In Fuzzy Formal Concept Analysis (FFCA), concept lattices are computed by scaling the problem and applying ordinary FCA algorithms. In this paper, the CbO family of algorithms is extended to work natively in the fuzzy setting, they are proved to be correct and output the whole set of formal concepts, which makes them mathematically equivalent to the scaling approach. However, experimental results demonstrate the performance improvement of these methods compared to scaling. The paper also discusses a new fuzzy strategy based on blacklisting redundant truth values to enhance the performance of algorithms by taking advantage of the structure of the residuated lattice.

This article delves into the process of fuzzifying time series, which entails converting a conventional time series into a time-indexed sequence of fuzzy numbers. The focus lies on the well-established practice of fuzzifying time series when a predefined degree of uncertainty is known, employing fuzzy numbers to quantify volatility or vagueness. To address practical challenges associated with volatility or vagueness quantification, we introduce the concept of informed time series. An algorithm is proposed to derive fuzzy time series, and findings include the examination of structural breaks within the realm of fuzzy time series. Additionally, this article underscores the significance of employing topological tools in the analysis of fuzzy time series, accentuating the role of these tools in extracting insights and unraveling intricate relationships within the data. • Introduces fuzzification of time series with informed time series. • Fuzzy time series captures uncertainty with fuzzy numbers. • Shows fuzzification can maintain stationarity despite structural breaks. • Dynamic time warping extended for fuzzy time series analysis. • Applications include stock market prediction and pattern recognition.

This paper explores weak Heyting algebras, an extension of complete Heyting algebras, focusing on characterizing this concept and identifying essential properties in terms of implication operators. The main emphasis is on unraveling the defining features and significance of the novel weak Heyting algebras. We further classify these structures within the context of a complete lattice and extend our findings to the Cartesian product. We facilitate comprehensive comparisons among these structures, by contributing to the broader understanding of weak Heyting algebras in mathematical research.

Our study is centered on the aggregation of fuzzy graphs, looking for conditions under which the aggregation process yields another fuzzy graph. We conduct an in-depth analysis of the preservation of several important properties and structures inherent to fuzzy graphs, like paths, cycles, or bridges. In addition we obtain appropriate criteria for when the aggregation of complete fuzzy graphs is again a complete fuzzy graph.