Search Results - (( pressure optimization method algorithm ) OR ( parameter evaluation model algorithm ))

Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation by Kumar, A., Ridha, S., Ganet, T., Vasant, P., Ilyas, S.U.

“…The impact of each input parameter affecting the pressure drop is quantified using the RF algorithm. …”
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Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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Modelling and calibration of high-pressure direct injection compressed natural gas engine by Mohd Fadzil, Abdul Rahim

“…An optimal Artificial Neural Network (ANN) model is required to facilitate model-based calibration (MBC) procedure. …”
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Artificial neural network and inverse solution method for assisted history matching of a reservoir model by Negash, B.M., Vel, A., Elraies, K.A.

“…This allows to directly simulate the trained neural network and avoid the use of objective function and optimization algorithm. The efficacy of the developed approach was evaluated using a benchmark reservoir model case study which was originally developed for investigation of three-phase three-dimensional Black-Oil modelling techniques under the 9th SPE comparative study project. …”
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Model-based hybrid variational level set method applied to object detection in grey scale images by Wang, Jing

“…To tackle the persistent challenge of segmenting grayscale images with both uneven characteristics and high noise levels, a hybrid level-set algorithm based on kernel metrics is introduced. This algorithm leverages an improved multi-scale mean filter to mitigate grayscale inhomogeneity while reducing the impact of scale parameter selection. …”
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Experimental and AI-driven enhancements in gas-phase photocatalytic CO2 conversion over synthesized highly ordered anodic TiO2 nanotubes by Hossen, Md. Arif, Hasan, Md. Munirul, Ahmed, Yunus, Azrina, Abd Aziz, Nurashikin, Yaacof, Leong, Kah Hon

“…Six popular ML algorithms of regression, kernel and neural network-based models were applied to predict the gas-phase CO2 photoconversion rate. …”
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Stochastic Modelling Of Bioethanol Fermentation By Saccharomyces Cerevisiae Grown In Oil Palm Residues by Samsudin , Mohd Dinie Muhaimin

“…Therefore, sensitivity analysis was then carried out in order to evaluate the influence of each kinetic model parameter on bioethanol yield. …”
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Chemometric approaches in the evaluation of trace metals in commercially raised tilapia and preliminary health risk assessment of its consumption / Low Kah Hin by Low, Kah Hin

“…The most significant microwave parameters were further evaluated by Box–Behnken design, while others were kept constant. …”
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Algorithm development for optimization of a refrigeration system by Izzat, Mohamad Adnan

“…This thesis deals with algorithm development for optimization of a refrigeration system. …”
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Metaheuristic Algorithm for Wellbore Trajectory Optimization by Biswas, K., Vasant, P.M., Vintaned, J.A.G., Watada, J.

“…In drilling engineering, the optimization of wellbore plays an important role, which can be optimized based on minimization of length, mud pressure, critical pressure, etc. …”
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Improvement and application of particle swarm optimization algorithm by Deevi, Durga Praveen, Kodadi, Sharadha, Allur, Naga Sushma, Dondapati, Koteswararao, Chetlapalli, Himabindu, Perumal, Thinagaran

“…Finally, real-world tests are performed to verify the proposed Algorithm's efficacy compared to existing optimization methods. …”
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Two level Differential Evolution algorithms for ARMA parameters estimatio by Salami, Momoh Jimoh Emiyoka, Tijani, Ismaila, Aibinu, Abiodun Musa

“…The performance of the algorithm is evaluated using both simulated ARMA models and practical rotary motion system. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…Not many researchers have investigated the effects of optimizing both the topology structures and the parameters used in ANNs. This research utilizes a genetic algorithm (GA) to optimize the multi-layer FFNN performance and structure in modelling three datasets: network traffic, rainfall, and tourist. …”
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Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market by Hazirah Halul

“…Therefore, this study focused to contribute on evaluating different algorithm models such as traditional ML and deep learning models with big stock data of multiple parameters from selected companies in Bursa Malaysia. …”

Numerical simulation of fluid flow in three dimensional domain based on two stage pressure-velocity correction method by Sabir, O., Ya, T.M.Y.S.T.

“…In this paper a two stage pressure-velocity correction approach for immersed boundary method is proposed. …”
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Numerical simulation of fluid flow in three dimensional domain based on two stage pressure-velocity correction method by Sabir, O., Ya, T.M.Y.S.T.

“…In this paper a two stage pressure-velocity correction approach for immersed boundary method is proposed. …”
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Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

“…The influence of conventional genetic algorithm parameter - generation gap has been investigated too. …”
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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

“…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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Thin Film Roughness Optimization In The Tin Coatings Using Genetic Algorithms by Fauzi, Nur Faiqah, Mohamad Jaya, Abdul Syukor, Mohammad Jarrah, Mu’ath Ibrahim, Akbar, Habibullah

“…In order to represent the process variables and coating roughness, a quadratic polynomial model equation was developed. Genetic algorithms were used in the optimization work of the coating process to optimize the coating roughness parameters. …”
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PID Tuning Of Process Plant Using Evolutionary Algorithm by Guong, Robert Ling Leh

“…In this project, Evolutionary algorithm (Particle Swarm Optimization) is implemented to optimize the controller parameters in order to improve the system performance of the real pressure plant. …”
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