Search Results - (( model extraction method algorithm ) OR ( simulation optimization based algorithm ))

Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

“…However, the developed algorithms only consider the selected features from a peak model based on the understanding of the EEG signals characteristics. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Binary Artificial Bee Colony Optimization For Weighted Random 2 Satisfiability In Discrete Hopfield Neural Network by Muhammad Sidik, Siti Syatirah

“…This proposed model will be employed in the Improved Reverse Analysis method to extract the relationship between various fields of real-life data sets based on logical representation. …”
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Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Ramarao, Taj, Mohammed Baloch

“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Rama Rao

“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

“…Stereo vision sensor can provide color and texture information for easy data and feature extraction. Based on literature, stereo algorithm is already being implemented to solve the distance measurement problem. …”
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Active vibration control of a flexible beam structure using chaotic fractal search algorithm by Tuan Abdul Rahman, Tuan Ahmad Zahidi, As'arry, Azizan, Abdul Jalil, Nawal Aswan

“…In conclusion, the simulation study indicates that the CFS algorithm possess capability to extract an adequate and stable model of the flexible beam structure, hence a better performance of control strategy can be achieved.…”
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Autoreclosure in extra high voltage lines using taguchi's method and optimized neural networks by K.S.R, Rao, F. D., Zahlay

“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi's Method. …”
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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

“…The proposed approach can be furthered categorized into two distinct stages: forecasting modeling and optimization modeling. Artificial neural network (ANN) has been widely used in forecasting tasks. …”
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Logic Mining Approach: Shoppers’ Purchasing Data Extraction via Evolutionary Algorithm by Mohd Kasihmuddin, Mohd Shareduwan, Abdul Halim, Nur Shahira, Mohd Jamaludin, Siti Zulaikha, Mansor, Mohd. Asyraf, Alway, Alyaa, Zamri, Nur Ezlin, Azhar, Siti Aishah, Marsani, Muhammad Fadhil

“…In reducing the learning complexity, a genetic algorithm was implemented to optimize the logical rule throughout the learning phase in performing a 2-satisfiability-based reverse analysis method, implemented during the learning phase as this method was compared. …”
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Vehicle detection for vision-based intelligent transportation systems using convolutional neural network algorithm by Khalifa, Othman Omran, Wajdi, Muhammad H., Saeed, Rashid A., Hassan Abdalla Hashim, Aisha, Ahmed, Muhammed Z., Ali, Elmustafa Sayed

“…Results from the simulated and evaluated algorithm showed that the proposed model was able to achieve a mAP of 97.8 in the daytime dataset and 95.1 in the nighttime dataset.…”
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Parameter extraction of solar photovoltaic modules using penalty-based differential evolution by Ishaque, K., Salam, Z., Mekhilef, Saad, Shamsudin, A.

“…The analyses carried out using synthetic current-voltage (I-V) data set showed that the proposed P-DE outperforms other Evolutionary Algorithm methods, namely the simulated annealing (SA), genetic algorithm (GA), and particle swarm optimization (PSO). …”
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Zero root-mean-square error for single- and double-diode photovoltaic models parameter determination by Mohammed Ridha, Hussein, Hizam, Hashim, Mirjalili, Seyedali, Othman, Mohammad Lutfi, Ya’acob, Mohammad Effendy

“…In this work, a new improved arithmetic optimization method based on the adaption of Newton–Raphson and Levenberg–Marquardt damping parameter (IAOANRaLMp) is presented to globally extract the parameter of the single- and double-diode PV models. …”
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JOINT TORQUEESTIMATION OF sEMG SIGNALS BASED ON INTELLIGENT TECHNIQUES FOR ROBOTIC ASSISTIVE SYSTEM by KU ABD RAHIM, KU NURHANIM

“…Subsequently, the signal processing that involved processes such as filtering and feature extraction was conducted. Thereafter, the actual joint torque was acquired through dynamic modeling. …”
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The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

“…It was demonstrated from the simulation investigation that the CWT model could yield a better signal transformation amongst the preprocessing algorithms. …”
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Obso based fractional pid for mppt-pitch control of wind turbine systems by Mehedi, I.M., Al-Saggaf, U.M., Vellingiri, M.T., Milyani, A.H., Saad, N.B., Yahaya, N.Z.B.

“…The simulation outcomes ensured the promising characteristics of the proposed model over the other methods. …”
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Modelling of Liquid-liquid Equilibrium Behaviour of Aqueous Two-Phase Polymer Mixture System for Protein Extraction by Ahmad, Murni M

“…We briefly discuss some issues involved in solving for the LLE compositions and present methods and steps taken to achieve robust, accurate and reliable simulations. We solve the minimization problem using the modified Shor's R-algorithm for non-smooth optimization [3,4]. …”
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Enhancing land cover classification in remote sensing imagery using an optimal deep learning model by Motwake, Abdelwahed, Hassan Abdalla Hashim, Aisha, Obayya, Marwa, Eltahir, Majdy M.

“…hyperparameter selection is accomplished with the help of the Reptile Search Algorithm (RSA). The simulation analysis was conducted upon the ISCSODL-LCC model using two benchmark datasets and the results established the superior performance of the proposed model. …”
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AQUEOUS TWO-PHASE POLYMER MIXTURE SYSTEM AS PROTEIN XTRACTION TECHNIQUE. MODELLING OF PROTEIN PARTITIONING BEHAVIOR by Ahmad, Murni M

“…A Gibbs energy of mixing minimization approach is presented to calculate the liquid-liquid equilibrium behaviour and protein partitioning behaviour in the polymer-mixture ATPES that is based on Flory-Huggins polymer theory. The minimization problem is solved using the modified Shor's R-algorithm for non-smooth optimization. …”
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