Search Results - (( motion optimization path algorithm ) OR ( parameter optimization bees algorithm ))
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1
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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2
Runtime reduction in optimal multi-query sampling-based motion planning
Published 2023“…Algorithms; Dispersions; Manufacture; Query processing; Robotics; High-dimensional; Low dispersions; Optimal solutions; Path length; Planning tasks; Sampling-based; Sampling-based algorithms; Sampling-based motion planning; Motion planning…”
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3
A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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4
A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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5
A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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6
A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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7
A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2022“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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8
A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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9
A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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10
A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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11
A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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12
Minimizing machining airtime motion with an ant colony algorithm
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13
Artificial bee colony in optimizing process parameters of surface roughness in end milling and abrasive waterjet machining
Published 2012“…This research develops an optimization algorithm using artificial bee colony (ABC) algorithm to optimize the process parameters that will lead to minimum surface roughness (Ra) value for both end miling and abrasive waterjet machining. …”
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14
Using the bees algorithm to optimise a support vector machine for wood defect classification
Published 2007“…The paper presents the results obtained to demonstrate the strengths of the Bees Algorithm as an optimization tool.…”
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15
Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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16
Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway
Published 2023“…Parameter estimation is conducted to obtain the optimal values for parameters related to the fermentation process. …”
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17
Cyclic Path Planning Of Hyper-Redundant Manipulator Using Whale Optimization Algorithm
Published 2023Article -
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Lévy mutation in artificial bee colony algorithm for gasoline price prediction
Published 2012“…In this paper, a mutation strategy that is based on Lévy Probabily Distribution is introduced in Artificial Bee Colony algorithm. The purpose is to better exploit promising solutions found by the bees.Such an approach is used to improve the performance of the original ABC in optimizing Least Squares Support Vector Machine hyper parameters.From the conducted experiment, the proposed lvABC shows encouraging results in optimizing parameters of interest.The proposed.lvABC-LSSVM has outperformed existing prediction model, Backpropogation Neural Network (BPNN), in predicting gasoline price.…”
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Estimation of optimal machining control parameters using artificial bee colony
Published 2013“…This research employed ABC algorithm to optimize the machining control parameters that lead to a minimum surface roughness (R a) value for AWJ machining. …”
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Artificial bee colony optimization of interval type-2 fuzzy extreme learning system for chaotic data
Published 2016“…This paper propose a novel hybrid learning algorithm for the design of IT2FLS. The proposed hybrid learning algorithm utilizes the combination of extreme learning machine (ELM) and artificial bee colony optimization (ABC) to tune the parameters of the consequent and antecedent parts of the IT2FLS, respectively. …”
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