no code implementations • 24 Nov 2023 • Faizal Hafiz, Jan Broekaert, Akshya Swain
This note focuses on the optimization of neural architectures for stock index movement forecasting following a major market disruption or crisis.
no code implementations • 23 Nov 2023 • Faizal Hafiz, Jan Broekaert, Davide La Torre, Akshya Swain
In a multi objective setting, a portfolio manager's highly consequential decisions can benefit from assessing alternative forecasting models of stock index movement.
no code implementations • 15 Nov 2021 • Faizal Hafiz, Jan Broekaert, Davide La Torre, Akshya Swain
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 inputs.
no code implementations • 27 Sep 2021 • 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.
no code implementations • 20 Jan 2020 • Renoh Johnson Chalakkal, Faizal Hafiz, Waleed Abdulla, Akshya Swain
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, i. e., exudate segmentation and imbalanced datasets.
no code implementations • 10 Sep 2019 • Faizal Hafiz, Akshya Swain, Eduardo M. A. M. Mendes, Luis Aguirre
In essence, the proposed approach casts grey-box identification problem into a multi-objective framework to balance bias-variance dilemma of model building while explicitly integrating a priori knowledge into the structure selection process.
no code implementations • 17 Aug 2019 • 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.
no code implementations • 15 Apr 2019 • Faizal Hafiz, Akshya Swain, Chirag Naik, Nitish Patel
A novel two-dimensional (2D) learning framework has been proposed to address the feature selection problem in Power Quality (PQ) events.
no code implementations • 3 Aug 2018 • Faizal Hafiz, Akshya Swain, Nitish Patel, Chirag Naik
This paper proposes a new generalized two dimensional learning approach for particle swarm based feature selection.