Search Results - (( java implication based algorithm ) OR ( pre implementation means algorithm ))
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Simulation model algorithm for pre-hospital emergency care (PHEC) volunteers in Indonesia
Published 2018“…The results reveals that simulation model using algorithm influences the improvement of traffic volunteers’ emergency management capabilities with p-value of < 0.05 and mean score difference of 34.5%, and the model is highly effective to be implemented to improve the capability of traffic assistant volunteers to manage trauma emergency with the mean score difference of 11.5%. …”
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A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds
Published 2007“…The results of the algorithm show significant improvement in comparison to a similar implementation of the hard c-means algorithm.…”
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Book Section -
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The Design of Pre-Processing Multidimensional Data Based on Component Analysis
Published 2011“…RapidMiner is used for data pre-processing using FastICA algorithm. Kernel K-mean is used to cluster the pre-processed data and Expectation Maximization (EM) is used to model. …”
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Image clustering comparison of two color segmentation techniques
Published 2010“…This project proposed a two color segmentation techniques such as K-means and Fuzzy C-means clustering algorithm that are accurately segment the desired images, which have the same color as the pre-selected pixels with background subtraction. …”
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Thesis -
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Embedded car plate image recognition system
Published 2008“…In order to speed up the image processing process, the system do not use complex algorithm such as Neural Network but use a simple algorithm such as template matching. …”
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Learning Object -
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Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting
Published 2021“…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589)
“…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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Monograph -
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The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
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An improved diabetes risk prediction framework : An Indonesian case study
Published 2018“…Pre-processing resolves the issue of missing data and hence normalizes the data.Outlier treatment employs k-mean clustering to validate the class.Suitable components were selected through comparison of classifier algorithms and feature selection.Attribute weighting based feature selection was selected for assigning weightage.Weighted risk factor was used on training dataset in order to improve accuracy and computation time of the prediction. …”
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Hybrid neural network in medicolegal degree of injury determination based on Visum et Repertum
Published 2023“…Then, the selection of the critical features is chosen via Neural Network (NN) as classification algorithm and Genetic Algorithm (GA) as an optimization technique. …”
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Optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization
Published 2018“…This technique can be implemented on existing buildings with existing HVAC systems with minimal modifications to the HVAC infrastructure. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Arabic Speaker Identification System for Forensic Authentication Using K-NN Algorithm
Published 2023Conference Paper -
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Exploring employee working productivity: initial insights from machine learning predictive analytics and visualization / Mohd Norhisham Razali ... [et al.]
Published 2023“…Experimental results revealed that the linear regression model achieved the best performance in terms of Mean Absolute Error (MAE) and Mean Squared Error (MSE), with values of 0.4878 and 0.4682, respectively. …”
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A study on component-based technology for development of complex bioinformatics software
Published 2004“…Next step which is highlighted another novel part in their study whereas a hybrid clustering SVM is introduced to reduce the training complexity. SOM and K-Means are integrated as a clustering algorithm to produce a granular input, while SVM is then used as a classifier. …”
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Monograph -
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A Novel Approach to Estimate Diffuse Attenuation Coefficients for QuickBird Satellite Images: A Case Study at Kish Island, the Persian Gulf.
Published 2013“…Eventually, the maximum likelihood classifier was implemented during pre and post correction steps to examine the capability of the proposed approach. …”
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Real-time identification of an unmanned quadcopter flight dynamics using fully tuned radial basis function network
Published 2018“…Recursive learning algorithms, such as Constant Trace (CT) can be implemented to solve insufficient training data and over-fitting problems by developing a new model from real-time flight data in each time step. …”
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