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Titlebook: Computational Intelligence in Information Systems; Proceedings of the C Somnuk Phon-Amnuaisuk,Thien-Wan Au,Saiful Omar Conference proceedin

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Engelbert Westkämper,Carina Löfflerure is key-dependent. The study uses binary polynomials and analyzes the correlation between the parameter sets recommended in the EESS 1v2 (2003) and Jeffrey Hoffstein et al. (2003). The observed relationships are then used to recommend an extended parameter selection criteria which ensures inverti
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Günter Heitbreder,Ralf Litzenbergd whenever a snake image is given as input. Our experiment shows that backpropagation neural network and nearest neighbour are highly accurate with greater than 87 % accuracy on CEDD descriptor in this problem.
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Personalentwicklung im Otto Versandn of self-efficacy and perceived enjoyment are also significant antecedents to perceived ease of use and perceived usefulness. This study confirms that self-efficacy, perceived enjoyment, perceived ease of use, and perceived usefulness are important variables of acceptance and attitude towards using 3D virtual learning spaces.
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Ehrenfried Stoffer,Wolfgang Sommermeyercted on six real datasets. Finally, the noisy instances are removed and relabeled and the performance was then measured using evaluation criteria. The findings of this study show that classification filtering have a potential capability to detect class noise.
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Personalentwicklung bei der Drägerwerk AGparticular cluster. The resulted rules were more intuitive to investors as compared with our previous work. Thus, the profiling process became easier. The evaluation results also showed that profiling stocks using class association rules helps investors in making better investment decisions.
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Estimation of Confidence-Interval for Yearly Electricity Load Consumption Based on Fuzzy Random Auto81 to 2000 are examined in evaluating the performance of three different left-right spreads of fuzzy random auto-regression models and some existing models, respectively. The result indicates that the smaller left-right spread of triangular fuzzy number provides the better forecast values if compared with based line models.
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Image Classification for Snake Species Using Machine Learning Techniquesd whenever a snake image is given as input. Our experiment shows that backpropagation neural network and nearest neighbour are highly accurate with greater than 87 % accuracy on CEDD descriptor in this problem.
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