Authors:
Filipe Cruz
;
António Coelho
and
Luis Paulo Reis
Affiliation:
Faculdade de Engenharia da Universidade do Porto, Portugal
Keyword(s):
Metaheuristics, optimization algorithms, optimization systems, expeditious modelling.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Biomedical Engineering
;
Computational Intelligence
;
Enterprise Information Systems
;
Evolutionary Computing
;
Expert Systems
;
Genetic Algorithms
;
Health Information Systems
;
Hybrid Learning Systems
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Knowledge-Based Systems Applications
;
Optimization Algorithms
;
Soft Computing
;
Symbolic Systems
Abstract:
Expeditious modelling of virtual urban environments consists of generating realistic 3d models from limited information. It has several practical applications but typically suffers from a lack of accuracy in the parameter values that feed the modeller. By gathering small amounts of information about certain key urban areas, it becomes possible to feed a system that automatically compares and adjusts the input parameter values to find optimal solutions of parameter combinations that resemble the real life model. These correctly parameterized rules can then be reapplied to generate virtual models of real areas with similar characteristics to the referenced area. Based on several nature inspired metaheuristic algorithms such as genetic algorithms, simulated annealing and harmony search, this paper presents a new hybrid metaheuristic algorithm capable of optimizing functions with both discrete and continuous parameters and offer competitive results in a highly neglected field of applicat
ion.
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