Titlebook: Recent Advances in Soft Computing; Proceedings of 23rd Radek Matou?ek Conference proceedings 2019 Springer Nature Switzerland AG 2019 Soft

Semblance

Optimization of Protein Mixture Filtration]. Filtration process of this mixture is very complicated because it is case of mixture filtration with compressible cake. Successful process strongly depends on mathematical describing of filtration, calculating optimal values of pressure difference, specific resistant of filtration cake and temper

inflame

Accelerated Genetic Programmings. Compared to neural networks (MLP), they can find a model in the form of a relatively simple mathematical relationship. The disadvantage is their computational difficulty. The following text describes several algorithm adjustments to enable acceleration and wider usage of the genetic programming.

regale

zonules

有斑點

Comparison of Three Novelty Approaches to Constants (Ks) Handling in Analytic Programming Powered bysed Differential evolution (SHADE). AP is a tool for symbolic regression tasks which enables to synthesise an analytical solution based on the required behaviour of the system. This paper offers another strategy to already known and used by the AP from the very beginning and approaches published rec

euphoria

Proposal of a New Swarm Optimization Method Inspired in Bison Behaviorarming into the circle of the strongest individuals and exploring the search space via organized run throughout the optimization process. The proposed algorithm is compared to the Particle Swarm Optimization and the Cuckoo Search algorithms on four benchmark functions.

abreast

AGATE

Waste Processing Facility Location Problem by Stochastic Programming: Models and Solutions units, optimal against the total expected cost. We minimize the waste management (WM) expenditure of the waste producers, which is derived from the related waste processing, transportation, and investment costs. We use a stochastic programming approach in recognition of the inherent uncertainties i

我沒有強迫

incisive

Grammatical Evolution for Classification into Multiple Classese short executable structures which are evolved to classify given input into multiple classes. Resulting structures are usable as computer programs for embedded devices with low computational resources. An universal formula for fitness value calculation of the evolved individual is introduced and an