Search Results - (( using optimization model algorithm ) OR ( variable active learning algorithm ))

Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations by Hossain, S.K.S., Ayodele, B.V., Alhulaybi, Z.A., Alwi, M.M.A.

“…Similarly, the model performance was also influenced by the nature of the optimization algorithms. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

“…In recent years soft computing methods like fuzzy logic and genetic algorithm are being used in modeling complex processes of hydrologic events. …”
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Short-Term forecasting of floating photovoltaic power generation using machine learning models by Mohd Herwan, Sulaiman, Mohd Shawal, Jadin, Zuriani, Mustaffa, Mohd Nurulakla, Mohd Azlan, Hamdan, Daniyal

“…The results indicate that the Neural Networks model consistently outperforms the other machine learning algorithms in terms of predictive accuracy. …”
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Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail by Sh. Ismail, Faridah

“…Back-propagation algorithm is a training method widely used in a multilayer perceptron Neural Network model. …”
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Artificial Neural Network-Forecasted Compression Strength of Alkaline-Activated Slag Concretes by Yi, Xuan Tang, Yeong, Huei Lee, Mugahed, Amran, Roman, Fediuk, Nikolai, Vatin, Beng, Ahmad Hong Kueh, Yee, Yong Lee

“…The prediction accuracy of the optimal ANN model was then compared to existing ANN-based models, while the variable selection was compared to existing AASC models with other machine learning algorithms, due to limitations in the ANN-based model. …”
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Artificial Neural Network Algorithms to Predict the Compressive Strength of Fly Ash-Based Geopolymers by Siaw Hui, Teo

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Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis by Adnani, Seyedeh Atena

“…In this system,similar insolvent system, three methods including one variable at a time, Taguchi method and ANN were used for optimization and prediction of percentage of conversion. …”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

“…Instead of solving the original optimal control problem, the model-based optimal control problem is solved. …”
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques by Lipu M.S.H., Hussain A., Saad M.H.M., Hannan M.A.

Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm by Rosmazi, Rosli, Zamri, Mohamed

“…This article presents a new modified cuckoo search algorithm with dynamic discovery probability and step-size factor for optimizing the Bouc–Wen Model in magnetorheological damper application. …”
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Application of conjugate gradient approach for nonlinear optimal control problem with model-reality differences by Leong, Wah June, Sie, Long Kek, Teo, Kok Lay, Sim, Sy Yi

“…In our approach, the linear quadratic optimal control model, which is adding the adjusted parameters into the model used, is employed. …”
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Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari by Mohammed , Heydari

“…An improved particle swarm algorithm (HPSOGA) is used to solve complex problems of water resources optimization. …”
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Modeling and optimization of multi-holes drilling path using Particle Swarm Optimization by Ab Rashid, Mohd Fadzil Faisae, Nik Mohamed, Nik Mohd Zuki, Romlay, Fadhlur Rahman Mohd, Razali, Akhtar Razul, Asmizam, Mokhtar

“…Later the problem is optimized using Particle Swarm Optimization (PSO) and compared with other algorithms including the new metaheuristics algorithms. …”
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Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference by Sie, Long Kek, Wah, June Leong, Sy, Yi Sim, Kok, Lay Teo

“…In our approach, the linear quadratic optimal control model, which is adding the adjusted parameters into the model used, is employed. …”
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Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin by Mohd Yassin, Ahmad Ihsan

“…This thesis proposes the application of a stochastic optimization algorithm called Binary Particle Swarm Optimization algorithm for structure selection of polynomial NARX/NARMA/NARMAX models. …”
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Comparison between multi-objective and single-objective optimization for the modeling of dynamic systems by Mohd Zakimi, Zakaria, Hishamuddin, Jamaluddin, Robiah, Ahmad, Sayed Mohammad Reza, Loghmanian

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Optimization of assembly line balancing with energy efficiency by using tiki-taka algorithm by Ariff Nijay, Ramli

“…This research aimed to establish a computational model that represents the ALB-EE, propose a new Tiki-Taka Algorithm (TTA) to solve and optimize the ALB-EE and validate the developed model through a real-life case study. …”
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Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models by Gholami M., Ghanbari-Adivi E., Ehteram M., Singh V.P., Najah Ahmed A., Mosavi A., El-Shafie A.

“…The honey badger optimization algorithm (HBOA), salp swarm algorithm (SASA), firefly algorithm (FIFA), and particle swarm optimization algorithm (PASOA) are used to adjust the MULP parameters. …”