Search Results - (( loading optimization method algorithm ) OR ( based prediction method algorithm ))

Optimization of stiffened panel fatigue life by using finite element analysis by Mazlan, Shahan

“…The multi-objective genetic algorithm which selects the design points based on Pareto optimal design combined with the adaptive multi-objective algorithm method which uses an optimal space-filling was shown to be efficient for time limitation and budget. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

“…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH by Norhafidzah, Mohd Saad

“…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River by Katipo?lu O.M., Kartal V., Pande C.B.

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Electricity Anomaly Point Detection using Unsupervised Technique Based on Electricity Load Prediction Derived from Long Short-Term Memory by Salleh N.S.M., Saripuddin M., Suliman A., Jorgensen B.N.

Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm by Abd Rahman, Mohd Shahrizan, Jamaludin, Nor Azliana Akmal, Zainol, Zuraini, Tengku Sembok, Tengku Mohd

“…The study employs a hybrid predictive model that combines Big Data technologies, Extract Load Transfer (ELT) processes, rule-based algorithms (RBA), machine learning (ML), and Power BI visualizations. …”
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Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks by Islam, B., Baharudin, Z., Nallagownden, P.

“…A hybrid approach that combines ANN and an evolutionary optimization technique, genetic algorithm (GA) is used for the development of a short term load forecast (STLF) model. …”
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Machine learning in botda fibre sensor for distributed temperature measurement by Nur Dalilla binti Nordin

“…An alternative method is proposed, utilizing machine learning algorithms. …”

RLF and TS fuzzy model identification of indoor thermal comfort based on PMV/PPD by Homod R.Z., Mohamed Sahari K.S., Almurib H.A.F., Nagi F.H.

“…This modeling is achieved using a Takagi-Sugeno (TS) fuzzy model and tuned by Gauss-Newton method for nonlinear regression (GNMNR) algorithm. …”

Enhancing unity-based AR with optimal lossless compression for digital twin assets by Hlayel, Mohammed, Hairulnizam, Mahdin, Hayajneh, Mohammad, AlDaajeh, Saleh H., Siti Salwani, Yaacob, Mazidah, Mat Rejab

“…Experimental results show a detailed comparison among these compression algorithms, which can give insights and help choose the best method according to the compression ratio, decompression speed, and resource usage. …”
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Predictive Functional Control With Reduced-Order Observer Design Using Particle Swarm Optimization For Pneumatic System by Abd Rahman, Azira

“…An optimization technique will be implemented in this project using Particle Swarm Optimization (PSO) algorithm. …”
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Carbon dioxide reforming of methane over Ni-based catalysts: Modeling the effect of process parameters on greenhouse gasses conversion using supervised machine learning algorithms by Ayodele B.V., Alsaffar M.A., Mustapa S.I., Kanthasamy R., Wongsakulphasatch S., Cheng C.K.

Analysis of model predictive control-based energy management system performance to enhance energy transmission by Chowdhury, Israth Jahan, Yusoff, Siti Hajar, Gunawan, Teddy Surya, Ahmad Zabidi, Suriza, Abu Hanifah, Mohd Shahrin, Mohd Sapihie, Siti Nadiah, Pranggono, Bernardi

“…A two-layer Economic Model Predictive Control (EMPC) framework has been developed and has improved results such as cost reductions compared to recent advanced methods. …”
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Modified strut-and-tie models for reinforced concrete deep beams with externally bonded CFRP systems by Hanoon, Ammar Nasiri

“…The STM is an effective shear design method based on the lower-bound plasticity theorem. …”
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Crack simulation for the cover of the landfill – A seismic design by Namdar, Abdoullah, Omer, Mughieda, Filippo, Berto, Nurmunira, Muhammad

“…Artificial Neural Networks (ANNs) based on Levenberg-Marquardt Algorithm and Abalone Rings Data Set mode were used to predict displacement in critical points of the model. …”
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Prediction accuracy improvement for Bitcoin market prices based on symmetric volatility information using artificial neural network approach by Othman, Anwar Hasan Abdullah, Kassim, Salina, Rosman, Romzie, Redzuan, Nur Harena

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Specific heat capacity extraction of soybean oil/mxene nanofluids using optimized long short-term memory by Qazani, Mohammad Reza Chalak, Aslfattahi, Navid, Kulish, Vladimir Vladimirovich, Asadi, Houshyar, Schmirler, Michal, Zakarya, Muhammad, Alizadehsani, Roohallah, Haleem, Muhammad, Kadirgama, Kumaran

“…In addition, the Bayesian optimization technique is employed to calculate the optimal hyperparameters of the developed SVR, GMDH, MLP and LSTM to reach the highest efficiency of the system in predicting the cpNF based on temperature and nanoflakes concentration. …”
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Optimal planning and design of hybrid renewable energy system for rural healthcare facilities / Olatomiwa Lanre Joseph by Olatomiwa Lanre , Joseph

“…Followed by development of prediction algorithm for solar radiation using soft-computing methodologies. …”
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Model predictive control based on Lyapunov function and near state vector selection of four-leg inverter / Abdul Mannan Dadu by Abdul Mannan, Dadu

“…The computational burden of C-MPC is expensive due to utilize all available voltage vectors of a power inverter to predict the future behavior of the system. This dissertation has focused on Lyapunov model predictive control (L-MPC) methods, in which Lyapunov control law is employed in the cost function to minimize the error between the desired control variables and the actual control variables of a three-phase four-leg inverter to optimize closed-loop system performance. …”
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Driver behaviour classification: a research using OBD-II data and machine learning by Muhamad Fadzil, Nur Farisya Aqilah, Mohd Fadzir, Hilda, Mansor, Hafizah, Rahardja, Untung

“…Hence, using On-board Diagnostic-II (OBD-II) data by categorising drivers based on their driving behaviour can be an efficient method. …”
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