Search Results - (( parameter optimization method algorithm ) OR ( parameter teaching learning algorithm ))

Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

“…To achieve this goal, an improved Teaching Learning-Based Optimization (ITLBO) algorithm was proposed in dealing with subset feature selection. …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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Optimization of balanced academic curriculum problem in educational institutions using teaching learning based optimization algorithm by Mohd Fadzil Faisae, Ab Rashid, Wasif, Ullah

“…This study aims to optimize BACP using the Teaching-Learning Based Optimization (TLBO) algorithm, addressing the limitations of existing approaches and providing an efficient framework for curriculum balancing. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

“…The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. …”
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Optimal power flow using a hybridization algorithm of arithmetic optimization and aquila optimizer by Ahmadipour, Masoud, Murtadha Othman, Muhammad, Bo, Rui, Sadegh Javadi, Mohammad, Mohammed Ridha, Hussein, Alrifaey, Moath

“…In this paper, a hybridization method based on Arithmetic optimization algorithm (AOA) and Aquila optimizer (AO) solver namely, the AO-AOA is applied to solve the Optimal Power Flow (OPF) problem to independently optimize generation fuel cost, power loss, emission, voltage deviation, and L index. …”
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Optimization-driven extreme learning machine for floating photovoltaic power prediction: A teaching learning-based approach by Mohd Redzuan, Ahmad, Nor Farizan, Zakaria, Mohd Shawal, Jadin, Mohd Herwan, Sulaiman

“…This study presents a novel Teaching–Learning-Based Optimization enhanced Extreme Learning Machine (TLBO-ELM) framework that achieves optimal parameter configuration without algorithmic tuning while maintaining computational efficiency for real-time deployment. …”
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A new teaching learning artificial bee colony based maximum power point tracking approach for assessing various parameters of photovoltaic system under different atmospheric condit... by Dokala Janandra, Krishna Kishore

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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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A simplified adaptive neuro-fuzzy inference system (ANFIS) controller trained by genetic algorithm to control nonlinear multi-input multi-output systems by Lutfy, Omar F., Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce

“…A real-coded genetic algorithm (GA) was utilized to optimize the premise and the consequent parameters of the ANFIS controller, instead of the hybrid learning methods that are widely used in the literature. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Performance analysis of distributed power flow controller with ultracapacitor for regulating the frequency deviations in restructured power system by Peddakapu, K., M. R., Mohamed, M. H., Sulaiman, Srinivasarao, P., Veerendra, A. S., Leung, P. K.

“…An innovative metaheuristic method called bat algorithm (BA) is used to ascertain the optimal gain parameters of the two degree of freedom (2DOF) controllers using an integral squared error (ISE) criteria. …”
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Utilizing the Kolmogorov-Arnold Networks for chiller energy consumption prediction in commercial building by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Muhammad Salihin, Saealal, Mohd Mawardi, Saari, Abu Zaharin, Ahmad

“…The methodology involves comparing KAN's performance with Artificial Neural Networks (NN) and a hybrid metaheuristic algorithm combined with deep learning, namely the Teaching-Learning-Based Optimization with Deep Learning (TLBO-DL). …”
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Utilizing the Kolmogorov-Arnold Networks for chiller energy consumption prediction in commercial building by Sulaiman, Mohd Herwan, Mustaffa, Zuriani, Saealal, Muhammad Salihin, Saari, Mohd Mawardi, Ahmad, Abu Zaharin

“…The methodology involves comparing KAN’s performance with Artificial Neural Networks (NN) and a hybrid metaheuristic algorithm combined with deep learning, namely the Teaching-Learning-Based Optimization with Deep Learning (TLBO-DL). …”
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Performance analysis of distributed power flow controller with ultra-capacitor for regulating the frequency deviations in restructured power system by Peddakapu, K., M. R., Mohamed, Mohd Herwan, Sulaiman, P., Srinivasarao, A. S., Veerendra, P. K., Leung

“…An innovative metaheuristic method called bat algorithm (BA) is used to ascertain the optimal gain parameters of the two degree of freedom (2DOF) controllers using an integral squared error (ISE) criteria. …”
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Cuckoo optimised 2DOF controllers for stabilising the frequency changes in restructured power system with wind-hydro units by Peddakapu, K., M. R., Mohamed, M. H., Sulaiman, Srinivasarao, P., Kishore, D. J. K., P. K., Leung

“…In this work, proportional-integral (PI), proportional-integral derivative (PID), and 2-degree of freedom PID (2-DOF-PID) controllers are proposed to stabilise the variations in the system parameters at distinct loading conditions. Different types of metaheuristic optimisation methods like teaching–learning-based optimisation (TLBO) and cuckoo search algorithms are suggested to acquire the optimal gain values of the proposed controllers. …”
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Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

“…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
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Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization by Nur Iffah, Mohamed Azmi

“…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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Optimization of turning parameters using ant colony optimization by Mohamad Nazri, Semoin

“…The project objectives are to develop Ant Colony Optimization (ACO) algorithm for CNC turning process and to optimize turning parameters for minimized production cost per unit. …”
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Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail by Foo, Fong Yeng, Lau, Gee Choon, Ismail, Zuhaimy

“…Trial and error often serves as the best method to determine the parameter. Therefore, a good optimization technique is required for identify the best parameter in minimizing the forecast errors. …”
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