Atnaujintas knygų su minimaliais defektais pasiūlymas! Naršykite ČIA >>

Solution To Energy And Environmental Problems Of Electric Power System: Using Hybdrid Meta-heuristics Search Algorithms

-15% su kodu: ENG15
48,81 
Įprasta kaina: 57,42 
-15% su kodu: ENG15
Kupono kodas: ENG15
Akcija baigiasi: 2025-03-03
-15% su kodu: ENG15
48,81 
Įprasta kaina: 57,42 
-15% su kodu: ENG15
Kupono kodas: ENG15
Akcija baigiasi: 2025-03-03
-15% su kodu: ENG15
2025-02-28 57.4200 InStock
Nemokamas pristatymas į paštomatus per 11-15 darbo dienų užsakymams nuo 10,00 

Knygos aprašymas

Salp swarm algorithm simulates the behaviour of salps in the salp chain during navigating and foraging in oceans. Salp swarm optimizer is inspired by salps and recently proposed metaheuristics search algorithm is based on ocean Salps. The salps form a chain (salp chain) for achieving precise locomotion by using coordinate changes. In the proposed research, a hybrid variant of salp swarm algorithm has been developed using a simulated annealing algorithm and named as SSA-SA. The proposed algorithm has been tested for various unimodal, multimodal and fixed-dimensions problems and corresponding results are compared with classical salp swarm optimizer. Experimentally, it has been observed that the proposed hybrid optimizer perform much better than other recently proposed algorithms and has been applied to solve power system optimization problems including multi-objective scheduling and dispatch problem of the realistic power system.

Informacija

Autorius: Vikram Kumar
Leidėjas: LAP LAMBERT Academic Publishing
Išleidimo metai: 2020
Knygos puslapių skaičius: 88
ISBN-10: 6202798270
ISBN-13: 9786202798273
Formatas: 220 x 150 x 6 mm. Knyga minkštu viršeliu
Kalba: Anglų

Pirkėjų atsiliepimai

Parašykite atsiliepimą apie „Solution To Energy And Environmental Problems Of Electric Power System: Using Hybdrid Meta-heuristics Search Algorithms“

Būtina įvertinti prekę

Goodreads reviews for „Solution To Energy And Environmental Problems Of Electric Power System: Using Hybdrid Meta-heuristics Search Algorithms“