Environmental factors are the difficulties of entrepreneurs when facing in the whole process of entrepreneurship. Due to the dynamic complexity of environmental factors and the limitations of entrepreneurial recogniti...
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ISBN:
(纸本)9789814619967
Environmental factors are the difficulties of entrepreneurs when facing in the whole process of entrepreneurship. Due to the dynamic complexity of environmental factors and the limitations of entrepreneurial recognition, an entrepreneur will find it difficult to comprehend the business environment. The analysis of entrepreneurial environment assessment is born based on the necessity, effectiveness of the proposed model, giving a pioneering project environmental assessment, establishing venture project dynamic environmental evaluation algorithm, which application will be approved by examples.
The aggregating fuzzy (S,N)-subimplications is obtained by the OWA-operator performed over the families of triangular sub(co)norms along with fuzzy negations. (S,N)-subimplications are characterized by the generalized...
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ISBN:
(纸本)9789814619967
The aggregating fuzzy (S,N)-subimplications is obtained by the OWA-operator performed over the families of triangular sub(co)norms along with fuzzy negations. (S,N)-subimplications are characterized by the generalized associativity and distributive properties together with extensions of the exchange and neutrality principles. As the main results, these families of subimplications extend related S-implications by preserving their corresponding properties. We also discuss the action of automorphisms on such fuzzy implication classes.
In this paper, we propose a self-adaption MapReduce framework based on granular computing (GrC), named gMapReduce. In the MapReduce model, the input data is partitioned into many data blocks which is the key step for ...
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ISBN:
(纸本)9789814619967
In this paper, we propose a self-adaption MapReduce framework based on granular computing (GrC), named gMapReduce. In the MapReduce model, the input data is partitioned into many data blocks which is the key step for the following parallel processing. The number of data blocks depends on the size of the block. It means the block size will affect the total running time. According to the proposed gMapReduce model, we design two algorithms, naive and advanced, for finding the appropriate granule. Both two algorithms can find the appropriate size of data block, thereby accelerating the running process effectively.
In this paper, a rule base representation with certainty factors is proposed firstly along with its inference method. Such a rule base is designed with certainty factors embedded in the consequence terms, rule terms a...
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ISBN:
(纸本)9789814619967
In this paper, a rule base representation with certainty factors is proposed firstly along with its inference method. Such a rule base is designed with certainty factors embedded in the consequence terms, rule terms as well as in the antecedent terms, which is shown to be capable of capturing uncertainty. As the evidential reasoning approach is applied to the rule combination, the overall representation and inference framework can be applied in rule based system for human decision making due to the fact. A numerical example is examined to show the implementation process of the proposed method, as comparing with a classical approache we can see its high perfprmance.
In virtual reality-based 3D garment design, one important issue is to minimize the perceptual gap between real and virtual products in their static and dynamic representations so that they can be considered as the sam...
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ISBN:
(纸本)9789814619967
In virtual reality-based 3D garment design, one important issue is to minimize the perceptual gap between real and virtual products in their static and dynamic representations so that they can be considered as the same by both designers and consumers. In this paper, we present a new method of online experimental design for quickly controlling human perception on virtual garments towards real products within a very few number of sensory tests. For each real product, this method uses the uniform design to generate the initial virtual fabrics then the principle of online active learning to sequentially create new virtual samples according to the evaluated similarity degrees of previous samples related to the real product. The proposed design of experiments will permit to identify the optimal values of the design parameters corresponding to the desired fabric. The criterion of data sensitivity is used to determine the most relevant design parameter on which we will enhance searches in the following step.
Existing research shows significant associations between online search volume and stock price on market level. Due to the individuality of each stock and limited attention of investors, how to effectively discover the...
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ISBN:
(纸本)9789814619967
Existing research shows significant associations between online search volume and stock price on market level. Due to the individuality of each stock and limited attention of investors, how to effectively discover the association between search volume and the price on individual stock level is worth studying. This paper investigates the association pattern between search volume variation and stock price variation on individual stock level, and designs a so-called ATARII method, which can effectively discover qualified association rules between search volume and stock price in an after-temporal manner. Furthermore, real world data experiments are conducted on China's A-share stock market. Based on the discovered after-temporal associations, a new trading strategy is designed, i.e., ATARII-Trading, which obtains best cumulative return, significantly outperforming market level trading strategy, buy-and-hold strategy and random strategy as well as A-share 300 index.
Co-clustering is an unsupervised machine learning technique, and it simultaneously clusters rows and columns for the input data matrix. In text co-clustering, the input data matrix is a high dimension and sparse matri...
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ISBN:
(纸本)9789814619967
Co-clustering is an unsupervised machine learning technique, and it simultaneously clusters rows and columns for the input data matrix. In text co-clustering, the input data matrix is a high dimension and sparse matrix, and the traditional co-clustering ignores the similarity between word and word, and the similarity between text and word. In this work, we propose a text co-clustering using matrix block and correlation coefficient. In the first step, the matrix block and correlation coefficient are used to reduce dimension, and the relevant feature terms are merged as a hybrid feature term. In the second step, the text terms are clustered using K-means algorithm. And in the last step, the hybrid feature terms and text terms are iteratively clustered by the adjusting algorithms. Experimental results show that our algorithm is effective for a high dimension and sparse text matrix.
This article deals with propositional fuzzy modal logic with evaluated syntax based on MV-algebras. We focus on its semantic theory from the viewpoint of Pavelka's graded semantics of propositional fuzzy logic, in...
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ISBN:
(纸本)9789814619967
This article deals with propositional fuzzy modal logic with evaluated syntax based on MV-algebras. We focus on its semantic theory from the viewpoint of Pavelka's graded semantics of propositional fuzzy logic, investigate the I, tautologies based on different Kripke frames. We also define the notion of I, semantic consequence operation, its some basic properties are presented.
In this paper, an intelligent control he rotary inverted pendulum by fuzzy logic is presented. Specifically, the design consists of a Takagi-Sugeno fuzzy model to approximate the non-linear system to a succession of p...
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ISBN:
(纸本)9789814619967
In this paper, an intelligent control he rotary inverted pendulum by fuzzy logic is presented. Specifically, the design consists of a Takagi-Sugeno fuzzy model to approximate the non-linear system to a succession of points where a linear system is described. A feedback gain is obtained that allows the stabilization of the inverted pendulum in a higher attractor than in the case of analytic Full State Feedback controller or Linear Quadratic Regulator.
This paper aims at establishing an outline of 2(n)-valued propositional calculus (2(n)P) to set logical foundation for big data science. After introducing the characteristics of big data and the significance of resear...
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ISBN:
(纸本)9789814619967
This paper aims at establishing an outline of 2(n)-valued propositional calculus (2(n)P) to set logical foundation for big data science. After introducing the characteristics of big data and the significance of researching on big data, we briefly analyze features of famous L-n system. This paper specifies 2(n)P from logical semantic and syntax. We firstly define connectives including negation inverted left perpendicular and disjunction boolean OR, and define conjunction boolean AND and implications -> based on them;we prove the {inverted left perpendicular, ->} is adequate set of connective. Then we structure the axiom set including all axioms of classical logic, and prove modus ponens and the consistent of 2(n)P, yet give the soundness theorem and the adequate theorem of 2(n)P.
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