Search Results - (( parameters deviations methods algorithm ) OR ( parameters estimation path algorithm ))
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1
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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2
Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023Conference Paper -
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Estimation of transformers health index based on condition parameter factor and hidden Markov model
Published 2018“…Next, the emission probabilities for each of the condition parameter factors were derived based on frequency of occurrence method. …”
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4
Analysis of robot localisation performance based on extended kalman filter
Published 2015“…First is the performance of the algorithm using different parameters in which different velocities and number of landmarks have been used to determine the accuracy of the localisation method. …”
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5
Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…Finally the adaptive portion of FLC is applied in order to compensate the effect of unknown parameter variations in the Pico-satellite system by using an adaptable gain which is connected in the forward path of the FLC. …”
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6
Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm
Published 2023“…Decision making; Disaster prevention; Floods; Routing algorithms; Water resources; Absolute deviations; Bat algorithms; Comparative analysis; Computational time; Flood routing; Muskingum models; Particle swarm optimization algorithm; Swarm algorithms; Particle swarm optimization (PSO); accuracy assessment; algorithm; comparative study; decision making; flood; flood forecasting; flood routing; numerical method; optimization; parameter estimation; water resource; United Kingdom; United States…”
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All-pass filtered x least mean square algorithm for narrowband active noise control
Published 2018“…Most available ANC uses the secondary path modelling including filtered x least mean square (FxLMS) algorithm. …”
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A hybrid metaheuristic algorithm for identification of continuous-time Hammerstein systems
Published 2021“…The results showed that the proposed method was efficient in identifying both the Hammerstein model subsystems in terms of the quadratic output estimation error and parameter deviation index. …”
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9
PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems
Published 2016“…The optimal parameters of the PID scheme optimized by the proposed MS algorithm are compared with that one’s obtained by GA algorithm, and the proposed method has proven that its performance is more efficient and improved as well. …”
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10
Statistical approach on grading: mixture modeling
Published 2006“…The problem lies in estimating the posterior density of the parameters which is analytically intractable. A solution to this problem is using the Markov Chain Monte Carlo method namely Gibbs sampler algorithm. …”
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11
Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm
Published 2018“…In this study, a hybrid of the bat algorithm (BA) and the particle swarm optimization (PSO) algorithm, i.e., the hybrid bat-swarm algorithm (HBSA), was developed for the optimal determination of these four parameters. …”
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12
Development of robust control scheme for wheeled mobile robot in restricted environment
Published 2021“…A novel algorithm so called laser simulator logic (LSL) has been develo ped to estimate the inertia moment when the environment is noisy and cannot use fuzzy logic algorithm. …”
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13
A new hybrid multiaxial fatigue life model based on critical plane continuum damage mechanics and genetic algorithm
Published 2015“…The proposed model serves as path-independent fatigue life estimating tool hence can be used with any type of loading conditions. …”
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14
An Optimized PID Parameters for LFC in Interconnected Power Systems Using MLSL Optimization Algorithm
Published 2016“…In order to enhance the dynamic performance, the optimal parameters of the PID scheme which optimized by the proposed MLSL algorithm are compared with that one’s obtained by GA algorithm. …”
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15
Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
Published 2018“…Design of hydraulic structures, flood warning systems, evacuation measures, and traffic management require river flood routing. A common hydrologic method of flood routing is the Muskingum method. The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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16
Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…The simulation results indicate that the proposed method is suitable to detect a single outlier. As for the multiple outliers, a clustering algorithm is considered and a dendogram to visualise the clustering algorithm is used. …”
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17
Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending
Published 2006“…The standard deviation between the finite element method and the neural network metamodels for the two functions are 0.635 degree and 0.985 mm respectively. …”
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18
Autonomous road roundabout detection and navigation system for smart vehicles and cities using laser simulator–fuzzy logic algorithms and sensor fusion
Published 2020“…The path generation algorithm was fully derived within the local maps and tested with a WMR platform in real-time.…”
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Investigation of firefly algorithm and chaos firefly algorithm for load prequency control / Zaid Najid
Published 2015“…In order to obtain the best controller parameter values for LFC, Firefly Algorithm (FA) and Chaos Firefly Algorithm (CFA) are used. …”
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20
Metaheuristic Algorithm for Wellbore Trajectory Optimization
Published 2019“…For smooth and effective performance (i.e. quickly locating global optima while taking the shortest amount of computational time) we must identify flexible control parameters. Later this parameter can be effectively fixed to tune different algorithm. …”
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