We have experience preparing input data for any type of data analysis and visualization.
Our team is highly experienced in building and applying heuristic algorithms for function optimizations and multi-dimensional domain search.
We are able to tailor custom search algorithms for both mono and multi-modal functions to find the global optima and avoid premature convergence. We have successfully introduced clustering algorithms for local minima isolation and local evolution in order to ensure behavior consistency. Our work includes genetic algorithms, particle swarm, threshold acceptance, simulated annealing and memetic algorithms.
We can understand, implement, and customize even the most complex neural network architectures in order best match problem requirements.