scholarly journals Application of Evolutionary Algorithms for Modelling and Optimisation of Ultrasound-Related Parameters on Synthesised SAPO-34 Catalysts: Crystallinity and Particle Size

2018 ◽  
Vol 43 (3-4) ◽  
pp. 236-243 ◽  
Author(s):  
Mohammad Javad Azarhoosh ◽  
Rouein Halladj ◽  
Sima Askari
Keyword(s):  
Genetic Algorithm ◽  
Particle Size ◽  
Predictive Power ◽  
Light Olefins ◽  
Fitness Functions ◽  
Minimum Particle Size ◽  
Predicted Values ◽  
Optimum Solution ◽  
Ultrasound Parameters ◽  
Good Agreement

First, the effects of ultrasound-related variables on the crystallinity and particle size of synthesised SAPO-34 catalysts were modelled using a genetic programming (GP) method. The results confirm that GP has good predictive power. Secondly, optimisation of the ultrasound parameters was considered using a genetic algorithm (GA) to obtain SAPO-34 catalysts with high crystallinity and minimum particle size for the best performance in the methanol to light olefins process. The GP models were used as the fitness functions inside the GA. Finally, the optimum solution was validated experimentally and the results indicate that there is a good agreement between experimental and predicted values.

Optimization of Morphology and Particle Size of Modified Sol Gel Synthesized YSZ Nanopowder Using Taguchi Method

2012 ◽  
Vol 21 ◽  
pp. 65-70 ◽  
Author(s):  
Morteza Hajizadeh Oghaz ◽  
Reza Shoja Razavi ◽  
Mohammad Reza Loghman-Estark ◽  
Reza Ghasemi
Keyword(s):  
Particle Size ◽  
Design Method ◽  
Sol Gel ◽  
Chelating Agent ◽  
Experimental Results ◽  
Experimental Conditions ◽  
Influence Of Process Parameters ◽  
Predicted Values ◽  
Good Agreement ◽  
Significant Factors

The morphology and particle size of yttria stabilized zirconia (YSZ) nanopowders synthesized by Pechini's method are very much dependent on the type of chelating agent, pH of solution, calcinations temperature, calcinations time, etc. In the present study, the influence of process parameters like the type of zirconium salt, pH of solution, calcinations temperature and time on the morphology and particle size of a YSZ nanopowder was analyzed by the Taguchi Design method and analysis of variance (ANOVA). According to the experimental results and ANOVA, the pH of solution and calcinations temperature are the most significant factors influencing the morphology and particle size of YSZ nanopowder; pH of solution is the most significant factor influencing the morphology; and calcinations temperature is the most significant factor affecting the particle size. Models were developed for predicting the morphology and particle size of the YSZ nanopowder. They were found to be in good agreement with the experimental results. The models were tested for experimental conditions and were found to be close to predicted values. Both morphology and particle size of YSZ nanopowders were mainly dependent on the pH of solution.

Task scheduling algorithm based on improved genetic algorithm in cloud computing environment

2020 ◽  
Vol 13 ◽  
Author(s):  
Ge Weiqing ◽  
Cui Yanru
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Task Completion ◽  
Improved Genetic Algorithm ◽  
Fitness Functions ◽  
Task Scheduling Algorithm ◽  
Simulation Results

Background: In order to make up for the shortcomings of the traditional algorithm, Min-Min and Max-Min algorithm are combined on the basis of the traditional genetic algorithm. Methods: In this paper, a new cloud computing task scheduling algorithm is proposed, which introduces Min-Min and Max-Min algorithm to generate initialization population, and selects task completion time and load balancing as double fitness functions, which improves the quality of initialization population, algorithm search ability and convergence speed. Results: The simulation results show that the algorithm is superior to the traditional genetic algorithm and is an effective cloud computing task scheduling algorithm. Conclusion: Finally, this paper proposes the possibility of the fusion of the two quadratively improved algorithms and completes the preliminary fusion of the algorithm, but the simulation results of the new algorithm are not ideal and need to be further studied.

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 Seasonal Estimates and Uncertainties of Snow Accumulation from CloudSat Precipitation Retrievals

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 363
Author(s):  
George Duffy ◽  
Fraser King ◽  
Ralf Bennartz ◽  
Christopher G. Fletcher
Keyword(s):  
Time Scales ◽  
Snow Water Equivalent ◽  
Spatial Scales ◽  
Snow Accumulation ◽  
High Latitudes ◽  
Percentage Points ◽  
Snow Water ◽  
Time Periods ◽  
Predicted Values ◽  
Good Agreement

CloudSat is often the only measurement of snowfall rate available at high latitudes, making it a valuable tool for understanding snow climatology. The capability of CloudSat to provide information on seasonal and subseasonal time scales, however, has yet to be explored. In this study, we use subsampled reanalysis estimates to predict the uncertainties of CloudSat snow water equivalent (SWE) accumulation measurements at various space and time resolutions. An idealized/simulated subsampling model predicts that CloudSat may provide seasonal SWE estimates with median percent errors below 50% at spatial scales as small as 2° × 2°. By converting these predictions to percent differences, we can evaluate CloudSat snowfall accumulations against a blend of gridded SWE measurements during frozen time periods. Our predictions are in good agreement with results. The 25th, 50th, and 75th percentiles of the percent differences between the two measurements all match predicted values within eight percentage points. We interpret these results to suggest that CloudSat snowfall estimates are in sufficient agreement with other, thoroughly vetted, gridded SWE products. This implies that CloudSat may provide useful estimates of snow accumulation over remote regions within seasonal time scales.

Astaxanthin–garlic oil nanoemulsions preparation using spontaneous microemulsification technique: optimization and their physico–chemical properties

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Seyedalireza Mortazavi Tabrizi ◽  
Afshin Javadi ◽  
Navideh Anarjan ◽  
Seyyed Javid Mortazavi Tabrizi ◽  
Hamid Mirzaei
Keyword(s):  
Antioxidant Activity ◽  
Particle Size ◽  
Subcritical Water ◽  
Chemical Properties ◽  
Polydispersity Index ◽  
Garlic Oil ◽  
Physico Chemical ◽  
Minimum Particle Size ◽  
Oil In Water ◽  
Technique Optimization

AbstractGarlic oil in water nanoemulsion was resulted through subcritical water method (temperature of 120 °C and pressure of 1.5 bar, for 2 h), using aponin, as emulsifier. Based on the prepared garlic oil nanoemulsion, astaxanthin–garlic oil nanoemulsions were prepared using spontaneous microemulsification technique. Response surface methodology was employed to evaluate the effects of independent variables namely, amount of garlic oil nanoemulsion (1–9 mL) and amount of provided astaxanthin powder (1–9 g) on particle size and polydispersity index (PDI) of the resulted nanoemulsions. Results of optimization indicated that well dispersed and spherical nanodroplets were formed in the nanoemulsions with minimum particle size (76 nm) and polydispersity index (PDI, 0.358) and maximum zeta potential value (−8.01 mV), using garlic oil nanoemulsion amount of 8.27 mL and 4.15 g of astaxanthin powder. Strong antioxidant activity (>100%) of the prepared astaxanthin–garlic oil nanoemulsion, using obtained optimum amounts of the components, could be related to the highest antioxidant activity of the colloidal astaxanthin (>100%) as compared to that of the garlic oil nanoemulsion (16.4%). However, higher bactericidal activity of the resulted nanoemulsion against Escherichia coli and Staphylococcus aureus, were related to the main sulfur bioactive components of the garlic oil in which their main functional groups were detected by Fourier transform-infrared spectroscopy.

Predicting Seepage of Earth Dams Using Neural Network and Genetic Algorithm

2011 ◽  
Vol 403-408 ◽  
pp. 3081-3085 ◽  
Author(s):  
Xin Ying Miao ◽  
Jin Kui Chu ◽  
Jing Qiao ◽  
Ling Han Zhang
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Field Data ◽  
Back Propagation ◽  
Earth Dam ◽  
Earth Dams ◽  
Gradient Descent Algorithm ◽  
Levenberg Marquardt ◽  
Lm Algorithm ◽  
Good Agreement

Measurements of seepage are fundamental for earth dam surveillance. However, it is difficult to establish an effective and practical dam seepage prediction model due to the nonlinearity between seepage and its influencing factors. Genetic Algorithm for Levenberg-Marquardt(GA-LM), a new neural network(NN) model has been developed for predicting the seepage of an earth dam in China using 381 databases of field data (of which 366 in 2008 were used for training and 15 in 2009 for testing). Genetic algorithm(GA) is an ecological system algorithm, which was adopted to optimize the NN structure. Levenberg-Marquardt (LM) algorithm was originally designed to serve as an intermediate optimization algorithm between the Gauss-Newton(GN) method and the gradient descent algorithm, which was used to train NN. The predicted seepage values using GA-LM model are in good agreement with the field data. It is demonstrated here that the model is capable of predicting the seepage of earth dams accurately. The performance of GA-LM has been compared with that of conventional Back-Propagation(BP) algorithm and LM algorithm with trial-and-error approach. The comparison indicates that the GA-LM model can offer stronger and better performance than conventional NNs when used as a quick interpolation and extrapolation tool.

scholarly journals Optimized Placement of Connecting the Distributed Generationswork Stand Alone to Improve the Distribution Systems Reliability

2013 ◽  
Vol 64 (2) ◽  
pp. 76-83
Author(s):  
Hamed Hashemi-Dezaki ◽  
Ali Agheli ◽  
Behrooz Vahidi ◽  
Hossein Askarian-Abyaneh
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
System Reliability ◽  
Distribution Systems ◽  
Analytical Approach ◽  
Distributed Generations ◽  
Joint Point ◽  
Cost Of Energy ◽  
Optimum Solution ◽  
The Cost

The use of distributed generations (DGs) in distribution systems has been common in recent years. Some DGs work stand alone and it is possible to improve the system reliability by connecting these DGs to system. The joint point of DGs is an important parameter in the system designing. In this paper, a novel methodology is proposed to find the optimum solution in order to make a proper decision about DGs connection. In the proposed method, a novel objective function is introduced which includes the cost of connector lines between DGs and network and the cost of energy not supplied (CENS) savings. Furthermore, an analytical approach is used to calculate the CENS decrement. To solve the introduced nonlinear optimization programming, the genetic algorithm (GA) is used. The proposed method is applied to a realistic 183-bus system of Tehran Regional Electrical Company (TREC). The results illustrate the effectiveness of the method to improve the system reliability by connecting the DGs work stand alone in proper placements.

scholarly journals Theoretical and Experimental Evaluation of Particle size Effect of Iron , Cobalt ,and Nickel Powders Suspended in Al Dura oil on XRF Intensities

2007 ◽  
Vol 4 (3) ◽  
pp. 475-481
Author(s):  
Baghdad Science Journal
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Laser System ◽  
Particle Size Effect ◽  
Particle Sizes ◽  
Iron Cobalt ◽  
X Ray ◽  
Nickel Powders ◽  
Good Agreement ◽  
Cobalt And Nickel

Iron , Cobalt , and Nickel powders with different particle sizes were subjected to sieving and He-Ne laser system to determine the particle size . 1wt% from each powders was blended carefully with 99wt% from Iraqi oil . Microscopic examination were carried for all samples to reveal the particle size distribution . A Siemens type SRS sequential wavelength dispersive(WDS) X-ray spectrometer was used to analyze all samples , and the XRF intensity were determined experimentally and theoretically for all suspended samples , Good agreement between theoretical and experimental results were found .

scholarly journals Optimasi Pemilihan Barang Dagangan bagi Pedagang Keliling dengan Algoritma Genetika

2017 ◽  
Vol 3 (1) ◽  
Author(s):  
Iryanto Iryanto ◽  
Eka Ismantohadi
Keyword(s):  
Genetic Algorithm ◽  
Analytical Solution ◽  
Maximum Capacity ◽  
The Right ◽  
Good Agreement

Existence of constraints increases difficulty in choosing the right goods for a seller. Indeed, the seller wants to optimize the profit gained. Due to limitation of capital and maximum capacity, the seller needs a certain strategy to do the selection. Moreover the fact that each goods has its own probability to sell makes the problem becomes more complex. In this paper, the problem is solved using genetic algorithm. The result of simulation is in a good agreement with analytical solution. The simulation of N-goods selection is also given in the paper. 

Preparation of High Density BaZr0.97Y0.03O3-δ Ceramic and its Interaction with Titanium Melt

2018 ◽  
Vol 768 ◽  
pp. 261-266 ◽  
Author(s):  
Ju Yun Kang ◽  
Guang Yao Chen ◽  
Bao Tong Li ◽  
Zi Wei Qin ◽  
Xiong Gang Lu ◽  
...  
Keyword(s):  
Particle Size ◽  
Ball Milling ◽  
Milling Time ◽  
Sintered Pellet ◽  
Conventional Solid State Reaction ◽  
Industrial Grade ◽  
Minimum Particle Size ◽  
Ni Alloy ◽  
Improved Stability ◽  
Ball Milling Time

In this paper, the BaZrO3(BZ) and BaZr0.97Y0.03O3-δ(BZY3) powders were prepared by using the industrial grade BaCO3, ZrO2and Y2O3powders combining the conventional solid state reaction. The BaZrO3(BZ) and BaZr0.97Y0.03O3-δ(BZY3) ceramics were fabricated at 1750°C. The effect of ball milling time and sintering aid (TiO2) on the sinterability of BaZr0.97Y0.03O3-δ(BZY3) ceramics were investigated, and the improved stability of BaZrO3refractory with Y2O3additive were studied according to the refractory-metal interaction. The results revealed that the particle size of BZY3 powders decreased first and then increased with the increasing of ball milling time from 6h to 12h, and the minimum particle size was only 2.252μm at 8h. When 2wt.%TiO2was added, the sintered pellet of BZY3 was the most densest and the relative density was above 95%. After melting the Ti2Ni alloy on the BZY and BZ ceramics, the thickness erosion layer of BaZrO3and BZY3refractories and Ti2Ni alloy is approximately 50μm and 20μm respectively, showing that BZY3 was more stable than BaZrO3refractory.

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