Search Results - (( using combination using algorithm ) OR ( data equalization based algorithm ))

Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

“…Based on the findings, Algorithm 2 outperforms Algorithm 1 in classifying the minority group, while both proposed algorithms perform equally well in classifying the majority group. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

“…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 by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A.

“…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 by Ahmed Dheyab, Saad, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

“…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 by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

“…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 by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

“…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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Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi by Rahimi, Ahmad Faris

“…In the implementation phase, Bubble Sort, Euclidean Distance, 10-Fold Cross validation, and K Nearest Neighbor algorithm are developed. This application is using the data from a Taiwan bank which is obtained from the UCI data repository website. …”
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Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

“…Two selection methods that are used in Genetic Algorithm are the roulette wheel and tournament selections. …”
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Weighted Sum-Dijkstra’s Algorithm in Best Path Identification based on Multiple Criteria by Ting, Kien Hua, Noraini Abdullah

“…In order to achieve the objective, Weighted Sum-Dijkstra’s Algorithm (WSDA), a combination method between WSM and Dijkstra’s Algorithm is applied to solve multiple criteria network problems. …”
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Development of prediction model for phosphate in reservoir water system based machine learning algorithms by Latif S.D., Birima A.H., Ahmed A.N., Hatem D.M., Al-Ansari N., Fai C.M., El-Shafie A.

A combinatory algorithm of univariate and multivariate gene selection by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

“…The results show that the mean of misclassification error of training samples in 100 iteration are almost equal in two algorithms but our algorithm have the better ability to classify independent samples.…”
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QR factorization equalisation scheme for mode devision multiplexing transmission in fibre optics by Abbas, Sharafal-Deen Abdulkadhum

“…The algorithm mentioned in the study reduces the computational complexity problem which is one of the main issues that accompany currently used tap filter algorithms, such as (LMS) and (RLS). …”
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Chaos synchronization and cryptography for secure communications / Fatin Nabila Abd Latiff by Fatin Nabila , Abd Latiff

“…If these two chaotic signals of equal power are combined and then used to transmit message signals, it may be difficult for intruders to use conventional attack methods because the chaotic carrier signal has added complexity. …”
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Validation of combine white noise using simulated data by Agboluaje, Ayodele Abraham, Ismail, Suzilah, Chee, Yin Yip

“…The white noise series are transformed into Combine White Noise Model (CWN).The assessments of the model are based on data simulation.The simulated data of 200 and 300 sample sizes of EGARCH are generated.The generated EGARCH data are based on low, moderate and high values of leverage and skewness.Each of these generated EGARCH data is used for the estimation of EGARCH and Moving Average (MA). …”
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Elitist hybrid migrating birds optimization and genetic algorithm based strategy for T-way test suite generation by Hasneeza Liza, Zakaria

“…Addressing the aforementioned issues, this research proposes the development and implementation of hybrid t-way strategy based Migrating Birds Optimization Algorithm (MBO) and Genetic Algorithm (GA) with elitism, termed Elitist Hybrid MBO-GA. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. Data level based methods are meant to solve the imbalanced classification problem based on the idea of making both classes equal in number. …”
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A framework for automatic modelling of survival using fuzzy inference. by Hamdan, Hazlina, Garibaldi, Jonathan M.

“…After the initialisation of the fuzzy inference structure, the replication data (until time to event) will be subject to be trained using the gradient descent and nonnegative least square algorithm to estimate the conditional event probability. …”
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Water level prediction using various machine learning algorithms: a case study of Durian Tunggal river, Malaysia by Ahmed A.N., Yafouz A., Birima A.H., Kisi O., Huang Y.F., Sherif M., Sefelnasr A., El-Shafie A.

“…In this study, six different Machine Learning (ML) algorithms were developed to predict the river�s water level, on a daily basis based on collected data from 1990 to 2019 which were used to train and test the proposed models. …”

Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

“…The designed system is validated by using images treated with noise of single and combination of various types. …”
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