Search Results for "high"

Dlib is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.

* Fast GPU linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use * Provides high-level syntax and functionality deliberately similar to Matlab * Provides an API that is aiming to be compatible with Armadillo for easy transition between CPU and GPU linear algebra code * Useful for algorithm development directly in C++, or quick conversion of research code into production environments * Distributed under the permissive Apache 2.0 license, useful for both open-source and proprietary (closed-source) software * Can be used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc * Downloads: http://coot.sourceforge.io/download.html * Documentation: http://coot.sourceforge.io/docs.html * Bug reports: http://coot.sourceforge.io/faq.html * Git repo: https://gitlab.com/conradsnicta/bandicoot-code

Classical genetic algorithm suffers heavy pressure of fitness evaluation for time-consuming optimization problems. To address this problem, we present an efficient genetic algorithm by the combination with clustering methods. The high efficiency of the proposed method results from the fitness estimation and the schema discovery of partial individuals in current population and. Specifically, the clustering method used in this paper is affinity propagation. The numerical experiments demonstrate that the proposed method performs promisingly for well-known benchmark problems in the term of optimization accuracy.