13 research outputs found
Particle Swarm Optimization and Uncertainty Assessment in Inverse Problems
Most inverse problems in the industry (and particularly in geophysical exploration) are highly underdetermined because the number of model parameters too high to achieve accurate data predictions and because the sampling of the data space is scarce and incomplete; it is always affected by different kinds of noise. Additionally, the physics of the forward problem is a simplification of the reality. All these facts result in that the inverse problem solution is not unique; that is, there are different inverse solutions (called equivalent), compatible with the prior information that fits the observed data within similar error bounds. In the case of nonlinear inverse problems, these equivalent models are located in disconnected flat curvilinear valleys of the cost-function topography. The uncertainty analysis consists of obtaining a representation of this complex topography via different sampling methodologies. In this paper, we focus on the use of a particle swarm optimization (PSO) algorithm to sample the region of equivalence in nonlinear inverse problems. Although this methodology has a general purpose, we show its application for the uncertainty assessment of the solution of a geophysical problem concerning gravity inversion in sedimentary basins, showing that it is possible to efficiently perform this task in a sampling-while-optimizing mode. Particularly, we explain how to use and analyze the geophysical models sampled by exploratory PSO family members to infer different descriptors of nonlinear uncertainty
Protein tertiary structure prediction via SVD and PSO sampling
International Work-Conference, Bioinformatics and Biomedical Engineering, IWBBIO 2018 (6th, 2018, Granada, Spain
Predicting protein tertiary structure and its uncertainty analysis via particle swarm sampling
On the use of principal component analysis and particle swarm optimization in protein tertiary structure prediction
International Conference, Artificial Intelligence and Soft Computing, ICAISC 2018 (17th, 2018, Zakopane, Poland
On the use of principal component analysis and particle swarm optimization in protein tertiary structure prediction
International Conference, Artificial Intelligence and Soft Computing, ICAISC 2018 (17th, 2018, Zakopane, Poland
Predicting protein tertiary structure and its uncertainty analysis via particle swarm sampling
Comparison of Different Sampling Algorithms for Phenotype Prediction
International Work-Conference, Bioinformatics and Biomedical Engineering, IWBBIO 2018 (6th, 2018, Granada, Spain
Sampling Defective Pathways in Phenotype Prediction Problems via the Fisher’s Ratio Sampler
International Work-Conference, Bioinformatics and Biomedical Engineering, IWBBIO 2018 (6th, 2018, Granada, Spain