Application of Cuckoo Search Algorithm User Interface for Parameter Optimization of Ultrasonic Machining Process

2020 ◽  
pp. 147-173
Author(s):  
D. Singh ◽  
R. S. Shukla
Keyword(s):  
User Interface ◽  
Parameter Optimization ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Machining Process ◽  
Ultrasonic Machining

scholarly journals Optimization of Roundness Error in Deep Hole Drilling using Cuckoo Search Algorithm

2019 ◽  
Vol 18 (3) ◽  
pp. 44-48
Author(s):  
Azizah Mohamad ◽  
Azlan Mohd Zain ◽  
Razana Alwee ◽  
Noordin Mohd Yusof ◽  
Farhad Najarian
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Machining Process ◽  
Hole Drilling ◽  
Machining Parameters ◽  
Deep Hole ◽  
Roundness Error ◽  
Deep Hole Drilling ◽  
Minimum Value

In the manufacturing industry, machining is a part of all manufacture in almost all metal products. Machining of holes is one of the most common processes in the manufacturing industries. Deep hole drilling,  DHD is classified as a complex machining process .This study presents an optimization of machining parameters in DHD using Cuckoo Search algorithm, CS comprising feed rate (f), spindle speed (s), depth of hole (d) and Minimum Quantity Lubrication MQL, (m). The machining performance measured is roundness error, Re. The real experimentation was designed based on Design of Experiment, DoE which is two levels full factorial with an added centre point. The experimental results were used to develop the mathematical model using regression analysis that used in the optimization process. Analysis of variance (ANOVA) and Fisher‘s statistical test (F-test) are used to check the significant of the model developed.  According to the results obtained by experimental the minimum value of Re  is 0.0222µm and by CS is 0.0198µm. For the conclusion, it was found that CS is capable of giving the minimum value of Re as it outperformed the result from the experimental.

Application of Differential Evolution Cuckoo Search Algorithm in Parameter Optimization of VG Equation

2021 ◽  
Vol 35 (09) ◽  
pp. 2159033
Author(s):  
Bo Yuan ◽  
Deji Chen
Keyword(s):  
Soil Moisture ◽  
Differential Evolution ◽  
Parameter Optimization ◽  
Optimization Model ◽  
Hybrid Algorithm ◽  
Search Algorithm ◽  
Characteristic Curve ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Moisture Characteristic

Van Genuchten (VG) equation is the most commonly used equation of soil moisture characteristic curve, and the accuracy of its parameters directly affects the calculation accuracy of soil moisture motion equation. In order to obtain the parameters of the equation more accurately, this paper establishes an optimization model of the VG equation parameters. This optimization model uses the advantages of the cuckoo search algorithm and the differential evolution algorithm to combine the two into a new hybrid cuckoo search algorithm, namely DECS algorithm, and uses this algorithm to solve the parameter optimization problem of VG equation of soil moisture characteristic curve. By collecting and analyzing the relevant experimental data of various soil qualities, the dehumidification and moisture absorption curves of three different soil qualities were selected for simulation calculation. The results show that in the experiment of solving the parameter estimation problem of the VG equation, the DECS hybrid algorithm has better exploration and development capabilities than the cuckoo search algorithm. The hybrid algorithm has relatively significant performance in terms of calculation accuracy and convergence.

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