42 citations · 97 across the 11 of their papers we have counts for
11 papers
Coevolution of Neural Architectures and Features for Stock Market Forecasting: A Multi-objective Decision Perspective
Faizal Hafiz, Jan Broekaert, Davide La Torre +1
In a multi objective setting, a portfolio manager's highly consequential decisions can benefit from assessing alternative forecasting models of stock index movement. The present in…
A Multi-criteria Approach to Evolve Sparse Neural Architectures for Stock Market Forecasting
Faizal Hafiz, Jan Broekaert, Davide La Torre +1
This study proposes a new framework to evolve efficacious yet parsimonious neural architectures for the movement prediction of stock market indices using technical indicators as in…
N-shot Palm Vein Verification Using Siamese Networks
Felix Marattukalam, Waleed H. Abdulla, Akshya Swain
The use of deep learning methods to extract vascular biometric patterns from the palm surface has been of interest among researchers in recent years. In many biometric recognition…
An Efficient Framework for Automated Screening of Clinically Significant Macular Edema
Renoh Johnson Chalakkal, Faizal Hafiz, Waleed Abdulla +1
The present study proposes a new approach to automated screening of Clinically Significant Macular Edema (CSME) and addresses two major challenges associated with such screenings,…
Multi-objective Evolutionary Approach to Grey-Box Identification of Buck Converter
Faizal Hafiz, Akshya Swain, Eduardo M. A. M. Mendes +1
The present study proposes a simple grey-box identification approach to model a real DC-DC buck converter operating in continuous conduction mode. The problem associated with the i…
Multi-Objective Evolutionary Framework for Non-linear System Identification: A Comprehensive Investigation
Faizal Hafiz, Akshya Swain, Eduardo MAM Mendes
The present study proposes a multi-objective framework for structure selection of nonlinear systems which are represented by polynomial NARX models. This framework integrates the k…
Efficient Feature Selection of Power Quality Events using Two Dimensional (2D) Particle Swarms
Faizal Hafiz, Akshya Swain, Chirag Naik +1
A novel two-dimensional (2D) learning framework has been proposed to address the feature selection problem in Power Quality (PQ) events. Unlike the existing feature selection appro…
Orthogonal Floating Search Algorithms: From The Perspective of Nonlinear System Identification
Faizal Hafiz, Akshya Swain, Eduardo Mendes
The present study proposes a new Orthogonal Floating Search framework for structure selection of nonlinear systems by adapting the existing floating search algorithms for feature s…
Structure Selection of Polynomial NARX Models using Two Dimensional (2D) Particle Swarms
Faizal Hafiz, Akshya Swain, Eduardo MAM Mendes +1
The present study applies a novel two-dimensional learning framework (2D-UPSO) based on particle swarms for structure selection of polynomial nonlinear auto-regressive with exogeno…
Two-Dimensional (2D) Particle Swarms for Structure Selection of Nonlinear Systems
Faizal Hafiz, Akshya Swain, Eduardo MAM Mendes
The present study proposes a new structure selection approach for non-linear system identification based on Two-Dimensional particle swarms (2D-UPSO). The 2D learning framework ess…
A Two-Dimensional (2-D) Learning Framework for Particle Swarm based Feature Selection
Faizal Hafiz, Akshya Swain, Nitish Patel +1
This paper proposes a new generalized two dimensional learning approach for particle swarm based feature selection. The core idea of the proposed approach is to include the informa…