In this paper, we integrate type-2 (T2) fuzzy sets with Markov random fields (MRFs) referred to as T2 FMRFs, which may handle both fuzziness and randomness in the structural patter...
Consider the problem of joint parameter estimation and prediction in a Markov random field: i.e., the model parameters are estimated on the basis of an initial set of data, and th...
In this paper, a recurrent neural network based fuzzy inference system (RNFIS) for prediction is proposed. A recurrent network is embedded in the RNFIS by adding feedback connecti...
In this article, we propose a random walk-based model to predict legislators’ votes on a set of bills. In particular, we first convert roll call data, i.e. the recorded votes a...
Abstract. In this paper, a new fuzzy logic-based approach to production scheduling in the presence of uncertain disruptions is presented. The approach is applied to a real-life pro...