A major challenge facing grid applications is the appropriate handling of failures. In this paper we address the problem of making parallel Java applications based on Remote Method...
Particle Swarm Optimisation (PSO) uses a population of particles that fly over the fitness landscape in search of an optimal solution. The particles are controlled by forces tha...
Riccardo Poli, Cecilia Di Chio, William B. Langdon
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Abstract--This study proposes an efficient self-evolving evolutionary learning algorithm (SEELA) for neurofuzzy inference systems (NFISs). The major feature of the proposed SEELA i...
Behavior synthesis and optimization beyond the register transfer level require an efficient utilization of the underlying platform features. This paper presents a platform-based ...