Pregled bibliografske jedinice broj: 932955
Finding Optimal Input Values for Desired Target Output by Using Particle Swarm Optimization Algorithm Within Probabilistic Models
Finding Optimal Input Values for Desired Target Output by Using Particle Swarm Optimization Algorithm Within Probabilistic Models // Incorporating Nature-Inspired Paradigms in Computational Applications / Khosrow-Pour, Mehdi. (ur.).
Hershey (PA): IGI Global, 2018. str. 76-107 doi:10.4018/978-1-5225-5020-4.ch003
CROSBI ID: 932955 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Finding Optimal Input Values for Desired Target Output by Using Particle Swarm Optimization Algorithm Within Probabilistic Models
Autori
Klepac, Goran
Vrsta, podvrsta i kategorija rada
Poglavlja u knjigama, ostalo
Knjiga
Incorporating Nature-Inspired Paradigms in Computational Applications
Urednik/ci
Khosrow-Pour, Mehdi.
Izdavač
IGI Global
Grad
Hershey (PA)
Godina
2018
Raspon stranica
76-107
ISBN
9781522550204
Ključne riječi
Swarm intelligence , optimisation
Sažetak
Developed predictive models, especially models based on probabilistic concept, regarding numerous potential combinatory states can be very complex. That complexity can cause uncertainty about which factors should have which values to achieve optimal value of output. An example of that problem is developed with a Bayesian network with numerous potential states and their interaction when we would like to find optimal value of nodes for achieving maximum probability on specific output node. This chapter shows a novel concept based on usage of the particle swarm optimization algorithm for finding optimal values within developed probabilistic models.
Izvorni jezik
Engleski
Citiraj ovu publikaciju:
Časopis indeksira:
- Scopus
