Search Results - (( parameter optimization based algorithm ) OR ( using optimization tree algorithm ))
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Tree-based contrast subspace mining method
Published 2020“…Hence, this thesis presents the optimization of parameters values for the tree-based method by genetic algorithm. …”
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Single and Multiple variables control using Tree Physiology Optimization
Published 2017“…This paper presents the tuning of single-input single-output (SISO), and multiple-input multiple-output (MIMO) control system using Tree Physiology Optimization (TPO). TPO is a metaheuristic optimization algorithm that has a clustered diversification search strategy inspired from plant shoots growth. …”
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Improvement of horizontal streak on disparity map thru parameter optimization for stereo vision algorithm
Published 2024“…Then, the research continues to optimize the proposed local based SVDM algorithm through parameters optimization in obtaining the final disparity map. …”
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Intrusion Detection Systems, Issues, Challenges, and Needs
Published 2021“…Optimization algorithms such as genetic algorithm (GA), particle swarm optimization (PSO) algorithm , ant colony algorithm, and many other algorithms are used along with classifiers to improve the work of these classifiers in detecting intrusion and to increase the performance of these classifiers. …”
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Robot manipulator minimum jerk trajectory planning based on the improved dung Beetle Optimizer Algorithm
Published 2024“…Trajectory planning of robotic manipulators in complex environments involves generating smooth and collision-free paths, and key aspects to consider include dynamic environment perception, path planning, trajectory smoothing and optimization, and obstacle avoidance. This paper discusses different algorithms and finally proposes a fusion of the improved Dung Beetle Optimizer (IDBO) algorithm using chaotic mapping, sinusoidal random mutation, and nonlinear convergence strategies with the bidirectional Rapidly exploring Random Tree (RRT) algorithm to achieve manipulator trajectory planning and minimum jerk optimization trajectory. …”
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Tree physiology optimization on SISO and MIMO PID control tuning
Published 2018“…This paper presents the tuning of PID controller for single-input single-output (SISO) and multiple-input multiple-output (MIMO) control systems using tree physiology optimization (TPO). TPO is a metaheuristic algorithm inspired from a plant growth system derived based on the idea of plant architecture and Thornley model (TM). …”
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Tree physiology optimization on SISO and MIMO PID control tuning
Published 2018“…This paper presents the tuning of PID controller for single-input single-output (SISO) and multiple-input multiple-output (MIMO) control systems using tree physiology optimization (TPO). TPO is a metaheuristic algorithm inspired from a plant growth system derived based on the idea of plant architecture and Thornley model (TM). …”
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Adaptive rapidly-exploring-random-tree-star (Rrt*) -Smart: algorithm characteristics and behavior analysis in complex environments
Published 2013“…This paper presents a new scheme for RRT*-Smart that helps it to adapt to various types of environments by tuning its parameters during planning based on the information gathered online. …”
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Wireless sensor nodes deployment using multi-robot based on improved spanning tree algorithm
Published 2015“…Developing an exploration algorithm based on spanning tree is the main contribution. …”
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui
Published 2019“…ReliefF can solve the problem of large feature dimension in the existing RKELM. By using clustering method K-Means, we have found the best center point position to calculate Kernel matrix. at last, we have employed Quantum-behaved Particle Swarm Optimization (QPSO) to get the optimal kernel parameter in the proposed model. …”
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Water optimization technique for precision irrigation system using IoT and machine learning
Published 2022“…The GBT is used to predict the real values based on the observations. …”
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Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…The segmentation process was optimized using Fuzzy-based Segmentation Parameter. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…The optimal scale, shape and compactness parameters of multi-resolution segmentation have been determined and the detection accuracy was evaluated based on receiver operating characteristics (ROC). …”
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Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat
Published 2024“…This is due to the data generated from the numerical model possess the pattern for the ML algorithm ease of prediction. In addition, Coati Optimization algorithm, Particle Swarm Opimisation (PSO) and Bayesian Optimsiation (BO) are integrated to identify optimal parameters and minimize settlement during twin tunnel excavation and GBT with the optimisation algorithm has shown consistent capability identifying the least SS induced by twin tunnels Keyword: …”
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Hybrid Neural Network and Decision Tree for for Exchange Rates Forecasting
Published 2012“…The models are constructed by using the better of parameters and architectures based on related work such as filtering mechanism, number of hidden layers, number of hidden neurons, training algorithm, and error measurement, with the assumption that if the hybrid model is constructed by the better parameters and architectures, then the output of the model also produces better result…”
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Diamond price prediction using random forest algorithm / Nur Amirah Mohd Azmi
Published 2025“…Traditional methods struggle to model these complexities effectively, necessitating adoption of advanced algorithms to improve accuracy. The aim of this project is to develop a Diamond Price Prediction System using Random Forest, designed to accurately predict diamond prices based on attributes. …”
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Determination of tree stem volume : A case study of Cinnamomum
Published 2013“…Transformations are numerically optimized for linearity and normality of models. The three stem biomass equations adopted are namely, the Newton, Huber and Smalian’s formulae, based on the multiple regression (MR) and polynomial regression (PR) techniques. …”
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