Fractal-based belief entropyQianli Zhou aYong Deng a b c d
In Wei et al. [12], a feature selection model was proposed based on the maximum mutual information and entropy of features to select appropriate features. The proposed model uses a hybrid method based on dynamic feature importance, which evaluates the relevance of each feature in the context of...
Ramadas et al. [5] put forward a variant of the differential evolution (DE) algorithm combining with a multilevel threshold of Kapur entropy to segment MRI and extract regions of the tumor. Kumar et al. [6] designed a multi-level image segmentation method because of Renyi entropy, combining...
fractal-based complex belief (FCB) entropyuncertainty measurementComplex evidence theory (CET), an extension of the traditional D-S evidence theory, has garnered academic interest for its capacity to articulate uncertainty through complex basic belief assignment (CBBA) and to perform uncertainty ...
We model intuitionistic fuzzy sets (IFS) by Dempster-Shafer theory (DST), and use fractal-based belief (FB) entropy to propose a new intuitionistic fuzzy measure. Combining the Shannon entropy measure of fuzzy sets (FS) and the proposed IFS measure, we explore the fractal features of FS and...
Connectivity patterns between nodes represent strength of compatibility (relevance) between the corresponding nodes and also reflect the difference in entropy of the node structures. information elements propagating in the network are belief functions with fractal dimension of uncertainty. They are processed...