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Articles 1 - 4 of 4
Full-Text Articles in Computer Engineering
Fitness Biasing For The Box Pushing Task, Gary Parker, Jim O'Connor
Fitness Biasing For The Box Pushing Task, Gary Parker, Jim O'Connor
Computer Science Faculty Publications
Anytime Learning with Fitness Biasing has been shown in previous works to be an effective tool for evolving hexapod gaits. In this paper, we present the use of Anytime Learning with Fitness Biasing to evolve the controller for a robot learning the box pushing task. The robot that was built for this task, was measured to create an accurate model. The model was used in simulation to test the effectiveness of Anytime Learning with Fitness Biasing for the box pushing task. This work is the first step in new research where an automated system to test the viability of Fitness …
Scalable Co-Evolution Of Soft Robot Properties And Gaits, Davis K. Knox
Scalable Co-Evolution Of Soft Robot Properties And Gaits, Davis K. Knox
Honors Theses
The field of soft robotics is very promising; applications in-clude urban search and rescue and covert surveillance, but these projects are not yet realized, partly because of the difficulties in soft robot shape and locomotion design. Be-cause of this, traditional design methods do not prove to be effective. This project attempts to come up with solu-tions to this soft robot design problem; utilizing a genetic algorithm, a computer simulation of Darwin’s “Survival of the Fittest,” this project attempts to make soft bodies move. This genetic algorithm evaluates each solution in simulation, and assigns each one a fitness based on distance …
Using Learning Automata For Multi-Objective Generation Dispatch Considering Cost, Voltage Stability And Power Losses, Ari̇f Karakaş, Celal Kocatepe, Fangxing Li
Using Learning Automata For Multi-Objective Generation Dispatch Considering Cost, Voltage Stability And Power Losses, Ari̇f Karakaş, Celal Kocatepe, Fangxing Li
Turkish Journal of Electrical Engineering and Computer Sciences
The economical and secure operation of power systems has significant importance. Due to technical limitations, the best economical operation point is not always the desired operating point for system stability or power losses. In this study, first, the most economical operating point is obtained by solving the non-linear, network-constrained economic dispatch problem using a genetic algorithm. Then, the system voltage stability is analyzed to compare the different possible operating points using V-Q sensitivity analysis. The power losses, obtained for various operating points, are considered the third objective function. Finally, these 3 aspects of cost, voltage stability, and power losses are …
Change Detection Without Difference Image Computation Based On Multiobjective Cost Function Optimization, Turgay Çeli̇k, Zeki̇ Yetgi̇n
Change Detection Without Difference Image Computation Based On Multiobjective Cost Function Optimization, Turgay Çeli̇k, Zeki̇ Yetgi̇n
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we propose a novel method for unsupervised change detection in multi-temporal satellite images by using multiobjective cost function optimization via genetic algorithm (GA). The spatial image grid of the input multi-temporal satellite images is divided into two distinct regions, representing ``changed'' and ``unchanged'' regions between input images, via the intermediate change detection mask produced by the GA. The dissimilarity of pixels of ``changed'' regions and similarity of pixels of ``unchanged'' regions between input multi-temporal images are measured using image quality metrics which consider correlation, spectral distortion, radiometric distortion, and contrast distortion. The contextual information of each pixel …