Search Results - (( parameter evaluation means algorithm ) OR ( variable extraction method algorithm ))
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1
Perturbation stochastic model updating of a bolted structure / Mohamad Azam Shah Aziz Shah
Published 2022“…For the latter, the bolted structure was reassembled 100 times to evaluate the variability of the dynamic behaviour of the structure. …”
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2
Clinical relevance of VKORC1 (G-1639A and C1173T) and CYP2C9*3 among patients on warfarin
Published 2011“…The mean dose predicted using the algorithm derived from cohort 1 was lower than the actual dose for cohort 2 (3·30 mg, SD 0·84 vs. 3·45 mg, SD 1·42). …”
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3
Enhancing obfuscation technique for protecting source code against software reverse engineering
Published 2019“…Empirical evaluation was conducted to evaluate the proposed Hybrid Obfuscation Technique. …”
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4
A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting
Published 2020“…Five evaluation metrics were utilized; mean average percent error (MAPE), accuracy, symmetric mean absolute percent error (SMAPE), root mean square percent error (RMSPE) and fitness value. …”
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5
Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links
Published 2022“…The quantum calculus provides an extra degree of freedom to search the local and global minima by inducing a q-parameter. Motivated by this fact, a quantum calculus-based noisy links incremental least mean squares (NL-qILMS) algorithm is proposed. …”
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6
Impact of evolutionary algorithm on optimization of nonconventional machining process parameters
Published 2025“…Specifically, the PSO algorithm achieved a mean surface roughness improvement of 0.44% over GA, and 1.1% and 1.23% over ACO and FA, respectively. …”
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7
An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis
Published 2022“…The k-means and the Gaussian mixture distribution were adopted as the clustering algorithms and each algorithm was tested on four datasets with four distinct clustering evaluation criteria: Calinski-Harabasz, Davies-Bouldin, Gap and Silhouette. …”
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8
Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network
Published 2023“…The evaluation process was implemented on RK-Means, K-Means++, and OK-Means models. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The feature extraction methods evaluated were Grayscale Pixel Values, Mean Pixel Value of Channels, and Extracting Edge Features. …”
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Objective and Subjective Evaluations of Adaptive Noise Cancellation Systems with Selectable Algorithms for Speech Intelligibility
Published 2018“…For subjective evaluation, listening tests were evaluated using the Mean Opinion Score (MOS) technique. …”
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Coronary artery stenosis detection and visualization / Tang Sze Ling
Published 2015“…The proposed method benchmarked with the state-of-the-art methods and achieved comparable results. …”
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14
Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…In other words, in order to get a good result, the BPNN learning algorithm needs to be executed several times with different topology structures and parameter values in order to determine the best set of parameter values used in the BPNN. …”
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15
Stock price predictive analysis: An application of hybrid barnacles mating optimizer with artificial neural network
Published 2023“…The proposed hybrid predictive model of BMO-ANN is tested on time series data of stock price using six selected inputs to predict the next day’ closing prices. Evaluated based on Mean Square Error (MSE) and Root Mean Square Error (RMSPE), the proposed BMO-ANN exhibits significant superiority over the other identified hybrid algorithms. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
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Bouc-Wen hysteresis parameter optimization for magnetorheological damper using Cuckoo search algorithm
Published 2020“…This paper proposed an optimized Phenomenological Bouc-Wen model for MR damper. Cuckoo search algorithm is used to optimize the parameters in phenomenological Bouc-Wen model. …”
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Optimizing timber transportation planning for timber harvesting using bees algorithm in Malaysia
Published 2023“…A Bees Algorithm (BA) was proposed to find an optimum TTP for timber extraction, forest road, and landing locations with grid cell-sized 10 m × 10 m and attributed with fixed and variable costs. …”
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Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach
Published 2022“…The performances of the algorithms were evaluated using the coefficient of determination (R2), root mean square error (RMSE), mean square error (MSE), and mean absolute error (MAE). …”
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Multi road marking detection system for autonomous car using hybrid- based method
Published 2018“…Wu dataset that consist of 1208 road images, which were extracted from videos recorded around California, the proposed algorithm performed satisfactorily. …”
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