Deterministic Parameter Selection of Artificial Bee Colony Based on Diagonalization

2019 ◽  
pp. 85-95
Author(s):  
Marco Antonio Florenzano Mollinetti ◽  
Mario Tasso Ribeiro Serra Neto ◽  
Takahito Kuno
Keyword(s):  
Artificial Bee Colony ◽  
Parameter Selection ◽  
Bee Colony ◽  
Selection Of

Logistic step size based artificial bee colony algorithm for optimum induction motor speed control

2019 ◽  
Vol 12 ◽  
Author(s):  
Fani Bhushan Sharma ◽  
Shashi Raj Kapoor
Keyword(s):  
Induction Motor ◽  
Artificial Bee Colony ◽  
Optimization Problems ◽  
Pi Controller ◽  
Motor Speed ◽  
Step Size ◽  
Abc Algorithm ◽  
Bee Colony ◽  
Pi Controllers ◽  
Selection Of

: The disruption in the parameters of induction motor (IM) are quite frequent. In case of substantial parameter disruption the IM becomes unreliable. To deal with this complication of parameter disruption the proportional integral (PI) controllers are utilized. The selection of PI controller parameters is process dependent and any inappropriate selection of controller setting may diverge to instability. In recent years swarm intelligence (SI) based algorithms are executing well to solve real-world optimization problems. Now a days, the tuning of PI controller parameters for IM is executed using a significant SI algorithm namely, artificial bee colony (ABC) algorithm. Further, the ABC algorithm is amended based on inspiration from mathematical logistic formula. The propound algorithm is titled as logistic ABC algorithm and is applied for PI controller tuning of IM. The outcomes reveals that the propound algorithm performs better as compared to other state- of-art strategies available in the literature.

scholarly journals Dynamic Relay Satellite Scheduling Based on ABC-TOPSIS Algorithm

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Shufeng Zhuang ◽  
Zhendong Yin ◽  
Zhilu Wu ◽  
Xiaoguang Chen
Keyword(s):  
Artificial Bee Colony ◽  
Dynamic Scheduling ◽  
Research Field ◽  
Scheduling Problem ◽  
Ideal Solution ◽  
Bee Colony ◽  
Order Preference ◽  
Simulation Results ◽  
Satellite Scheduling ◽  
Selection Of

Tracking and Data Relay Satellite System (TDRSS) is a space-based telemetry, tracking, and command system, which represents a research field of the international communication. The issue of the dynamic relay satellite scheduling, which focuses on assigning time resource to user tasks, has been an important concern in the TDRSS system. In this paper, the focus of study is on the dynamic relay satellite scheduling, whose detailed process consists of two steps: the initial relay satellite scheduling and the selection of dynamic scheduling schemes. To solve the dynamic scheduling problem, a new scheduling algorithm ABC-TOPSIS is proposed, which combines artificial bee colony (ABC) and technique for order preference by similarity to ideal solution (TOPSIS). The artificial bee colony algorithm is performed to solve the initial relay satellite scheduling. In addition, the technique for order preference by similarity to ideal solution is adopted for the selection of dynamic scheduling schemes. Plenty of simulation results are presented. The simulation results demonstrate that the proposed method provides better performance in solving the dynamic relay satellite scheduling problem in the TDRSS system.

scholarly journals An Improved ABC Algorithm and Its Application in Bearing Fault Diagnosis with EEMD

Algorithms ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 72 ◽  
Author(s):  
Weijia Chen ◽  
Yancai Xiao
Keyword(s):  
Fault Diagnosis ◽  
Artificial Bee Colony ◽  
The Other ◽  
Abc Algorithm ◽  
Original Algorithm ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis ◽  
Bee Colony ◽  
Selection Of ◽  
Improved Algorithm

The Ensemble Empirical Mode Decomposition (EEMD) algorithm has been used in bearing fault diagnosis. In order to overcome the blindness in the selection of white noise amplitude coefficient e in EEMD, an improved artificial bee colony algorithm (IABC) is proposed to obtain it adaptively, which providing a new idea for the selection of EEMD parameters. In the improved algorithm, chaos initialization is introduced in the artificial bee colony (ABC) algorithm to insure the diversity of the population and the ergodicity of the population search process. On the other hand, the collecting bees are divided into two parts in the improved algorithm, one part collects the optimal information of the region according to the original algorithm, the other does Levy flight around the current global best solution to improve its global search capabilities. Four standard test functions are used to show the superiority of the proposed method. The application of the IABC and EEMD algorithm in bearing fault diagnosis proves its effectiveness.

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