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Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Optimization of neural network architecture using genetic algorithm for load forecasting by Islam, B.U., Baharudin, Z., Raza, M.Q., Nallagownden, P.

“…In this paper, a computational intelligent technique genetic algorithm (GA) is implemented for the optimization of artificial neural network (ANN) architecture. …”
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Algorithm in the fluidized-bed reactor for the polymerization of propylene by Zanil, Mohd Fauzi, Chan, K.O., Hussain, Mohd Azlan

“…A modified artificial bee optimization is proposed in this study. The algorithm is based on the colony behavior of certain bee species to achieve optimal solution in the bounded environment. …”
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Optimal cost benefit of the EToU electricity tariff for a manufacturing operation by using optimization algorithm by Sulaima, Mohamad Fani, Alias, Nur Umirah, Wan Abdul Razak, Intan Azmira, Sardi, Junainah, Bohari, Zul Hasrizal

“…Optimization algorithm namely Ant Colony Optimization (ACO) is implemented and cases with and without implementation of algorithm are compared in order to idealize the load profile of DSM strategy. …”
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Numerical optimization of elevated thin reinforced concrete shell structures subjected to extreme loading / Azizah Abdul Nassir by Abdul Nassir, Azizah

“…The shape optimization process involves minimizing the maximum displacement using the gradient descent algorithm. …”
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Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar by Anuar, Norhasnelly

“…Hence they need the knowledge of load profile to help them choose their electricity supplier. …”
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Sliding mode controller optimization-based three-phase rectifier: review study by Mahmood, Omar Talal, Wan Hasan, Wan Zuha, Ismail, Luthffi Idzhar, Ramli, Hafiz Rashidi Harun

“…This paper discusses the optimization parameters of SMC and stability and load fluctuation in the rectifier system. …”
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Simultaneous load management strategy for electronic manufacturing facilities by using epso algorithm / M.F. Sulaima … [et al.] by Sulaima, M.F., Dahlan, N.Y., Bohari,, Z.H., Nasir, M.N.M., Mustafa, R.F., Duc, Luong Nguyen

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Simultaneous load management strategy for electronic manufacturing facilities by using EPSO algorithm by Sulaima, Mohamad Fani, Dahlan, Nofri Yenita, Bohari, Zul Hasrizal, Mohd Nasir, Mohamad Na'im, Mustafa, R.F., Nguyen, Duc Luong

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Chaotic mutation immune evolutionary programming for photovoltaic planning in power system / Sharifah Azma Syed Mustaffa by Syed Mustaffa, Sharifah Azma

“…Therefore, the installation of PV requires optimization process to identify the correct location and sizing. …”
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Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction by Jinmei Shi, Yu-Beng Leau, Kun Li, Huandong Chen

“…Also, it does not easily fall into local optima. The evolutionary algorithm can be used to optimize the number of its hidden layer nodes. …”
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Non-Intrusive Electrical Load Monitoring and Identification: Approaches, Tools and a Case Study by Elixie A.E., Alkahtani A.A., Alkawsi G., Salle S.F., Fazea Y., Ekanayake J.

“…This paper adopts a non-intrusive load monitoring algorithm (NILM) to assist in generating a recommender system based on smart meter data. …”

Optimizing Neural Network Prediction of Composite Fatigue Life Under Variable Amplitude Loading Using Bayesian Regularization by Megat-Yusoff, Puteri Sri Melor

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Using ideal time horizon for energy cost determination by Hasan, Raed Abdulkareem, Abdulwahid, Hadeel W., Abdalzahra, Arwa Sahib

“…In most optimal VM placement algorithms, the first step to determine the proper time horizon, T for the prediction of the expected maximum future load, L. …”
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Raziq, Muhamad Aiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

“…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Muhamad Aiman Raziq, Muhamad Aiman Raziq, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

“…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Raziq, MuhamadAiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

“…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural networkbwith open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, H. P. Manurung, Yupiter, Raziq, Muhamad Aiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon6 & Vladimir S. Kachinskyi, John R. C. Dizon6 & Vladimir S. Kachinskyi

“…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by SuhailaAbd Halim, SuhailaAbd Halim, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Raziq, Muhamad Aiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinsky, Vladimir S. Kachinsky

“…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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