A great effort has been done during last years to improve range image segmentation results. The efficacy of the algorithms is affected by the parameters tuning. In this work two well-known search techniques have been applied to this task: genetic algorithms and simulated annealing. These techniques are adopted in cascade: the former to obtain a rough seed point set and the latter to have a more...

This paper covers the evaluation and fine-tuning of different values of genetic operator’s parameters in the process of optimizing the designs of the integrated circuits. We investigated the interdependence of various values of these parameters in the use over the set of test-bench circuits, as well as their influence on the quality of the final solution and the convergence speed. Due to the in...

fuzzy clustering methods are conveniently employed in constructing a fuzzy model of a system, but they need to tune some parameters. in this research, fcm is chosen for fuzzy clustering. parameters such as the number of clusters and the value of fuzzifier significantly influence the extent of generalization of the fuzzy model. these two parameters require tuning to reduce the overfitting in the...

Mustafa Baz, Brady Hunsaker Department of Industrial Engineering, University of Pittsburgh, 1048 Benedum Hall, Pittsburgh, PA 15261, USA, {[email protected], [email protected]} J. Paul Brooks Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, VA 23284, USA, [email protected] Abhijit Gosavi Department of Industrial & Systems Engineering, Unive...

This paper presents the Optimal Well-tempered Tuning system (OWT), a software application for computing optimal tuning systems in real-time. The optimal tuning systems are created from a framework, proposed by us, that formalizes historical and cross-cultural criteria. The parameters of the system are a fixed number of pitches, a repeat factor, an ideal tuning set, and weights for keys and inte...

Abstract A protocol based on Bayesian optimization is demonstrated for determining model parameters in a coarse-grained polymer simulation. This process takes as input the microscopic distribution functions and temperature-dependent density targeted system. The then iteratively considers simulations to sample space of parameters, aiming minimize discrepancy between new target. Successive sample...

Growing Neural Gas (GNG) algorithm is an unsupervised learning which belongs to the competitive family. Since then, GNG has been a subject vaious developments and implementations found in literatures for two main reasons: first, number of neurons (i.e., nodes) adaptive. Meaning, it periodically changed through adding new removing old accordingly order find best network captures topological stru...