Genetic algorithm for the determination of development system in mine

2020 ◽  
pp. 209-212
Author(s):  
Q.X. Yun ◽  
K.M. Huang
Keyword(s):  
Genetic Algorithm ◽  
Development System

FIDDLE. Simultaneous Indexing and Structure Solution from Powder Diffraction Data using a Genetic Algorithm and Correlation Functions

2019 ◽  
Author(s):  
Carmen Guguta ◽  
Jan M.M. Smits ◽  
Rene de Gelder
Keyword(s):  
Genetic Algorithm ◽  
Powder Diffraction ◽  
Diffraction Data ◽  
Correlation Functions ◽  
Cross Correlation ◽  
Simultaneous Optimization ◽  
Powder Diffraction Data ◽  
Structure Solution ◽  
Matching Technique

A method for the determination of crystal structures from powder diffraction data is presented that circumvents the difficulties associated with separate indexing. For the simultaneous optimization of the parameters that describe a crystal structure a genetic algorithm is used together with a pattern matching technique based on auto and cross correlation functions.<br>

scholarly journals Full spectrum and genetic algorithm-selected spectrum-based chemometric methods for simultaneous determination of azilsartan medoxomil, chlorthalidone, and azilsartan: Development, validation, and application on commercial dosage form

2021 ◽  
Vol 19 (1) ◽  
pp. 205-213
Author(s):  
Hany W. Darwish ◽  
Abdulrahman A. Al Majed ◽  
Ibrahim A. Al-Suwaidan ◽  
Ibrahim A. Darwish ◽  
Ahmed H. Bakheit ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Simultaneous Determination ◽  
Predictive Power ◽  
Principal Component Regression ◽  
Selection Procedure ◽  
Principal Component ◽  
Chemometric Methods ◽  
Full Spectrum ◽  
Azilsartan Medoxomil

Abstract Five various chemometric methods were established for the simultaneous determination of azilsartan medoxomil (AZM) and chlorthalidone in the presence of azilsartan which is the core impurity of AZM. The full spectrum-based chemometric techniques, namely partial least squares (PLS), principal component regression, and artificial neural networks (ANN), were among the applied methods. Besides, the ANN and PLS were the other two methods that were extended by genetic algorithm procedure (GA-PLS and GA-ANN) as a wavelength selection procedure. The models were developed by applying a multilevel multifactor experimental design. The predictive power of the suggested models was evaluated through a validation set containing nine mixtures with different ratios of the three analytes. For the analysis of Edarbyclor® tablets, all the proposed procedures were applied and the best results were achieved in the case of ANN, GA-ANN, and GA-PLS methods. The findings of the three methods were revealed as the quantitative tool for the analysis of the three components without any intrusion from the co-formulated excipient and without prior separation procedures. Moreover, the GA impact on strengthening the predictive power of ANN- and PLS-based models was also highlighted.

scholarly journals GENETIC ALGORITHM BASED SOLUTION IN PWM CONVERTER SWITCHING FOR VOLTAGE SOURCE INVERTER FEEDING AN INDUCTION MOTOR DRIVE

2017 ◽  
Vol 27 (2) ◽  
pp. 45-60
Author(s):  
V. Jegathesan
Keyword(s):  
Genetic Algorithm ◽  
Lower Order ◽  
Pulse Width Modulation ◽  
Experimental Results ◽  
Voltage Source ◽  
Pwm Inverter ◽  
Harmonic Elimination ◽  
Transcendental Equations ◽  
Voltage Harmonics

This paper presents an efficient and reliable Genetic Algorithm based solution for Selective Harmonic Elimination (SHE) switching pattern. This method eliminates considerable amount of lower order line voltage harmonics in Pulse Width Modulation (PWM) inverter. Determination of pulse pattern for the elimination of some lower order harmonics of a PWM inverter necessitates solving a system of nonlinear transcendental equations. Genetic Algorithm is used to solve nonlinear transcendental equations for PWM-SHE. Many methods are available to eliminate the higher order harmonics and it can be easily removed. But the greatest challenge is to eliminate the lower order harmonics and this is successfully achieved using Genetic Algorithm without using Dual transformer. Simulations using MATLABTM and Powersim with experimental results are carried out to validate the solution. The experimental results show that the harmonics up to 13th were totally eliminated. 

scholarly journals Lecture Scheduling Automation Using Genetic Algorithm

2019 ◽  
Vol 8 (5C) ◽  
pp. 1444-1447
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Test Results ◽  
Scheduling Problems ◽  
Scheduling System ◽  
Parameter Values

This paper aims produce an academic scheduling system using Genetic Algorithm (GA) to solve the academic schedule. Factors to consider in academic scheduling are the lecture to be held, the available room, the lecturers and the time of the lecturer, the suitability of the credits with the time of the lecture, and perhaps also the time of Friday prayers, and so forth. Genetic Algorithms can provide the best solution for some solutions in dealing with scheduling problems. Based on the test results, the resulting system can automate the scheduling of lectures properly. Determination of parameter values in Genetic Algorithm also gives effect in producing the solution of lecture schedule

scholarly journals OPTIMIZATION OF PHARMACEUTICAL WASTEWATER TREATMENT BY BIOSORPTION USING GENETIC ALGORITHM

2021 ◽  
Vol 6 (2) ◽  
pp. 31-38
Author(s):  
Ola Belal Hasan Abdallah ◽  
Priy Brat Dwivedi
Keyword(s):  
Genetic Algorithm ◽  
Wastewater Treatment ◽  
Model Equation ◽  
Diclofenac Sodium ◽  
Pharmaceutical Wastewater ◽  
Design Expert ◽  
Pharmaceutical Industries ◽  
Percentage Removal ◽  
Optimized Conditions

Purpose of the study: Optimizing the process of pharmaceutical wastewater treatment by biosorption using a genetic algorithm. Methodology: The main steps followed were, determination of the wavelength at maximum absorbance (λmax), drawing the calibration curve between the absorbance and the concentration of diclofenac sodium, designing the experiment using Design-Expert software, finding the percentage removal of diclofenac sodium for each run, obtaining the model equation of the analysis, finding the optimized condition using genetic algorithm in MATLAB software, running the experiment at the optimized conditions and analyzing the results. Main Findings: The technique used in the optimizing process was effective, in which the percentage removal was obtained as 8.73% at the optimized conditions. It was equivalent to 3.43 mg removal / g of activated carbon. Applications of this study: This technique can be applied in different industries especially the chemical and pharmaceutical industries. Novelty/Originality of this study: Using genetic algorithm in order to find the optimized condition of removing diclofenac sodium based on a set of data.

Sign in / Sign up

Export Citation Format

Share Document