Search Results - (( parameter evaluation path algorithm ) OR ( using optimization learning algorithm ))
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Evaluation of robot path planning algorithms in global static environments: genetic algorithm vs ant colony optimization algorithm / Nohaidda Sariff and Norlida Buniyamin
Published 2010“…Performances between both algorithms were compared and evaluated in terms of speed and number of iterations that each algorithm takes to find an optimal path within several selected environments. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…Sampling-based motion planning is a class of randomized path planning algorithms with proven completeness. …”
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Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm
Published 2023Subjects:Conference Paper -
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A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains
Published 2023“…These parameters are designed carefully to cover different requirements of the path planner. …”
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Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff
Published 2011“…Subsequently, both algorithms were applied to the test environments. Finally, the performances of both algorithms were analyzed and evaluated based on the required criteria. …”
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An Experiment of Ant Algorithms : Case Study of Kota Kinabalu Central Town
Published 2005“…The objectives of this study are to explore and evaluate the Ant System (AS) algorithm and Ant Colony System (ACS) algorithm in finding shortest paths. …”
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Performance analysis of ZigBeePRO network using shortest path algorithm for Distributed Renewable Generation
Published 2021“…Due to this polarization effect, the brick-built type cabin at the DRG site is a consequence of a higher propagation path loss than the Iron (III)-made cabin. The other performance parameters, including network throughput, data loss, and ZigBeePRO collision, are also evaluated.…”
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All-pass filtered x least mean square algorithm for narrowband active noise control
Published 2018“…The performance evaluation in terms of convergence speed of the proposed algorithm is validated with standard ANC without secondary path modelling. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…Teaching learning-based optimization is one of the widely accepted metaheuristic algorithms inspired by teaching and learning within classrooms. …”
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Attack path selection optimization with adaptive genetic algorithms
Published 2016“…It calculates the appropriate adjustments for the control parameters such as selection and crossover rate. Possible attack paths are then identified and evaluated based on an attack graph representing the network under study. …”
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Attack path selection optimization with adaptive genetic algorithms
Published 2016“…It calculates the appropriate adjustments for the control parameters such as selection and crossover rate. Possible attack paths are then identified and evaluated based on an attack graph representing the network under study. …”
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Transmission path optimization Based on Efficiency Communication System
Published 2022“…At the same time, the developed algorithm combines the relative position of the cluster and the base station to further improve the routing method of the sub-cluster head, Finally, the algorithm analyzes the influence of different parameters on the transmission path, and use the simulation experiments to evaluate the conclusions.…”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…Therefore, in this study a new optimized variant of machine learning algorithms is presented. …”
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Real-Time Optimal Trajectory Correction (ROTC) for autonomous quadrotor / Noorfadzli Abdul Razak
Published 2018“…The algorithm works if the quadrotor undergoes a deviation, an admissible trajectory path is generated for the quadrotor rapidly return on the straight-line route. …”
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15
An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction
Published 2014“…Backpropagation (BP) learning algorithm is the well-known learning technique that trained ANN. …”
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Particle swarm optimization for neural network learning enhancement
Published 2006“…To overcome this problem, Genetic Algorithm (GA) has been used to determine optimal value for BP parameters such as learning rate and momentum rate and also for weight optimization. …”
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Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle
Published 2023“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm
Published 2024“…This paper investigates the optimization of a CHFS problem using the Teaching Learning-Based Optimization (TLBO) algorithm. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. …”
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