two-dimensional objects. Consistent real-valued relations are based on the real-valued realization o...
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ISBN:
(纸本)9789814619967
This paper presents the graphical illustration of the Boolean consistent real-valued relations on the example of two two-dimensional objects. Consistent real-valued relations are based on the real-valued realization of the Boolean algebra.
Selection of relevant parameters from a high dimensional process operation setting space is a problem frequently encountered in industrial process modelling. This paper presents a method for selecting the most relevan...
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ISBN:
(纸本)9789814619967
Selection of relevant parameters from a high dimensional process operation setting space is a problem frequently encountered in industrial process modelling. This paper presents a method for selecting the most relevant fabric mechanical parameters for each sensory quality feature. The proposed relevancy criterion has been developed using two approaches. The first utilizes a fuzzy sensitivity criterion by exploiting from experimental data the relationship between mechanical parameters and all the sensory quality features for each evaluator. Next an OWA aggregation procedure is applied to aggregate the ranking lists provided by different evaluators. In the second approach, a panel of experts provides their ranking lists of mechanical features according to their professional knowledge. Also by applying OWA, the data sensitivity-based ranking list and the knowledge-based ranking list are combined to determine the final ranking list and the final relevant mechanical parameters for a given sensory quality feature.
This paper is a continuation of previous works on the semantic 2-tuples model, a representation model to deal with unbalanced linguistic terms sets. We propose to study how our semantic 2-tuples can help language proc...
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ISBN:
(纸本)9789814619967
This paper is a continuation of previous works on the semantic 2-tuples model, a representation model to deal with unbalanced linguistic terms sets. We propose to study how our semantic 2-tuples can help language processing since they offer a fuzzy semantic interpretation of words describing imprecise data. Thus, we propose two measures to catch the semantics of a set of words. We show the relevance of the measures in a use case where a lexicon has to be enriched.
Traditional patent classification schemes, which are mainly based on either IPC or UPC, are too complicated and general to meet the needs of specific industries. The paper proposes a dynamic classification method, the...
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ISBN:
(纸本)9789814619967
Traditional patent classification schemes, which are mainly based on either IPC or UPC, are too complicated and general to meet the needs of specific industries. The paper proposes a dynamic classification method, the "user demand-driven patent topic classification", aiming to a specific industry or technology area. In the paper, classification topics of the method are grouped into technical topic, application topic and application-technical mixed topic. Automatic process of the method using machine learning techniques is presented as well. A case study on the technology area of system on a chip (SoC) is conducted using machine learning techniques, validating the feasibility of the method. The experiment results demonstrate that automatic patent topic classification based on the combination of patents' metadata and citation information can obtain perfect performance with a greatly simplified document preprocessing.
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