most citedMetaheuristic Design of Feedforward Neural Networks: A Review of Two Decades of Research

604 citations

5 papers

cs.NE201712 cited

Predictive modeling of die filling of the pharmaceutical granules using the flexible neural tree

Varun Kumar Ojha, Serena Schiano, Chuan-Yu Wu +2

In this work, a computational intelligence (CI) technique named flexible neural tree (FNT) was developed to predict die filling performance of pharmaceutical granules and to identi…

cs.AI201718 cited

Multiobjective Programming for Type-2 Hierarchical Fuzzy Inference Trees

Varun Kumar Ojha, Vaclav Snasel, Ajith Abraham

This paper proposes a design of hierarchical fuzzy inference tree (HFIT). An HFIT produces an optimum treelike structure, i.e., a natural hierarchical structure that accommodates s…

cs.NE201726 cited

Ensemble of heterogeneous flexible neural trees using multiobjective genetic programming

Varun Kumar Ojha, Ajith Abraham, Václav Snášel

Machine learning algorithms are inherently multiobjective in nature, where approximation error minimization and model's complexity simplification are two conflicting objectives. We…

cs.NE2017604 cited

Metaheuristic Design of Feedforward Neural Networks: A Review of Two Decades of Research

Varun Kumar Ojha, Ajith Abraham, Václav Snášel

Over the past two decades, the feedforward neural network (FNN) optimization has been a key interest among the researchers and practitioners of multiple disciplines. The FNN optimi…

cs.DC201725 cited

CHAOS: A Parallelization Scheme for Training Convolutional Neural Networks on Intel Xeon Phi

Andre Viebke, Suejb Memeti, Sabri Pllana +1

Deep learning is an important component of big-data analytic tools and intelligent applications, such as, self-driving cars, computer vision, speech recognition, or precision medic…