Optimal Design of Low Voltage CMOS Second Generation Current Conveyor Using Hybrid Cuckoo Search and Particle Swarm Optimization Algorithm

2017 ◽  
Author(s):  
K. B. Maji ◽  
R. Kar ◽  
D. Mandal ◽  
S. P. Ghoshal
Keyword(s):  
Particle Swarm Optimization ◽  
Optimal Design ◽  
Optimization Algorithm ◽  
Second Generation ◽  
Particle Swarm Optimization Algorithm ◽  
Low Voltage ◽  
Particle Swarm ◽  
Cuckoo Search ◽  
Current Conveyor ◽  
Swarm Optimization

Optimal Design of Multi-Channel Fiber Bragg Grating Filters Based on Particle Swarm Optimization Algorithm

2014 ◽  
Vol 34 (8) ◽  
pp. 0806005
Author(s):  
刘暾东 Liu Tundong ◽  
叶增软 Ye Zengruan ◽  
陈静 Chen Jing ◽  
陶继平 Tao Jiping ◽  
江灏 Jiang Hao
Keyword(s):  
Particle Swarm Optimization ◽  
Optimal Design ◽  
Fiber Bragg Grating ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Bragg Grating ◽  
Swarm Optimization ◽  
Bragg Grating Filters

Test Case Optimization and Prioritization Using Improved Cuckoo Search and Particle Swarm Optimization Algorithm

2018 ◽  
Vol 7 (4.6) ◽  
pp. 275
Author(s):  
Chandrasekhara Reddy T ◽  
Srivani V ◽  
A. Mallikarjuna Reddy ◽  
G. Vishnu Murthy
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Heuristic Algorithms ◽  
Search Algorithm ◽  
Particle Swarm ◽  
Cuckoo Search ◽  
Test Suite ◽  
Swarm Optimization ◽  
Cuckoo Algorithm

For minimized t-way test suite generation (t indicates more strength of interaction) recently many meta-heuristic, hybrid and hyper-heuristic algorithms are proposed which includes Artificial Bee Colony (ABC), Ant Colony Optimization (ACO), Genetic Algorithms (GA), Simulated Annealing (SA), Cuckoo Search (CS), Harmony Elements Algorithm (HE), Exponential Monte Carlo with counter (EMCQ), Particle Swarm Optimization (PSO), and Choice Function (CF). Although useful strategies are required specific domain knowledge to allow effective tuning before good quality solutions can be obtained. In our proposed technique test cases are optimized by utilizing Improved Cuckoo Algorithm (ICSA). At that point, the advanced experiments are organized or prioritized by utilizing Particle Swarm Optimization algorithm (PSO). The Particle Swarm Optimization and Improved Cuckoo Algorithm (PSOICSA) estimation is a blend of Improved Cuckoo Search Algorithm(ICSA) and Particle Swarm Optimization (PSO). PSOICSA could be utilized to advance the test suite, and coordinate both ICSA and PSO for a superior outcome, when contrasted with their individual execution as far as experiment improvement. 

scholarly journals Using the Cuckoo Search for Generating New Particles in Particle Swarm Optimization Algorithm

2020 ◽  
Vol 16 (4) ◽  
pp. 430-438
Author(s):  
Fariaa Abdalmajeed Hameed ◽  
Harith Raad Hasan ◽  
Ahmed Abdullah Ahmed ◽  
Gulala Ali Hama Amin
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Cuckoo Search ◽  
Swarm Optimization ◽  
New Particles
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