This paper introduces the design of rough neurons based on rough sets. Rough neurons instantiate approximate reasoning in assessing knowledge gleaned from input data. Each neuron c...
James F. Peters, Andrzej Skowron, Zbigniew Suraj, ...
A recurring theme in AI and multiagent systems is how to select the "most desirable" elements given a binary dominance relation on a set of alternatives. Schwartz's...
Felix Brandt, Felix A. Fischer, Paul Harrenstein, ...
We propose the use of rough sets theory to improve the first approximation provided by a multi-objective evolutionary algorithm and retain the nondominated solutions using a new ...
Traditionally, membership to the fuzzy-rough lower, resp. upper approximation is determined by looking only at the worst, resp. best performing object. Consequently, when applied t...
We present a novel surface reconstruction algorithm that can recover high-quality surfaces from noisy and defective data sets without any normal or orientation information. A set ...