9 citations · 30 across the 6 of their papers we have counts for
7 papers
Rethinking Neural Width for Alternating Current Optimal Power Flow Proxies
Dhruvi Khandelwal, Anurag Basistha, Ayushi Jolotia +1
Deep learning proxies for Alternating Current Optimal Power Flow (ACOPF) lack systematic methods for determining architectural size. This paper conducts a constructive thought expe…
Toolbox for Discovering Dynamic System Relations via TAG Guided Genetic Programming
Stefan-Cristian Nechita, Roland Toth, Dhruv Khandelwal +1
Data-driven modeling of nonlinear dynamical systems often require an expert user to take critical decisions a priori to the identification procedure. Recently an automated strategy…
A Tree Adjoining Grammar Representation for Models Of Stochastic Dynamical Systems
Dhruv Khandelwal, Maarten Schoukens, Roland Tóth
Model structure and complexity selection remains a challenging problem in system identification, especially for parametric non-linear models. Many Evolutionary Algorithm (EA) based…
Data-driven Modelling of Dynamical Systems Using Tree Adjoining Grammar and Genetic Programming
Dhruv Khandelwal, Maarten Schoukens, Roland Tóth
State-of-the-art methods for data-driven modelling of non-linear dynamical systems typically involve interactions with an expert user. In order to partially automate the process of…
Grammar-based Representation and Identification of Dynamical Systems
Dhruv Khandelwal, Maarten Schoukens, Roland Tóth
In this paper we propose a novel approach to identify dynamical systems. The method estimates the model structure and the parameters of the model simultaneously, automating the cri…
On the Simulation of Polynomial NARMAX Models
Dhruv Khandelwal, Maarten Schoukens, Roland Tóth
In this paper, we show that the common approach for simulation non-linear stochastic models, commonly used in system identification, via setting the noise contributions to zero res…
Robust Fault Diagnosis by Optimal Input Design for Self-sensing Systems
Dhruv Khandelwal, Siep Weiland, Amol Khalate
This paper presents a methodology for model based robust fault diagnosis and a methodology for input design to obtain optimal diagnosis of faults. The proposed algorithm is suitabl…