Search Results - (( parameter optimization method algorithm ) OR ( based distributed learning algorithm ))

Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
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Virtual power plant and microgrids controller for energy management based on optimization techniques by Abdolrasol M.G.M., Mohamed A., Hannan M.A.

Software defect prediction framework based on hybrid metaheuristic optimization methods by Wahono, Romi Satria

“…In this study, a software defect prediction framework that combines metaheuristic optimization methods for feature selection and parameter optimization, with meta learning methods for solving imbalanced class problem on datasets, which aims to improve the accuracy of classification models has been proposed. …”
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Parameter estimation in computational systems biology models: a comparative study of initialization methods in global optimization by Muhammad Akmal, Remli, Nor Syahidatul Nadiah, Ismail, Noor Azida, Sahabudin, Nor Bakiah, Abd Warif

“…Global optimization method based on an enhanced scatter search (ESS) algorithm is a suitable choice to address this issue. …”
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New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification by Balakrishnan, Malarvili, Ting, Chee Ming, Shaikh Salleh, Sheikh Hussain

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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. …”

A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition by Koh J.S., Tan R.H.G., Lim W.H., Tan N.M.L.

“…Therefore, a modified PSO hybridized with adaptive local search (MPSO-HALS) is designed as a robust, real-time MPPT algorithm. A modified initialization scheme that leverages grid partitioning and oppositional-based learning is incorporated to produce an evenly distributed initial population across P-V curve. …”

Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

“…Three major problems are encountered when designing metaheuristics; the first problem is balancing exploration with exploitation capabilities (which leads to premature convergence or trapping in the local minima), while the second problem is the dependency of the algorithm on the controlling parameters, which are parameters with unknown optimal values. …”
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Fault classification in smart distribution network using support vector machine by Chuan O.W., Ab Aziz N.F., Yasin Z.M., Salim N.A., Wahab N.A.

“…In this paper, a machine-learning algorithm known as Support Vector Machine (SVM) for fault type classification in distribution system has been developed. …”

Reactive power tracing in pool-based power system utilising the hybrid genetic algorithm and least squares support vector machine by Mohd Wazir, Mustafa, Prof. Dr., Mohd Herwan, Sulaiman, Hussain, Shareef, Dr., Siti Nur Hidayah, Abd Khalid

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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

“…Next, an advanced machine learning based on is utilized to predict islanding and none islanding states. …”
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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 results indicated that the hydropower generated by the proposed algorithm could produce an evenly distributed high amount of energy increases the reliability of the reservoir system. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…Also, self-adaptive scaling factor and crossover probability control parameters are introduced to diminish time of finding an optimal parameter to produce the best population. …”
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Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

“…The segmentation process was optimized using Fuzzy-based Segmentation Parameter. …”
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Mobility-aware Offloading Decision For Multi-access Edge Computing In 5g Networks by Saeid Jahandar, Lida Kouhalvandi, Ibraheem Shayea, Mustafa Ergen, Marwan Hadri Azmi, Hafizal Mohamad

Uncertainty parameters of battery energy storage integrated grid and their modeling approaches: A review and future research directions by Reza M.S., Hannan M.A., Ker P.J., Mansor M., Lipu M.S.H., Hossain M.J., Mahlia T.M.I.

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A predictive approach to improve a fault tolerance confidence level on grid resources scheduling by Bouyer, Asgarali, Md. Sap, Mohd. Noor

“…Therefore, finding a stable and fault tolerance resource require designing a predictive method that doing this work. Many methods are presented in a few years ago, but in these algorithms, some parameters such as job requirements and clear predictor method are not truly considered and also some methods apply optimistic view in grid scheduling cycle. …”
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A novel islanding detection technique using modified Slantlet transform in multi-distributed generation by Hizam, Hashim, Ahmadipour, Masoud, Mohd Radzi, Mohd Amran, Othman, Mohammad Lutfi, Chireh, Nikta

“…In this paper, a new hybrid islanding detection scheme based on a combination of a modified Slantlet Transform (MSLT) and machine learning is applied to a passive time frequency islanding detection of multiple distributed generation units. …”
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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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Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin by Shamsuddin, Noraishah

“…The Resilient Backpropagation (RPROP) algorithm is used to train the network. The optimized learning parameter used is 0.07 and the network has best performance when hidden neurons equal to 220. …”
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