8 citations · 8 across the 2 of their papers we have counts for
9 papers
Quantifying the Classification of Exoplanets: in Search for the Right Habitability Metric
Margarita Safonova, Archana Mathur, Suryoday Basak +2
What is habitability? Can we quantify it? What do we mean under the term habitable or potentially habitable planet? With estimates of the number of planets in our Galaxy alone runn…
SBAF: A New Activation Function for Artificial Neural Net based Habitability Classification
Snehanshu Saha, Archana Mathur, Kakoli Bora +2
We explore the efficacy of using a novel activation function in Artificial Neural Networks (ANN) in characterizing exoplanets into different classes. We call this Saha-Bora Activat…
Habitability Classification of Exoplanets: A Machine Learning Insight
Suryoday Basak, Surbhi Agrawal, Snehanshu Saha +4
We explore the efficacy of machine learning (ML) in characterizing exoplanets into different classes. The source of the data used in this work is University of Puerto Rico's Planet…
Time Reversed Delay Differential Equation Based Modeling Of Journal Influence In An Emerging Area
Poulami Sarkar, Snehanshu Saha, Archana Mathur +4
A recent independent study resulted in a ranking system which ranked Astronomy and Computing (ASCOM) much higher than most of the older journals highlighting its niche prominence.…
A Comparative Analysis of the Cobb-Douglas Habitability Score (CDHS) with the Earth Similarity Index (ESI)
Surbhi Agrawal, Suryoday Basak, Snehanshu Saha +2
We present an analytical comparison of the Cobb-Douglas Habitability Production Function (CD-HPF) and the Earth Similarity Index (ESI). The key differences between the ESI and CD-H…
Machine Learning in Astronomy: A Case Study in Quasar-Star Classification
Mohammed Viquar, Suryoday Basak, Ariruna Dasgupta +2
We present the results of various automated classification methods, based on machine learning (ML), of objects from data releases 6 and 7 (DR6 and DR7) of the Sloan Digital Sky Sur…