One of the hardest problems in reasoning about a physical system is finding an approximate model that is mathematically tractable and yet captures the essence of the problem. Appr...
In this paper, a novel learning algorithm for Hidden Markov Models (HMMs) has been devised. The key issue is the achievement of a sparse model, i.e., a model in which all irreleva...
This paper presents a new LP (Linear Programming) model to solve a tactical wood procurement and harvesting problem. This optimization problem occurs in several wood supply chains...
Turing complete Genetic Programming (GP) models introduce the concept of internal state, and therefore have the capacity for identifying interesting temporal properties. Surprisin...
Xiao Luo, Malcolm I. Heywood, A. Nur Zincir-Heywoo...
A second-order hierarchical uncertainty model of a system of independent random variables is studied in the paper. It is shown that the complex nonlinear optimization problem for ...