Search Results - (( using composition using algorithm ) OR ( parameter optimization model algorithm ))

Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization by Lee, Jesee Kar Ming

“…The ANN model is further improved using GA and PSO. Each algorithm has its own parameters and is further optimized using RSM. …”
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A hybrid numerical approach for multi-responses optimization of process parameters and catalyst compositions in CO2 OCM process over CaO-MnO/CeO2 catalyst by Istadi, Istadi, Saidina Amin, Nor Aishah

“…The optimization was aimed to obtain optimal process parameters and catalyst compositions with high catalytic performances. …”
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques by Hammid, Ali Thaeer

“…Secondly, this approach hybridizing the FA with the rough algorithm (RA), where RA is used to control the steps of randomness for the FA while optimizing the weights of the standard BPNN model. …”
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Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms by Fard Masoumi, Hamid Reza

“…All process parameters are selected to conduct the optimization by using some statistical algorithms such as Artificial Neural networks (ANNs), Response Surface Methodology (RSM), Wavelet Neural Network (WNN) and Partial Least Squares (PLS). …”
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Application of response surface methodology coupled with genetic algorithm in the optimization of cutting conditions for surface roughness in end-milling of Inconel 718 using coate... by Ishtiyaq, M. H., Amin, A. K. M. Nurul, Karim, A.N. Mustafizul, Ginta, Turnad Lenggo, Patwari, Muhammed Anayet Ullah

“…RSM has been utilized to develop an efficient mathematical model for surface roughness in terms of cutting parameters. …”
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Machinability performance of Al–NiTi and Al–NiTi–nano SiC composites with parametric optimization using GSA by Mokkandi, Purusothaman, Jayamani, Manivannan, Sekarbabu, Balakiruthiha, Kadambarajan, Jeya Prakash, Nagarajan, Rajini, Hameed Sultan, Mohamed Thariq, Shanmugavel, Rajesh

“…Regression model is used to develop the surface roughness and kerf angle model for Al–NiTi and Al–NiTi–nano SiC composites. …”
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Decentralized Adaptive Pi With Adaptive Interaction Algorithm Of Wastewater Treatment Plant by Rahmat, Mohd Fua'ad, Rahmat, Mohd Fuaad, Abdul Wahab, Norhaliza, Che Razali, Mashitah, Gaya, Muhammad Sani, Samsudin, Sharatul Izah

“…The Pi controller parameters are obtained by using simple updating algorithm developed based on adaptive interaction theory. …”
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Multi-Objective Optimization of Minimum Quantity Lubrication in end Milling of Aluminum Alloy AA6061T6 by Najiha, M. S., M. M., Rahman, K., Kadirgama, M. M., Noor, D., Ramasamy

“…Response surface methodology coupled with a central composite design of experiments is used for modeling. …”
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Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool by Samuel Simbine, Augusto

“…This final year project identified relevant parameters through literature research, analysis and expert interview, and evaluated different machine learning algorithms and identified linear regression as the most applicable and efficient with its R-square of 0.8015, qualifying it to be used for the development of a hybrid model for the AI-based tool for predictive process optimization for chemical plants.…”
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Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

Composite nonlinear feedback control with multi-objective particle swarm optimization for active front steering system by Ramli L., Sam Y.M., Mohamed Z., Khairi Aripin M., Fahezal Ismail M.

Experimental Investigation and Optimization of Minimum Quantity Lubrication for Machining of AA6061-T6 by Najihah, Mohamed, M. M., Rahman, K., Kadirgama

“…Optimization is performed using a genetic algorithm and the optimized designs are obtained in the form of Pareto optimal designs. …”
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Hybrid scheme for the prediction of microstructural features of ferritic stainless steel welds by Amuda, Muhammed Olawale Hakeem, Mridha, Shahjahan

“…There is an increasing use of predictive tools in modeling microstructural features of welds towards eliminating weld defects and optimizing mechanical properties. …”
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Analysis of parallel flow type internally cooled membrane-based liquid desiccant dehumidifier using a neural networks approach by Quadros, Jaimon Dennis, Khan, Sher Afghan, T., Prashanth

“…Backpropagation algorithm (BP), artificial bee colony (ABC), and genetic algorithm (GA) models were used to train the neural network (NN) parameters using the data collected from the CCD-based response equation. …”
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Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer by Temitope T., Dele-Afolabi, Masoud, Ahmadipour, Mohamed Ariff, Azmah Hanim, A.A., Oyekanmi, M.N.M., Ansari, Sikiru, Surajudeen, Kumar, Niraj

“…An extreme learning machine (ELM) prediction approach refined by Aquila optimizer (AO), a new cutting-edge metaheuristic optimization algorithm was utilized to develop a prediction model for the performance assessment of the developed solder composites. …”
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Modeling of the end milling process for aluminum alloy AA6061T6 using hss tool by Najiha, M. S., M. M., Rahman, A. R., Yusoff

“…The resultant model is then tested for optimization using a genetic algorithm.…”
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Modeling of the End Milling Process for Aluminium Alloy AA6061T6 Using HSS Tool by Najiha, M. S., M. M., Rahman, A. R., Yusoff

“…The resultant model is then tested for optimization using genetic algorithm.…”
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Ozone Concentration Forecasting Based on Artificial Intelligence Techniques: A Systematic Review by Yafouz A., Ahmed A.N., Zaini N., El-Shafie A.

Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer by Dele-Afolabi T.T., Ahmadipour M., Azmah Hanim M.A., Oyekanmi A.A., Ansari M.N.M., Sikiru S., Kumar N.

“…An extreme learning machine (ELM) prediction approach refined by Aquila optimizer (AO), a new cutting-edge metaheuristic optimization algorithm was utilized to develop a prediction model for the performance assessment of the developed solder composites. …”

Tailoring the energy harvesting capacity of zinc selenide semiconductor nanomaterial through optical band gap modeling using genetically optimized intelligent method by Olubosede, Olusayo, Abd Rahman, Mohd Amiruddin, Alqahtani, Abdullah, Souiyah, Miloud, Latif, Mouftahou B., Oke, Wasiu Adeyemi, Aldhafferi, Nahier, Owolabi, Taoreed O.

“…This present work provides novel ways whereby the wide energy band gap of zinc selenide can be effectively modulated and tuned for light energy harvesting capacity enhancement by hybridizing a support vector regression algorithm (SVR) with a genetic algorithm (GA) for parameter combinatory optimization. …”
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