Scopus
YÖKSİS DOI Eşleşti
SJR Q1
Cost optimization of mixed feeds with the particle swarm optimization method
Neural Computing and Applications · Şubat 2013
Özet
In this study, the best mixed feed was prepared by using the algorithm of particle swarm optimization (PSO) and by taking into account the breeding type and method of the poultries and various farm animals (cattle, sheep, rabbit), their needs, ages, and feeding costs and optimizing them all. Results obtained through PSO were compared through linear programming and real-coded genetic algorithm. According to the results that were obtained, PSO produces more rapid, more stable, and optimum values. © 2011 Springer-Verlag London Limited.
YÖKSİS Kayıtları
Cost optimization of mixed feeds with the particle swarm optimization method
NEURAL COMPUTING & APPLICATIONS · 2013 SCI-Expanded
Doç. Dr. MEHMET AKİF ŞAHMAN →
Cost optimization of mixed feeds with the particle swarm optimization method
Neural Computing and Applications · 2013 SCI-Expanded
Prof. Dr. ADEM ALPASLAN ALTUN →
YÖKSİS Kayıtları — ISSN Eşleşmesi
Bu dergide (ISSN eşleşmesi) kurumun 20 kaydı bulundu.
YÖKSİS Kayıtları — ISSN Eşleşmesi
Bu dergide (ISSN eşleşmesi) kurumun 20 kaydı bulundu.
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Cost optimization of mixed feeds with the particle swarm optimization method
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Fuzzy logic based induction motor protection system
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Makale Bilgileri
Toplam Atıf
37 atıf
· Scopus
ISSN09410643
Yayın TarihiŞubat 2013
Cilt / Sayfa22 · 383-390
Scopus ID2-s2.0-84872599141
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey
Havuzumuzdaki Atıflar 0
Bu makaleye, sistemimizdeki Scopus veritabanında bulunan 0 makale atıf yapmıştır. Scopus genel atıf sayısı: 37.
Bu makaleye, kendi Scopus havuzumuzdaki başka bir makaleden atıf kaydı bulunmuyor.
Scimago Dergi (ISSN Eşleşmesi)
Neural Computing and Applications
Q1
SJR Skoru1,067
H-Index166
YayıncıSpringer London
ÜlkeUnited Kingdom
Artificial Intelligence (Q1)
Software (Q1)
Metrikler
37
Atıf