no code implementations • 27 Aug 2019 • Varun Ojha, Ajith Abraham, Vaclav Snasel
This paper provides an in-depth review of the optimal design of type-1 and type-2 fuzzy inference systems (FIS) using five well known computational frameworks: genetic-fuzzy systems (GFS), neuro-fuzzy systems (NFS), hierarchical fuzzy systems (HFS), evolving fuzzy systems (EFS), and multi-objective fuzzy systems (MFS), which is in view that some of them are linked to each other.
no code implementations • 6 Jul 2017 • Varun Kumar Ojha, Ajith Abraham, Vaclav Snasel
Optimization of neural network (NN) significantly influenced by the transfer function used in its active nodes.
no code implementations • 6 Jul 2017 • Varun Kumar Ojha, Ajith Abraham, Vaclav Snasel
A comprehensive performance analysis of the underlying parameters such as: selection strategy, distance measure metric and pheromone evaporation rate of the ACO suggests that the Roulette Wheel Selection strategy enhances the performance of the ACO due to its ability to provide non-uniformity and adequate diversity in the selection of a solution.
1 code implementation • 16 May 2017 • Varun Kumar Ojha, Vaclav Snasel, Ajith Abraham
Hence, the proposed HFIT is an efficient and competitive alternative to the other FISs for function approximation and feature selection.