A novel hybrid algorithm combining hunting search with harmony search algorithm for training neural networks

2013 ◽  
Vol 64 (5) ◽  
pp. 748-761 ◽  
Author(s):  
S Kulluk
Keyword(s):  
Neural Networks ◽  
Hybrid Algorithm ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm

scholarly journals Application of Harmony Search algorithm with Neural Networks Solving MTHD Problem in Multi l evel inverter with Alterable DC links

2016 ◽  
Vol 8 (1) ◽  
pp. 12-28 ◽  
Author(s):  
Mohammad Reza Jannati Oskuee ◽  
◽  
Rahim Shamsi Varzeghan ◽  
Alireza Eyvaz i zadeh Khosroshahi ◽  
Sajad Najafi Ravadanegh ◽  
...  
Keyword(s):  
Neural Networks ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm

scholarly journals Economic and Emission Dispatch Problems Using a New Hybrid Algorithm

2021 ◽  
Vol 15 ◽  
pp. 21-28
Author(s):  
Mimoun Younes ◽  
Fouad Khodja ◽  
Riad Lakhdar Kherfene
Keyword(s):  
Hybrid Algorithm ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Optimization Techniques ◽  
Computational Time ◽  
Environmental Legislation ◽  
Multi Objective ◽  
Economic Power Dispatch ◽  
Emission Dispatch

Environmental legislation, with its increasing pressure on the energy sector to control greenhouse gases, is a driving force to reduce CO2 emissions, forced the power system operators to consider the emission problem as a consequential matter beside the economic problems, so the economic power dispatch problem has become a multi-objective optimization problem. This paper sets up an new hybrid algorithm combined in two algorithm, the harmony search algorithm and ant colony optimization (HSA-ACO), to solve the optimization with combined economic emission dispatch. This problem has been formulated as a multi-objective problem by considering both economy and emission simultaneously. The feasibility of the proposed approach was tested on 3-unit and 6-unit systems. The simulation results show that the proposed algorithm gives comparatively better operational fuel cost and emission in less computational time compared to other optimization techniques.

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