Search Results - (( data normalization path algorithm ) OR ( variable training based algorithm ))
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Wide area measurement system in the IEEE-14 bus system using multiobjective shortest path algorithm for fault analysis
Published 2021“…The distances of the normal path (without simulated fault) and the new path (with simulated fault) were recorded. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…The focus of the paper is to propose a hybrid approach for the selection of the most influential input variables for the training and testing of neural network based hybrid models. …”
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Improved Dynamic Ant Colony System (DACS) on Symmetric Traveling Salesman Problem (TSP).
Published 2007“…Their ability as a colony to find paths or routes to the food sources has inspired the development of an algorithm namely Ant Colony System (ACS). …”
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Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks
Published 2015“…The efficacy of these models depends upon many factors such as, neural network architecture, type of training algorithm, input training and testing data set and initial values of synaptic weights. …”
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Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks
Published 2024thesis::doctoral thesis -
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Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms
Published 2021“…Initially, the Ridge algorithm-based modeling is performed in detail, and then SVR-based LR, named as SVR (LR), SVR-based radial basis function—SVR (RBF), and SVR-based polynomial regression—SVR (Poly.) algorithms, are applied. …”
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Multidimensional Minimization Training Algorithms for Steam Boiler Drum Level Trip Using Artificial Intelligence Monitoring System
Published 2010“…The selection of the relevant variables for the neural networks is based on merging between theoretical analysis base and the plant operator experience. …”
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Intelligent motion planning of a mobile robot by using convolutional neural network / Siti Asmah Abdullah
Published 2019“…By the path reference created by A* algorithm the robot is capable in optimizing its path to reach the designated destination. …”
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A new hybrid multiaxial fatigue life model based on critical plane continuum damage mechanics and genetic algorithm
Published 2015“…Interpolation scheme based on the multiaixality of stresses is suggested for the determination of coefficients of the model for different loading paths. Material parameter including stress sensitivity factor for normal or shear stress can be incorporated to improve the calibration process. …”
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Improving Channel Assignment for Vehicular Ad-hoc Sensor Network in Disaster Management System
Published 2024“…Moreover, an average of 22.91% for LTE-AIC with respect to normal LTE-A and 38.63% compared to LTE for high data rate. …”
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Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)
Published 2008“…The primary concern is to acquire the clear picture of the implementation of Multi-Objective Genetic Algorithm and the essential of variable valve timing effects on the engine performances in various engine speeds. …”
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Proceeding Paper -
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Neural network based model predictive control for a steel pickling process
Published 2009“…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network
Published 2021“…Prior to the development of ANN-based WQI prediction model, the BR algorithm was chosen with two-, three-, four-, five- and six-neuron architectures for 60% and 70% training. …”
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Monograph -
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Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models
Published 2023“…Based on the identical dataset, the GA-BP and PSO-BP algorithms are also compared to the PCA-BAS-ENN algorithm. …”
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Reinforcement learning-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage traning
Published 2022“…Third, the concept of multistage training based on the dynamic variables was proposed as an opposing concept to one-stage combinatory training. …”
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Deadline guarantee for scientific workflow using dynamic scheduling algorithms on IaaS clouds
Published 2018“…We will conduct a simulation experiment of scientific workflow algorithms with both of the algorithms mentioned above. …”
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The Identification of High Potential Archers Based on Fitness and Motor Ability Variables: A Support Vector Machine Approach
Published 2018“…Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the performance variables tested. SVM models with linear, quadratic, cubic, fine RBF, medium RBF, as well as the coarse RBF kernel functions, were trained based on the measured performance variables. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA
Published 2012“…The research work also investigates several recursive algorithms including recursive Kalman filter (RKF) and extended Kalman filter (EKF) using extreme learning machine (ELM) and hybrid linear/nonlinear training technique by incorporating the fiee derivative concept. …”
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