6 papers
Integrating Neurosymbolic AI in Advanced Air Mobility: A Comprehensive Survey
Kamal Acharya, Iman Sharifi, Mehul Lad +2
Neurosymbolic AI combines neural network adaptability with symbolic reasoning, promising an approach to address the complex regulatory, operational, and safety challenges in Advanc…
A Data-Driven Approach to Enhancing Gravity Models for Trip Demand Prediction
Kamal Acharya, Mehul Lad, Liang Sun +1
Accurate prediction of trips between zones is critical for transportation planning, as it supports resource allocation and infrastructure development across various modes of transp…
Decoding Android Malware with a Fraction of Features: An Attention-Enhanced MLP-SVM Approach
Safayat Bin Hakim, Muhammad Adil, Kamal Acharya +1
The escalating sophistication of Android malware poses significant challenges to traditional detection methods, necessitating innovative approaches that can efficiently identify an…
Neurosymbolic AI for Travel Demand Prediction: Integrating Decision Tree Rules into Neural Networks
Kamal Acharya, Mehul Lad, Liang Sun +1
Travel demand prediction is crucial for optimizing transportation planning, resource allocation, and infrastructure development, ensuring efficient mobility and economic sustainabi…
Regional Air Mobility Flight Demand Modeling in Tennessee State
Kamal Acharya, Mehul Lad, Houbing Song +1
Advanced Air Mobility (AAM), encompassing Urban Air Mobility (UAM) and Regional Air Mobility (RAM), offers innovative solutions to mitigate the issues related to ground transportat…
Demand Modeling for Advanced Air Mobility
Kamal Acharya, Mehul Lad, Liang Sun +1
In recent years, the rapid pace of urbanization has posed profound challenges globally, exacerbating environmental concerns and escalating traffic congestion in metropolitan areas.…