114,83 €
127,59 €
-10% with code: EXTRA
Dynamic Parameter Adaptation for Meta-Heuristic Optimization Algorithms Through Type-2 Fuzzy Logic
Dynamic Parameter Adaptation for Meta-Heuristic Optimization Algorithms Through Type-2 Fuzzy Logic
114,83
127,59 €
  • We will send in 10–14 business days.
Proposes a methodology for parameter adaptation in meta-heuristic optimization methodsUses three different optimization methods: PSO (Particle Swarm Optimization), ACO (Ant Colony Optimization) and GSA (Gravitational Search Algorithm), to verify the improvement of the proposed methodologyDemonstrates the advantage of the methodology by using various simulations
127.59
  • Publisher:
  • ISBN-10: 3319708503
  • ISBN-13: 9783319708508
  • Format: 15.6 x 23.4 x 0.6 cm, minkšti viršeliai
  • Language: English
  • SAVE -10% with code: EXTRA

Dynamic Parameter Adaptation for Meta-Heuristic Optimization Algorithms Through Type-2 Fuzzy Logic (e-book) (used book) | bookbook.eu

Reviews

Description

Proposes a methodology for parameter adaptation in meta-heuristic optimization methods
Uses three different optimization methods: PSO (Particle Swarm Optimization), ACO (Ant Colony Optimization) and GSA (Gravitational Search Algorithm), to verify the improvement of the proposed methodology
Demonstrates the advantage of the methodology by using various simulations

EXTRA 10 % discount with code: EXTRA

114,83
127,59 €
We will send in 10–14 business days.

The promotion ends in 21d.12:44:56

The discount code is valid when purchasing from 10 €. Discounts do not stack.

Log in and for this item
you will receive 1,28 Book Euros!?
  • Author: Frumen Olivas
  • Publisher:
  • ISBN-10: 3319708503
  • ISBN-13: 9783319708508
  • Format: 15.6 x 23.4 x 0.6 cm, minkšti viršeliai
  • Language: English English

Proposes a methodology for parameter adaptation in meta-heuristic optimization methods
Uses three different optimization methods: PSO (Particle Swarm Optimization), ACO (Ant Colony Optimization) and GSA (Gravitational Search Algorithm), to verify the improvement of the proposed methodology
Demonstrates the advantage of the methodology by using various simulations

Reviews

  • No reviews
0 customers have rated this item.
5
0%
4
0%
3
0%
2
0%
1
0%
(will not be displayed)