Estimation of surface parameters from a 30 metre micro-meteorological tower over a deep moist convective region

The estimation of u*, 0*, q*. and Obukov-length In the surface layer from micro-meteorological tower data still poses an important challange. In the present study a procedure for the parametric estimation has been developed which is consistent both with the similarity relation and the profile relation. The study has been done using both fast response and slow response tower data. Since similarity relations involve a particular level z. so inspite of starting from a layer, the parameters should be attributed to a relations involve a particular level only, It has been suggested that the convenient level is geometric mean height of the layer. The ratio of eddy diffusivities (KhKm.) has been estimated both for stable and unstable situation and this ratio is presented by a single expression which incidentally yields a new value of a constant involved.

Grading Similarity

There are numerous words across languages expressing similarity or indistinguishability. In this paper, three types of similarity expressions in German and English are compared—ähnlich/similar, so/such, and gleich/same. They differ in a number of respects, one of them being gradability: While ähnlich/similar are gradable, so/such as well as gleich/same are not. The analysis in this paper starts from the analysis of German so as a demonstrative expressing similarity (instead of identity) to its demonstration target (Umbach and Gust 2014). It is suggested that the meaning of the three types of similarity expressions is based on a common similarity relation, while differences in meaning are provided by constraints referring to the selection of dimensions of comparison and preconditions of usage. The focus of the paper is on gradability and on the question of what it means for a pair of items to be more similar than another pair. An analysis in the spirit of Klein (1980) is presented accounting for the fact that ähnlich/similar are gradable while neither so/such nor gleich/same are. The formal framework makes use of representations based on attribute spaces and classifiers, where representations may be of different granularity.

Generalized dynamic attribute reduction based on similarity relation of intuitionistic fuzzy rough set

In view of the characteristics with big data, high feature dimension, and dynamic for a large-scale intuitionistic fuzzy information systems, this paper integrates intuitionistic fuzzy rough sets and generalized dynamic sampling theory, proposes a generalized attribute reduction algorithm based on similarity relation of intuitionistic fuzzy rough sets and dynamic reduction. It uses dynamic reduction sampling theory to divide a big data set into small data sets and relative positive domain cardinality instead of dependency degree as decision-making condition, and obtains reduction attributes of big intuitionistic fuzzy decision information systems, and achieves the goal of extracting key features and fault diagnosis. The innovation of this paper is that it integrates generalized dynamic reduction and intuitionistic fuzzy rough set, and solves the problem of big data set which cannot be solved by intuitionistic fuzzy rough set. Taking an actual data as an example, the scientificity, rationality and effectiveness of the algorithm are verified from the aspects of stability, diagnostic accuracy, optimization ability and time complexity. Compared with similar algorithms, the advantages of the proposed algorithm for big data processing are confirmed.

Use of Some Topological Concepts in the Study of Some COVID−19 Symptoms

We apply some topological concepts on topological spaces generated from both equality and similarity relation for our information system, which examine 10 hypothetical patients who suffer from some COVID−19 symptoms. This is based on the degree of accuracy generated from the cardinality of the lower and upper approximation. This method is clarified by application.

Orderings on Generalized Regular Interval Valued Fuzzy Matrices

In this paper, a special type of ordering for k - regular Interval Valued Fuzzy Matrix (IVFM) is introduced as a generalization of the minus partial ordering for regular fuzzy matrices. A set of equivalent conditions for a pair of k – regular IVFM to be under this ordering are obtained. We exhibit that this ordering is preserved under similarity relation.

Evaluation of the quality and relevance of a fuzzy partition

This paper proposes a couple of criteria for evaluating the quality and relevance of a fuzzy partition. These criteria are established from a fuzzy classification system and its recursive De Morgan triplet. We propose a comparison process between the classes of a fuzzy partition, based on a translation invariant similarity relation. Therefore a classification process is carried out with the equivalence relations determined by the similarity relation. Such a relation is built on the commutative group structure formed by the elements of the fuzzy classification system. Our approach is illustrated through an example on image analysis by the fuzzy c-means algorithm.