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Object-parameter approaches to predicting unknown data in an incomplete fuzzy soft set

Liu Y., Qin K., Rao C., Alhaji Mahamadu M.

International Journal of Applied Mathematics and Computer Science

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2017

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Vol. 27, no. 1

157--167

EN

The research on incomplete fuzzy soft sets is an integral part of the research on fuzzy soft sets and has been initiated recently. In this work, we first point out that an existing approach to predicting unknown data in an incomplete fuzzy soft set suffers from some limitations and then we propose an improved method. The hidden information between both objects and parameters revealed in our approach is more comprehensive. Furthermore, based on the similarity measures of fuzzy sets, a new adjustable object-parameter approach is proposed to predict unknown data in incomplete fuzzy soft sets. Data predicting converts an incomplete fuzzy soft set into a complete one, which makes the fuzzy soft set applicable not only to decision making but also to other areas. The compared results elaborated through rate exchange data sets illustrate that both our improved approach and the new adjustable object-parameter one outperform the existing method with respect to forecasting accuracy.

2

Rough Approximations Based on Valued Tolerance Relations

Qin K., Luo J., Pei Z.

Fundamenta Informaticae

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2015

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Vol. 142, nr 1-4

183--194

EN

Rough set approach for knowledge discovery in incomplete information systems has been extensively studied. This paper conduct a further study of valued tolerance relation based rough approximations. We make an analysis of the existing rough approximabilities and propose a new approach for lower (upper) approximability, which is a generalization of Pawlak approximation operators for complete information system. The approach has also been generalized to fuzzy cases. Some basic properties of the approximation operators are examined.

3

Analysis of Fructus Arctii from Different Regions of China by HPLC Coupled with Chemometrics Methods

Liu Q., Qin K., Shen B., Cai H., Cai B.

Acta Chromatographica

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2015

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Vol. 27, no. 4

697--709

EN

To evaluate the quality of Fructus Arctii, an accurate and reliable method of high-performance liquid chromatography/diode array detection—electrospray ionization—mass spectrometry (HPLC/DAD—ESI—MS) was developed. Nine compounds, including chlorogenic acid, caffeic acid, trans-p-hydroxycinnamic acid, arctiin, arctignan A, ethyl caffeate, matairesinol, arctigenin, and lappaol B, were determined simultaneously in 19 batches of Fructus Arctii samples collected from different localities. Nineteen common peaks were identified or tentatively assigned by comparing their mass spectrometric data with reference compounds, self-established compound library, and published literatures. Also, the 19 common peaks were selected as characteristic peaks to assess the similarity of chromatographic fingerprinting of these samples. Moreover, hierarchical clustering analysis (HCA) and principal components analysis (PCA) were successfully applied to demonstrate the variability of samples. The results indicated the content of nine compounds that varied greatly among the samples, and 19 samples collected from different localities could be discriminated. Furthermore, chlorogenic acid, arctiin, and arctigenin were found to be chemical markers for evaluating the quality of Fructus Arctii.

4

High-efficiency carrier frequency estimation algorithm for real-time multi-domain communication signal analysis

Wang Q., Yang X., Yan X, Qin K.

Metrology and Measurement Systems

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2014

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Vol. 21, nr 2

281--292

EN

Based on real-time multi-domain communication signal analysis architecture, a high-efficiency blind carrier frequency estimation algorithm using the power spectrum symmetry of the measured modulated signal is presented. The proposed algorithm, which utilizes the moving averaged power spectrum achieved by the realtime spectrum analysis, iteratively identifies the carrier frequency in according to the power difference between the upper sideband and lower sideband, which is defined and revised by the estimated carrier frequency in each iteration. When the power difference of the two sidebands converges to the preset threshold, the carrier frequency can be obtained. For the modulation analysis, the measured signal can be coarsely compensated by the estimated result, and the residual carrier frequency error is eliminated by a following carrier synchronization loop. Compared with previous works, owing to the moving averaged power spectrum normalization and the smart iterative step variation mechanism for the two sidebands definition, the carrier frequency estimation accuracy and speed can be significantly improved without increasing the computational effort. Experimental results are included to demonstrate the outstanding performance of the proposed algorithm.

5

Approximation Operators, Binary Relation and Basis Algebra in L-fuzzy Rough Sets

Wu Z., Li T., Qin K., Ruan D.

Fundamenta Informaticae

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2011

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Vol. 111, nr 1

47-63

EN

Approximation operators play a vital role in rough set theory. Their three elements, namely, binary relation in the universe, basis algebra and properties, are fundamental in the study of approximation operators. In this paper, the interrelations among the three elements of approximation operators in L-fuzzy rough sets are discussed under the constructive approach, the axiomatic approach and the basis algebra choosing approach respectively. In the constructive approach, the properties of the approximation operators depend on the basis algebra and the binary relation. In the axiomatic approach, the induced binary relation is influenced by the axiom set and the basis algebra. In the basis algebra choosing approach, the basis algebra is constructed by properties of approximation operators and specific binary relations.