Learning in neural networks can broadly be divided into two categories, viz., off-line (or
batch) learning and online (or incremental) learning. In this paper, a review of a variety of …

This paper proposes an interval type-2 fuzzy-neural network with support-vector regression
(IT2FNN-SVR) for noisy regression problems. The antecedent part in each fuzzy rule of an …

In this work a new radial basis function based classification neural network named as
generalized classifier neural network, is proposed. The proposed generalized classifier …

This paper presents a hybrid evolutionary algorithm (EA) to solve nonlinear-regression
problems. Although EAs have proven their ability to explore large search spaces, they are …

This paper presents an approach to prediction based on a new interval type-2 Atanassov-
intuitionistic fuzzy logic system (IT2AIFLS) of the Takagi-Sugeno-Kang fuzzy inference with …

The two-spiral task is a well-known benchmark for binary classification. The data consist of
points on two intertwined spirals which cannot be linearly separated. This article reviews …

To control the molten steel temperature in a Ladle Furnace accurately, it is necessary to
build a precise (ie accurate and good generalized) temperature prediction model. To solve …

This paper proposes a new nonparametric regression method, based on the combination of
generalized regression neural networks (GRNNs), density-dependent multiple kernel …

In this paper, a novel impatience-determined model was proposed for qualitative and
quantitative characterization of the impatience level during evacuation. We firstly developed …

Most of the existing Artificial Intelligence (AI) models for data regression commonly assume
that the data samples are completely clean without noise or worst yet, only the symmetrical …