Search Results - (( model evaluation means algorithm ) OR ( _ identification using algorithm ))*
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1
System identification using Extended Kalman Filter
Published 2017“…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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Student Project -
2
Identification of continuous-time hammerstein model using improved archimedes optimization algorithm
Published 2024“…Various advantages were observed with this proposed algorithm, including a lower number of coefficient criteria, improved accuracy in Hammerstein model identification, and diminished processing demands by reducing gain redundancy between nonlinear and linear subsystems. …”
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Article -
3
An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding
Published 2020“…In the classic Bag of visual words model, the Fuzzy c-means algorithm is replaced with K-means and the accuracy of SIFT matching is increased. …”
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4
Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm
Published 2021“…The optimization task involved hysteresis parameter identification of the root mean square error between the model and an actual magnetorheological damper. …”
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5
Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane
Published 2021“…This paper presents the identification of double pendulum overhead crane (DPOC) plant based on the hybrid Multi-Verse Optimizer with Sine Cosine Algorithm (HMVOSCA) using the continuous-time Hammerstein model. …”
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Conference or Workshop Item -
6
Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure
Published 2023“…This input-output data was then applied in a system identification method, which used an evolutionary algorithm with a linear autoregressive with exogenous (ARX) model structure to generate a dynamic model of the system. …”
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Article -
7
Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure
Published 2023“…This input-output data was then applied in a system identification method, which used an evolutionary algorithm with a linear autoregressive with exogenous (ARX) model structure to generate a dynamic model of the system. …”
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8
Data mining based damage identification using imperialist competitive algorithm and artificial neural network
Published 2018“…The efficiency coefficient and mean square error (MSE) are used to evaluate the performance of the ICA-ANN model. …”
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9
Relevance detection and summarizing strategies identification algorithm using linguistic measures / Seyed Asadollah Abdiesfandani
Published 2016“…The algorithm simulates two important tasks that are frequently used by the human experts to identify summarizing strategies used to produce the summary sentences: 1) sentences relevance identification; and 2) summarizing strategies identification. …”
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Thesis -
10
Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA)
Published 2024“…The statisti-cal analysis was used to evaluate the performance of the model based on the objective function which is the Mean Square Error (MSE). …”
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11
Real time nonlinear filtered-x lms algorithm for active noise control
Published 2012“…The developed THF-NLFXLMS algorithm is tested by means of simulation and implemented experimentally using FPGA-based real time controller for a nonlinear ANC application. …”
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Thesis -
12
Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…The statistical analysis was used to evaluate the performance of the model based on the objective function which is the Mean Square Error (MSE). …”
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13
Modeling of vehicle trajectory using K-means and fuzzy C-means clustering
Published 2019“…Hence, the clustering of vehicle trajectory dataset for similar patterns identification is implemented with k-means and fuzzy c-means (FCM) clustering algorithm. …”
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Proceedings -
14
A new hybrid genetic algorithm-sarima-artificial neural network in forecasting Malaysian export amount of palm oil
Published 2021“…The forecast accuracy for all the models was evaluated using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and Pearson correlation coefficient. …”
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Thesis -
15
A Hybrid Artificial Intelligence Model for Detecting Keratoconus
Published 2023“…This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. …”
Article -
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Self-calibration algorithm for a pressure sensor with a real-time approach based on an artificial neural network
Published 2018“…To verify the proposed model’s capability to build a self-calibration algorithm, the model was tested using an untrained input data set. …”
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Pothole detection using UAV with deep learning algorithm for road inspection
Published 2024“…The pothole detection model achieved a precision of 0.437, a recall of 0.800, and a mean average precision (mAP) of 0.740, highlighting its accuracy and reliability. …”
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Conference or Workshop Item -
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Normalized SPSA for Hammerstein model identification of twin rotor and electro-mechanical positioning systems
Published 2025“…Performance metrics such as the objective functions statistics, the number of function evaluations (NFE), and time- and frequency-domain responses were used for evaluation. …”
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Artifact identification for blood pressure and photoplethysmography signals in an unsupervised environment / Lim Pooi Khoon
Published 2020“…The robustness of this artifact detection algorithm was then evaluated on both short and continuous data collected from young and older subjects which included arrhythmia patients. …”
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Thesis -
20
An efficient method of biometric matching using interpolated ECG data
Published 2010“…The ECG features are extracted from both the training dataset and the test dataset for model development and identification. Two ECG biometric algorithms which are Cross Correlation (CC) and Percent Root-Mean-Square Deviation (PRD) were used for performance evaluation. …”
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