Training ANFIS by using the artificial bee colony algorithm
نویسندگان
چکیده
منابع مشابه
OPTIMIZATION OF SKELETAL STRUCTURAL USING ARTIFICIAL BEE COLONY ALGORITHM
Over the past few years, swarm intelligence based optimization techniques such as ant colony optimization and particle swarm optimization have received considerable attention from engineering researchers. These algorithms have been used in the solution of various structural optimization problems where the main goal is to minimize the weight of structures while satisfying all design requirements...
متن کاملStructural optimization using artificial bee colony algorithm
This paper presents an artificial bee colony (ABC) algorithm for structural optimization of planar and space trusses under stress, displacement and buckling constraints. In order to improve the performance of the classic ABC algorithm, modifications in neighborhood searching method, onlooker phase, and scout phase are proposed. Optimization of different typical truss structures is performed usi...
متن کاملElite Opposition-based Artificial Bee Colony Algorithm for Global Optimization
Numerous problems in engineering and science can be converted into optimization problems. Artificial bee colony (ABC) algorithm is a newly developed stochastic optimization algorithm and has been widely used in many areas. However, due to the stochastic characteristics of its solution search equation, the traditional ABC algorithm often suffers from poor exploitation. Aiming at this weakness o...
متن کاملArtificial Bee Colony Training of Neural Networks
The Artificial Bee Colony (ABC) is a recently introduced swarm intelligence algorithm for optimization, that has previously been applied successfully to the training of neural networks. This paper explores more carefully the performance of the ABC algorithm for optimizing the connection weights of feed-forward neural networks for classification tasks, and presents a more rigorous comparison wit...
متن کاملTraining Spiking Neural Models Using Artificial Bee Colony
Spiking neurons are models designed to simulate, in a realistic manner, the behavior of biological neurons. Recently, it has been proven that this type of neurons can be applied to solve pattern recognition problems with great efficiency. However, the lack of learning strategies for training these models do not allow to use them in several pattern recognition problems. On the other hand, severa...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES
سال: 2017
ISSN: 1300-0632,1303-6203
DOI: 10.3906/elk-1601-240