This paper presents a novel and notable swarm approach to evolve an optimal set of weights and architecture of a neural network for classification in data mining. In a distributed ...
To save precious time and space, many games and simulations use static terrain and fixed (or random) reconstruction of areas that a player leaves and later revisits. This can resu...
This paper proposes and evaluates the k-greedy equivalence search algorithm (KES) for learning Bayesian networks (BNs) from complete data. The main characteristic of KES is that i...
The framework of this paper is the design of complex communication protocols by simulation, based on formal description techniques (FDT). We propose a general-purpose scalable mod...
In this paper a two-level hierarchical model for the location of concentrators and routers in computers networks is presented. Given a set of candidate locations and the capacitie...