Particle Stability Time in the Stochastic Model of PSO

Studies in Computational Intelligence - Computational Intelligence ◽

10.1007/978-3-030-16469-0_1 ◽

2019 ◽

pp. 1-18

Author(s):

Krzysztof Trojanowski ◽

Tomasz Kulpa

Keyword(s):

Stochastic Model ◽

Particle Stability ◽

Stability Time

Download Full-text

Stasis type particle stability in a stochastic model of particle swarm optimization

Proceedings of the Genetic and Evolutionary Computation Conference ◽

10.1145/3449639.3459405 ◽

2021 ◽

Author(s):

Tomasz Kulpa ◽

Krzysztof Trojanowski ◽

Krzysztof Wójcik

Keyword(s):

Particle Swarm Optimization ◽

Stochastic Model ◽

Particle Swarm ◽

Swarm Optimization ◽

Particle Stability ◽

Type Particle

Download Full-text

A Fruitful Stochastic Model

Contemporary Psychology ◽

10.1037/007600 ◽

1964 ◽

Vol 9 (7) ◽

pp. 273-276

Author(s):

ANATOL RAPOPORT

Keyword(s):

Stochastic Model

Download Full-text

Some thoughts on "A stochastic model for individual choice behaviour"

PsycEXTRA Dataset ◽

10.1037/e627282012-097 ◽

1960 ◽

Author(s):

R. J. Audley

Keyword(s):

Stochastic Model ◽

Individual Choice ◽

Choice Behaviour

Download Full-text

A Stochastic Model for Evolution of Altruistic Genes

Journal de Physique I ◽

10.1051/jp1:1996223 ◽

1996 ◽

Vol 6 (4) ◽

pp. 445-453 ◽

Cited By ~ 4

Author(s):

Roberta Donato

Keyword(s):

Stochastic Model

Download Full-text

A Stochastic Model for the Inheritance of the Cancer Proneness Phenotype

Methods of Information in Medicine ◽

10.1055/s-0038-1636689 ◽

1987 ◽

Vol 26 (03) ◽

pp. 117-123

Author(s):

P. Tautu ◽

G. Wagner

Keyword(s):

Stochastic Model ◽

Gaussian Process ◽

Covariance Function ◽

Neoplastic Disease ◽

Disease Phenotype ◽

Probabilistic Representation ◽

Temporal Behaviour ◽

Continuous Trait ◽

Continuous Parameter ◽

Level Zero

SummaryA continuous parameter, stationary Gaussian process is introduced as a first approach to the probabilistic representation of the phenotype inheritance process. With some specific assumptions about the components of the covariance function, it may describe the temporal behaviour of the “cancer-proneness phenotype” (CPF) as a quantitative continuous trait. Upcrossing a fixed level (“threshold”) u and reaching level zero are the extremes of the Gaussian process considered; it is assumed that they might be interpreted as the transformation of CPF into a “neoplastic disease phenotype” or as the non-proneness to cancer, respectively.

Download Full-text