In this paper, we consider First-order fuzzy differential equations with initial value conditions. The convergence, consistency and stability of difference method for approximating the solution of fuzzy differential equations involving generalized H-differentiability, are studied. Then the local truncation error is defined and sufficient conditions for convergence, consistency and stability of ...

In this paper, we have proposed a SIR fuzzy epidemic model by taking the transmission rate and recovery as numbers. The basic reproduction number been computed. Further considering initial values for susceptible, infected recovered population numerical simulation has carried out using Runge-Kutta method. We can predict of virus prevent COVID-19 outbreak in India with results obtained from model.

We present a novel fuzzy clustering technique called CRUDAW that allows a data miner to assign weights on the attributes of a data set based on their importance (to the data miner) for clustering. The technique uses a novel approach to select initial seeds deterministically (not randomly) using the density of the records of a data set. CRUDAW also selects the initial fuzzy membership degrees de...

Two fuzzy database query languages are proposed. They are used to query to fuzzy databases that are enhanced from relational databases in a way that fuzzy sets are allowed in both attribute values and truth values. A fuzzy calculus query language is constructed based on the relational calculus and a fuzzy algebra query language is also constructed based on the relational algebra. In addition, t...

Conventional Association Rule Mining (ARM) algorithms usually deal with datasets with categorical values and expect any numerical values to be converted to categorical ones using ranges (Age = 25 to 60). Fuzzy logic is used to convert quantitative values of attributes to categorical ones so as to eliminate any loss of information arising due to sharp partitioning (using ranges) and then generat...

At the conceptual stage of design, designers only have vague ideas of initial shapes which they gradually refine. These imprecise shapes may be specified by a set of fuzzy shape descriptors which represent the intent of a designer. It is also desirable to be able to save them in a database for future reference or for use as initial shapes for new designs. Most research on fuzzy databases has be...

In this paper, we propose a genetic-algorithm-based fuzzy-knowledge integration framework that can simultaneously integrate multiple fuzzy rule sets and their membership function sets. The proposed approach consists of two phases: fuzzy knowledge encoding and fuzzy knowledge integration. In the encoding phase, each fuzzy rule set with its associated membership functions is first transformed int...