Satisfiability problem is an NP-complete problem that finds itself or its variants in many combinatorial problems. There exist many complete algorithms that give successful results...
This research introduces a general class of functions serving as generalized neuron models to be used in artificial neural networks. They are cast in the common framework of comp...
Abstract- On marginal winter nights, highway authorities face a difficult decision as to whether or not to salt the road network. The consequences of making a wrong decision are s...
— Ordinal regression is an important type of learning, which has properties of both classification and regression. Here we describe an effective approach to adapt a traditional ...
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...