Search Results - (( data implication learning algorithm ) OR ( data equalization based algorithm ))
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Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making
Published 2023“…The study’s primary objectives were to identify the determinants that impacted urban upper-secondary students' enrolment in Additional Mathematics within the Kuantan District, Pahang, Malaysia, and to develop a novel stacked ensemble machine learning algorithm based on these determinants, following the CRISP-DM data science methodology. …”
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Application of Bat Algorithm and Its Modified Form Trained with ANN in Channel Equalization
Published 2022“…An alternative approach to training neural network-based equalizers is to use metaheuristic algorithms. …”
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Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems
Published 2013“…The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. …”
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Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems
Published 2012“…The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. …”
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Reduced-rank technique for joint channel estimation in TD-SCDMA systems.
Published 2013“…The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. …”
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Improved power output forecastingtechnique for effective battery management in photovoltaic system / Utpal Kumar Das
Published 2019“…A PSO-based algorithm is adopted for the appropriate selection of dominated parameters of SVR-based model to achieve better performance. …”
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Segmentation of MRI brain images using statistical approaches
Published 2011“…Therefore, these algorithms can be improved upon. A neighbourhood-based noise-reduction algorithm which uses the edges of an image is proposed. …”
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A comparative analysis of machine learning algorithms for diabetes prediction
Published 2024“…The methodology involves data collection, pre-processing, and training the algorithms using k-fold cross-validation. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…The best algorithm will not be the same for all the data sets. …”
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Enhanced handover decision algorithm in heterogeneous wireless network
Published 2017“…It also employs three types of vertical handover decision algorithms: equal priority, mobile priority and network priority. …”
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A comparison of watermarking image quality based on dual intermediate significant bit with genetic algorithm
Published 2013“…In this case, when the two hidden bits are equal to the original bits, there will be no change to the other remaining bits.However, if the original value is not equal to the embedded one, the nearest pixel to the original one will be chosen as the watermarked image.The second method, GA method is used to embed two bits of watermarking data within every pixel of the original image and to find the optimal value based on the existing DISB.On the other hand, if the two embedded bits are equal to the original bits then this means the watermarked image is still the same as the original one without any changes, while in the other case GA is used in determining the minimum fitness value in which the fittest is the absolute value between the pixel and chromosome and the value of chromosome between 0-255.The results indicate that the two methods produce a high quality watermarked image, but there is a big difference in the processing time, so the DISB method is faster than the GA method.…”
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Adjusted 0-1 knapsack problem in cargo flow by using artificial bee colony algorithm / Nor Zuliiziati Md Jani
Published 2021“…With its total value as much as possible, the number of items that may become less or at least equal to or equal to the limit. The aim of this research is to determine the flow of the shipment based on volume and to determine the total cost based on the flow of shipment by using Artificial Bee Colony (ABC) algorithm. …”
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Prediction of payment method in convenience stores using machine learning
Published 2023“…This study explores the application of machine learning techniques, specifically the Random Forest algorithm, to predict payment modes in the context of the Indonesian community. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40…”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2023“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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Malware Classification and Detection using Variations of Machine Learning Algorithm Models
Published 2025“…Types of attacks can be Ping of Death, flooding, remote-controlled attacks, UDP flooding, and Smurf Attacks. Attack data was obtained from the ClaMP dataset, which has an unbalanced data set, and has very high noise, so it is necessary to analyze data packets in network logs and optimize feature extraction which is then analyzed statistically with machine learning algorithms. …”
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