In this project area, mathematical modeling, classical and heuristic optimization on binary or non-binary computers, together with methods of pre distortion, modulation, equalization and decoding is used.
In connection with astronomy
The method is based on measuring the flow of light from the parent star during transit, which is detected by the transit depth of about 2% compared to the light from the contours of the exo-planet. Either by using photometry or spectrometry
Factors that affect the observation of planets are exo-atmospheric absorption, the optical depth and climatic factors.
This project is exploring the use of adaptive equalizers to cancel the atmospheric effect on the observation of Exo-planet Transit. By using data from the star GJ 1214 (with transit exoplanet GJ 1214b) and a reference star with 65 observations every 185 seg. And the Mandel & Agol model that relates the radii and the center distance between the parent star and the exo-planet has managed to suppress the atmosphere.
In regarding with Mining
This project proposes the use of two Heuristic methods such as neural networks and genetic algorithms for control of a bank Rougher flotation.
Using a model previously generated by a team member, it has been proposed and chosen the foam height as a control variable, comparing both techniques.
To improve the performance of neural networks have started using mathematical programming methods, because expanding the search space, since they are the optimal combination of foam thicknesses distributed in the 5 banks to maximize recovery. Like other authors who have recently published, it has been confirmed that the last two banks do not have much relevance in the overall performance of the process, but with a smaller computation cost.
In this project we are working in a redundant system that blends LIDAR magnetometers in order to represent a geographical mapping of the mine and the position of the people, using the technique of Multi-objective denominated SLAM.