48 citations · 119 across the 9 of their papers we have counts for
10 papers
Equipment Health Assessment: Time Series Analysis for Wind Turbine Performance
Jana Backhus, Aniruddha Rajendra Rao, Chandrasekar Venkatraman +3
In this study, we leverage SCADA data from diverse wind turbines to predict power output, employing advanced time series methods, specifically Functional Neural Networks (FNN) and…
Predictive Analysis for Optimizing Port Operations
Aniruddha Rajendra Rao, Haiyan Wang, Chetan Gupta
Maritime transport is a pivotal logistics mode for the long-distance and bulk transportation of goods. However, the intricate planning involved in this mode is often hindered by un…
Optimal Load Shedding for Public Safety Power Shutoffs
Aniruddha Rajendra Rao, Chandrasekar Venkatraman, Robert Ellis +1
Public utilities are faced with situations where high winds can bring trees and debris into contact with energized power lines and other equipments, which could ignite wildfires. A…
An ensemble of convolution-based methods for fault detection using vibration signals
Xian Yeow Lee, Aman Kumar, Lasitha Vidyaratne +3
This paper focuses on solving a fault detection problem using multivariate time series of vibration signals collected from planetary gearboxes in a test rig. Various traditional ma…
A Functional approach for Two Way Dimension Reduction in Time Series
Aniruddha Rajendra Rao, Haiyan Wang, Chetan Gupta
The rise in data has led to the need for dimension reduction techniques, especially in the area of non-scalar variables, including time series, natural language processing, and com…
Modern Non-Linear Function-on-Function Regression
Aniruddha Rajendra Rao, Matthew Reimherr
We introduce a new class of non-linear function-on-function regression models for functional data using neural networks. We propose a framework using a hidden layer consisting of c…
Non-linear Functional Modeling using Neural Networks
Aniruddha Rajendra Rao, Matthew Reimherr
We introduce a new class of non-linear models for functional data based on neural networks. Deep learning has been very successful in non-linear modeling, but there has been little…
Modern Multiple Imputation with Functional Data
Aniruddha Rajendra Rao, Matthew Reimherr
This work considers the problem of fitting functional models with sparsely and irregularly sampled functional data. It overcomes the limitations of the state-of-the-art methods, wh…
A Non-linear Function-on-Function Model for Regression with Time Series Data
Qiyao Wang, Haiyan Wang, Chetan Gupta +2
In the last few decades, building regression models for non-scalar variables, including time series, text, image, and video, has attracted increasing interests of researchers from…
Spatio-Temporal Functional Neural Networks
Aniruddha Rajendra Rao, Qiyao Wang, Haiyan Wang +2
Explosive growth in spatio-temporal data and its wide range of applications have attracted increasing interests of researchers in the statistical and machine learning fields. The s…