The robustness analysis of intuitionistic fuzzy difference (IFD) is based on an evaluation of the delta sensitivity in representable fuzzy negations, triangular norms and conorms. The results in the class of IFD opera...
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ISBN:
(纸本)9789813146969
The robustness analysis of intuitionistic fuzzy difference (IFD) is based on an evaluation of the delta sensitivity in representable fuzzy negations, triangular norms and conorms. The results in the class of IFD operators preserve projections and dual constructions related to their intuitionistic approach.
Production of high quality goods at the lowest achievable cost as quickly as possible is the main biggest challenge for manufacturing organizations. The design and implementation of agile supply chains (ASCs) is attra...
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ISBN:
(纸本)9789813146969
Production of high quality goods at the lowest achievable cost as quickly as possible is the main biggest challenge for manufacturing organizations. The design and implementation of agile supply chains (ASCs) is attracting more interest, recently. ASCs require suppliers to strengthen their flexible and agile attributes to remain competitive and to react quickly to market changes and customer preferences. Therefore, each organization in the chain will get the maximum benefit from ASC if they are able to identify satisfactorily agile suppliers. The aim of this research is to apply an analytical multi criteria model, more specifically the analytical hierarchy process to get criteria weights and axiomatic design to get the ranking of alternatives under intuitionistic fuzzy environment that is based on the group decision making approach. The verification of the proposed methodology is performed with the help of a case study in the Turkish apparel industry.
Most of the web content today is generated on the fly using dynamic server side scripts. This web is known as hidden web or deep web. Extracting data from deep web is a non-trivial task as the layout and structure of ...
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ISBN:
(纸本)9789813146969
Most of the web content today is generated on the fly using dynamic server side scripts. This web is known as hidden web or deep web. Extracting data from deep web is a non-trivial task as the layout and structure of deep web is highly irregular. Deep web data extraction is important as it is useful for meta-search engine applications and comparative shopping lists. Before such data can be used for further processing, it must first be aligned so that the processing task could be made easier. This process is called data alignment. In the early days, data are aligned based on the conventional DOM Tree structure, and its underlying visual cue and more recently, ontologies have been used to align deep web data. However, this approach makes little use of the full semantics provided by WordNet libraries. In this paper, we propose a full-fledged multilingual WordNet to align data records. Unlike existing approaches, we make full use of the semantic properties provided by WordNet libraries, with multi-language support. Experimental results show that our approach is highly efficient in data alignment.
To solve boolean satisfiability (SAT) problems more efficient, this paper presents a polarity decision policy, which calculates the polarity of variable according to the Jeroslow-Wang heuristic and Glucose heuristic, ...
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ISBN:
(纸本)9789813146969
To solve boolean satisfiability (SAT) problems more efficient, this paper presents a polarity decision policy, which calculates the polarity of variable according to the Jeroslow-Wang heuristic and Glucose heuristic, the proposed approach is embed into the SAT solver Glucose2.3. Experiment results show that the performance of the new solver, named Glucose_IM, is better than Glucose2.3 on the application certified UNSAT instances and hard combinatorial SAT instances at SAT competition 2013.
In view of the semi-supervised classification problem for imbalanced data, a new semi-supervised learning algorithm based on SVM is proposed. In this method, the classification method based on SVM for unbalanced data ...
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ISBN:
(纸本)9789813146969
In view of the semi-supervised classification problem for imbalanced data, a new semi-supervised learning algorithm based on SVM is proposed. In this method, the classification method based on SVM for unbalanced data is used to tag unlabeled documents in order to deal with the imbalance of data. The experimental results on several benchmark data sets show the validity of this method.
Image segmentation is an essential step for many computer vision tasks. In this paper, we propose two pooling strategies to evaluate the image segmentation quality. Based on the hypotheses that correlate with the huma...
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ISBN:
(纸本)9789813146969
Image segmentation is an essential step for many computer vision tasks. In this paper, we propose two pooling strategies to evaluate the image segmentation quality. Based on the hypotheses that correlate with the human perception of segmentation quality, we explore to assign perceptual meaningful weights to the quality map. To the best of our knowledge, this is the first work that adopts perceptual pooling strategies in the quantitative segmentation evaluation. Extensive experiments are conducted on the subjective evaluation benchmark and BSDS500, which indicate that the proposed strategies can improve the performance of evaluation measures and produce a more perceptually meaningful judgment on the segmentation quality.
The problem of the accumulation of experience and the use of decision-making in the previously observed situations is researched. The main objective of the research is development of the data model that provides the u...
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ISBN:
(纸本)9789813146969
The problem of the accumulation of experience and the use of decision-making in the previously observed situations is researched. The main objective of the research is development of the data model that provides the upgrade of reliability of decision-making on the basis of experience. The concept of the image of the situation, which has not clearly defined center and a neighborhood, is introduced. The main thing is not trajectories in feature space but the admissible transformations of situations and solutions.
Opinions, the key influencer of human behavior and activity is ranked as of one of the strong factors that determine the effectiveness of one's strategy and approach in terms of influential power and trend setting...
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ISBN:
(纸本)9789813146969
Opinions, the key influencer of human behavior and activity is ranked as of one of the strong factors that determine the effectiveness of one's strategy and approach in terms of influential power and trend setting capabilities. This highlights the importance of sentiment analysis done upon the extracted data. Today, statistics have shown significantly that most opinions can be obtained via many social media platforms. Social media has provided a convenient platform for web users to comfortably share their thoughts and to boldly voice up. Having to process such huge amount of data, it is proposed that automated sentiment analysis is done when extracting social media data. Using an effective algorithm which produces meaningful information from raw data, the possibilities of venturing deeper into areas like decision making and influential thinking are simply limitless.
Objective Programming Method for an Intuitionistic Trapezoidal Fuzzy Model (MOPM-ITFM) is proposed to improve the accuracy of estimation by optimizing the parameters. The advantage of the proposal is more realistic to...
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ISBN:
(纸本)9789813146969
Objective Programming Method for an Intuitionistic Trapezoidal Fuzzy Model (MOPM-ITFM) is proposed to improve the accuracy of estimation by optimizing the parameters. The advantage of the proposal is more realistic to consider the degrees of both the acceptance and the rejection of intuitionistic trapezoidal fuzzy number (ITFN) than conventional fuzzy model only considering the former. The proposal is realized by tuning the membership function shapes, the adaptive factors of matching degree and the rule weights. The constraint condition of the proposal is considered in the definition of ITFN. Input fuzzy partitions of an Intuitionistic Trapezoidal Fuzzy Model (ITFM) are modified through the proposal. MOPM-ITFM has been used for a medical diagnosis. Compared with Single Objective Programming Method (SOPM), the results show that the mean square error (MSE) between the output given by domain experts and the output of (MOPM-ITFM) improves 47% than that of SOPM. In the further work, the interpretability of input fuzzy partitions is also needed to be improved in ITFM.
When handling, multivariate impacts analysis, i.e. in acknowledging multiple incommensurable dimensions, any decision making process requires a step of value judgement declaration. Here is presented an extension of al...
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