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.
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 • 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 • 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 • 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 • 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 • 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 • 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.