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

Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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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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Sensitivity analysis and optimization of a cardiovascular lumped parameter model for patient-specific modelling by Siti Munirah, Muhammad Ali, El-Bouri, Wahbi, Wan Naimah, Wan Ab Naim, Mohd Jamil, Mohamed Mokhtarudin

“…Four key parameters were identified as the most influential and subsequently optimized. Model outputs, specifically mean arterial pressure (MAP), were validated against clinical values from a public database. …”
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Modeling And Optimization Of Physical Vapour Deposition Coating Process Parameters For Tin Grain Size Using Combined Genetic Algorithms With Response Surface Methodology by Mohamad Jaya, Abdul Syukor, Muhamad, Mohd Razali, Abd Rahman, Md Nizam, Mohammad Jarrah, Mu'ath Ibrahim, Hasan Basari, Abd Samad

“…Optimization of thin film coating parameters is important in identifying the required output.Two main issues of the process of physical vapor deposition (PVD) are manufacturing costs and customization of cutting tool properties.The aim of this study is to identify optimal PVD coating process parameters.Three process parameters were selected, namely nitrogen gas pressure (N2),argon gas pressure (Ar),and Turntable Speed (TT),while thin film grain size of titanium nitrite (TiN) was selected as an output response.Coating grain size was characterized using Atomic Force Microscopy (AFM) equipment.In this paper,to obtain a proper output result,an approach in modeling surface grain size of Titanium Nitrite (TiN)coating using Response Surface Method (RSM) has been implemented. …”
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Particle swarm optimization algorithm to enhance the roughness of thin film in tin coatings by Jamil Alsayaydeh, Jamil Abedalrahim, Zainon, Maslan, Mohammad Alshannaq, Osama Saleh, Hammouda, Montaser B A, Ali, Mohanad Faeq, Alkhashaab, Mohammed Abdul Razaq, Mohamad Jaya, Abdul Syukor

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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.

“…This study emphasizes on the performance evaluation of given algorithms and their pitfalls in predicting accurate pressure drop. …”
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Intelligence Integration Of Particle Swarm Optimization And Physical Vapour Deposition For Tin Grain Size Coating Process Parameters by Abdul Syukor, Mohamad Jaya, Mu*ath Ibrahim, Mohammad Jarrah, Mohd Asyadi Azam, Mohd Abid, Mohd Razali, Muhamad

“…Optimization of thin film coating parameters is important in identifying the required output.Two main issues of the process of physical vapor deposition (PVD) are manufacturing costs and customization of cutting tool properties.The aim of this study is to identify optimal PVD coating process parameters.Three process parameters were selected,namely nitrogen gas pressure (N2),argon gas pressure (Ar),and Turntable Speed (TT),while thin film grain size of titanium nitrite (TiN) was selected as an output response.Coating grain size was characterized using Atomic Force Microscopy (AFM) equipment.In this paper,to obtain a proper output result,an approach in modeling surface grain size of Titanium Nitrite (TiN)coating using Response Surface Method (RSM) has been implemented. …”
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Application of Evolutionary Algorithm for Assisted History Matching by Zahari, Muhammad Izzat

“…Today, tremendous efforts are made to develop Automatic History Matching algorithms. While the automatic method focus on optimization which is normally computer based. …”
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Development of cost reduction mathematical model for natural gas transmission network system by Mehrdad, Nikbakht Eliaderany

“…Therefore, the data clearly exhibit that the proposed method provides a solution that was nearer to an optimized network.…”
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Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network by Sivarao, Subramonian

“…The model was then fed with new sets of machining parameters to experimentally validate the model’s ability in predicting the cut quality. …”
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Fuzzy-Genetic based approach in decision making for repair of turbochargers using additive manufacturing by Hiyam Adil Habeeb, Dzuraidah Abd Wahab, Abdul Hadi Azman, Mohd Rizal Alkahari

“…Genetic algorithm optimization method was used to optimize the cost of the repairing process once the decision on whether the turbocharger was repairable was determined by the Fuzzy system. …”
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AI-enhanced generative design for efficient heat exchangers in thermoelectric generators: revolutionizing waste heat recovery in thermoelectricity / Andrew Robert Martin Hughes ...... by Andrew, Robert Martin Hughes, Bhathal Singh, Baljit Singh, Remeli, Muhammad Fairuz, Peixer, Guilherme Fidelis, Ratan Singh, Wandeep Kaur

“…This study addresses these challenges by using NSGA-II, combined with a semi-empirical model, to optimize PFHE design in TEG systems. The optimization focuses on refining fin design parameters such as number, width, and height while adhering to constraints on fin area and pressure drop.…”
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PREDICTIVE MAXIMUM POWER POINT TRACKING (MPPT) ALGORITHM FOR PERMANENT EXCHANGE MEMBRANE FUEL CELL (PEMFC) by MOHD RIZZWAN, MINGGU

“…Generally, the output characteristics of fuel cells are non-linear and influenced by parameters such as the cell temperature, oxygen partial pressure, hydrogen partial pressure, and membrane water content. …”
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Development of optimized maintenance scheduling model for coal-fired power plant boiler by Noor Fazreen Binti Ahmad Fuzi, Ms.

“…Literature revealed that mathematical methods and metaheuristic algorithms are common approaches in solving combinatorial optimization problems with a large search space in a reasonable computational run time. …”

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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Wearables-assisted smart health monitoring for sleep quality prediction using optimal deep learning by Hamza, Manar Ahmed, Hassan Abdalla Hashim, Aisha, Alsolai, Hadeel, Gaddah, Abdulbaset, Othman, Mahmoud, Yaseen, Ishfaq, Rizwanullah, Mohammed, Zamani, Abu Sarwar

“…For sleep quality prediction, the WSHMSQP-ODL model uses the deep belief network (DBN) model. To enhance the sleep quality prediction performance of the DBN model, the enhanced seagull optimization (ESGO) algorithm is used for hyperparameter tuning. …”
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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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Multivariate Based Analysis of Methane Adsorption Correlated to Toc and Mineralogy Impact from Different Shale Fabrics by Irfan, S.A., Azli, N.M., Abdulkareem, F.A., Padmanabhan, E.

“…The SVR methods utilize the iteration approach to sequential minimal optimization. …”
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Modelling of cupping suction system based on system identification method by Suresh, Kavindran, Ghazali, M. R., Ahmad, M. A.

“…The detection of cupped suction system plants using a standard model based on a modified Sine Cosine Algorithm (mSCA) is presented in this research. …”
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