Nonlinear model predictive control (MPC) of a simulated chaotic cutting process is presented. The nonlinear MPC combines a neural-network model and a genetic-algorithm-based optim...
Selecting an optimum maintenance policy independent of other parameters of the production system does not always yield the overall optimum operating conditions. For instance, high...
Abstract. Machine learning can be utilized to build models that predict the runtime of search algorithms for hard combinatorial problems. Such empirical hardness models have previo...
Frank Hutter, Youssef Hamadi, Holger H. Hoos, Kevi...
In this paper, we develop a probabilistic model for estimation of the numbers of cache misses during the sparse matrix-vector multiplication (for both general and symmetric matrice...
RENO is a modified MIPS R10000 register renamer that uses map-table “short-circuiting” to implement dynamic versions of several well-known static optimizations: move eliminat...