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Wyszukujesz frazę "evolution algorithm" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Fuzzy ranking based non-dominated sorting genetic algorithm-II for network overload alleviation
Autorzy:
Pandiarajan, K.
Babulal, C. K.
Powiązania:
https://bibliotekanauki.pl/articles/141059.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
non-dominated sorting genetic algorithm
generation rescheduling
particle swarm optimization (PSO)
differential evolution
overload index
Opis:
This paper presents an effective method of network overload management in power systems. The three competing objectives 1) generation cost 2) transmission line overload and 3) real power loss are optimized to provide pareto-optimal solutions. A fuzzy ranking based non-dominated sorting genetic algorithm-II (NSGA-II) is used to solve this complex nonlinear optimization problem. The minimization of competing objectives is done by generation rescheduling. Fuzzy ranking method is employed to extract the best compromise solution out of the available non-dominated solutions depending upon its highest rank. N-1 contingency analysis is carried out to identify the most severe lines and those lines are selected for outage. The effectiveness of the proposed approach is demonstrated for different contingency cases in IEEE 30 and IEEE 118 bus systems with smooth cost functions and their results are compared with other single objective evolutionary algorithms like Particle swarm optimization (PSO) and Differential evolution (DE). Simulation results show the effectiveness of the proposed approach to generate well distributed pareto-optimal non-dominated solutions of multi-objective problem
Źródło:
Archives of Electrical Engineering; 2014, 63, 3; 367-384
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An Analytical Study for the Role of Fuzzy Logic in Improving Metaheuristic Optimization Algorithms
Autorzy:
Vij, Sonakshi
Jain, Amita
Tayal, Devendra
Castillo, Oscar
Powiązania:
https://bibliotekanauki.pl/articles/385121.pdf
Data publikacji:
2018
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
fuzzy logic
metaheuristics
evolutionary computing
genetic algorithm
particle swarm optimization (PSO)
ant colony optimization
fuzzy evolutionary algorithm
fuzzy cuckoo
fuzzy simulated annealing
fuzzy swarm intelligence
fuzzy differential evolution
tabu
fuzzy mutation
fuzzy natural selection
fuzzy fitness function
big bang big crunch
fuzzy bacterial
neuro fuzzy logic
logika rozmyta
metaheurystyka
obliczenia ewolucyjne
algorytm genetyczny
optymalizacja roju cząstek
optymalizacja kolonii mrówek
Opis:
The research applications of fuzzy logic have always been multidisciplinary in nature due to its ability in handling vagueness and imprecision. This paper presents an analytical study in the role of fuzzy logic in the area of metaheuristics using Web of Science (WoS) as the data source. In this case, 178 research papers are extracted from it in the time span of 1989-2016. This paper analyzes various aspects of a research publication in a scientometric manner. The top cited research papers, country wise contribution, topmost organizations, top research areas, top source titles, control terms and WoS categories are analyzed. Also, the top 3 fuzzy evolutionary algorithms are extracted and their top research papers are mentioned along with their topmost research domain. Since neuro fuzzy logic poses feasible options for solving numerous research problems, hence a section is also included by the authors to present an analytical study regarding research in it. Overall, this study helps in evaluating the recent research patterns in the field of fuzzy metaheuristics along with envisioning the future trends for the same. While on one hand this helps in providing a new path to the researchers who are beginners in this field as they can start exploring it through the analysis mentioned here, on the other hand it provides an insight to professional researchers too who can dig a little deeper in this field using knowledge from this study.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2018, 12, 4; 11-27
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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