MOSCH: A Multi-Objective Spatial Clustering Algorithm with Constraint-Handling Methods

by Bridget Baksa
Artificial Intelligence and Machine Learning have become the focal point of technological research within the past decade. Extensive research, code development, and testing has led to the production of a machine learning algorithm that handles multiple objective and constraint functions in spatial clustering. The MOSCH algorithm produces a range of clustering solutions that meet both objective and constraint goals and has been tested on both artificial data sets and real-life data sets.
Major: 
IST
Exhibition Category: 
Engineering
Exhibition Format: 
Poster Presentation
Campus: 
Berks
Faculty Sponsor: 
Abdullah Konak
Location: 
Alumni Hall, HUB-Robeson Center
Poster Number: 
106