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An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system
Published 2011“…The idea is to use GA as an optimizer to find the optimal values of hyper-parameters of LS-SVM and adopt a supervised learning approach to train the LS-SVM model. …”
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Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm
Published 2020“…Existing approaches for this optimization problem have several drawbacks, including non-adaptive network configuration that may cause premature death of sensor nodes. Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin
Published 2014“…On top of that, the multiobjective QIEP is also applied to determine the optimal undervoltage load shedding (UVLS) in various loading conditions according to load profile with and without DG. …”
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Efficient transmission based on genetic evolutionary algorithm
Published 2022“…Through the simulation of the transmission performance of genetic optimization algorithm, the comparison of transmission energy consumption between GA and evolutionary algorithm is analyzed, and the evolutionary algorithm with higher transmission performance is obtained. …”
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Tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm
Published 2011“…This paper attempts to trace the real power transfer of individual generators to loads in pool based power system by incorporating the hybridization of Least Squares Support Vector Machine (LS-SVM) with Continuous Genetic Algorithm (CGA)- CGA-LSSVM. …”
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Prediction of COVID-19 outbbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman
Published 2024“…A prototype architecture and a user-friendly graphical interface tailored for SVM-based outbreak predictions are developed, accompanied by detailed code snippets elucidating essential steps in data loading, encoding, scaling, and SVM model training. …”
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Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm
Published 2023“…Simulation results show that WSN deployed using the MOTPSMA sensor node placement algorithm outperforms the performance of the other two algorithms in terms of coverage, connectivity and energy usage. © 2014 King Fahd University of Petroleum and Minerals.…”
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Reactive power planning for maximum load margin improvement using Fast Artificial Immune Support Vector Machine (FAISVM)
Published 2023“…FAISVM is a hybrid algorithm that incorporates the application of Artificial Immune System (AIS) and Support Vector Machine (SVM) in solving RPP problems. …”
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WSN sensor node placement approach based on multi-objective optimization
Published 2023“…A sensor node placement algorithm that utilizes Multi-objective Territorial Predator Scent Marking Algorithm (MOTPSMA) is presented in this paper. …”
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Automatic design, optimization and In-Situ Fabrication of Heterogeneous Swarm Robot bodies using 3-D printing and multi-objective evolutionary algorithms
Published 2012“…In this research, an artificial evolution approach utilizing Single-Objective Evolutionary Algorithm (SOEA) and Multi-Objective Evolutionary Algorithm (MOEA) respectively are investigated in the automatic design and optimization of the morphology of a Six Articulated-Wheeled Robot (SAWR) with climbing ability. …”
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Fault classification in smart distribution network using support vector machine
Published 2023“…Right setting parameters are important to learning results and generalization ability of SVM. Gaussian radial basis function (RBF) kernel function has been used for training of SVM to accomplish the most optimized classifier. …”
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Multi-sensor fusion based on multiple classifier systems for human activity identification
Published 2019“…The study proposes a multi-view ensemble algorithm to integrate predicted values of different motion sensors. …”
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Predicting Petroleum Reservoir Properties from Downhole Sensor Data using an Ensemble Model of Neural Networks
Published 2013“…One of such is the difficulty in determining the most suitable learning algorithm for optimal model performance. To save the cost, effort and time involved in the use of trial-and-error and evolutionary methods, this paper presents an ensemble model of ANN that combines the diverse performances of seven "weak" learning algorithms to evolve an ensemble solution in the prediction of porosity and permeability of petroleum reservoirs. …”
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Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification
Published 2019“…After that, the simulation results were validated in the Load Test, and it shows that structure made from PLA material was able to withstand load with 1.7kg while the structure made from ABS material is only able to withstand load with 1.6kg. …”
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