Search Results - (( using solution using algorithm ) OR ( using (vectorisation OR vectorization) means algorithm ))

Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

“…After classifying the time set using the canopy with the K-means algorithm and the vector representation weighted by factors, the clustering impact is assessed using purity, precision, recall, and F value. …”

A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works by Gorment N.Z., Selamat A., Krejcar O.

Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine by Fathi Mahdi Elsiddig Haroun, Mr.

“…In this dissertation, a new vegetation encroachment detection method was proposed by studying the feasibility of using the visible-light band of highresolution satellite images using the RetinaNet deep learning model and Support Vector Machine algorithm (SVM). …”

A novel RSSI prediction using imperialist competition algorithm (ICA), radial basis function (RBF) and firefly algorithm (FFA) in wireless networks by Goudarzi, Shidrokh, Hassan, Wan Haslina, Hassan Abdalla Hashim, Aisha, Soleymani, Seyed Ahmad, Anisi, Mohammad Hossein, Zakaria, Omar M.

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K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm by Al-Hafiz, Ali Raheem, Jabir, Adnan J., Subramaniam, Shamala

“…In the first phase, the best set of features is identified by the Genetic algorithm and is utilised by the K-means clustering algorithm to divide the dataset into groups with similar traits. …”
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An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum by Darzi S., Tiong S.K., Tariqul Islam M., Rezai Soleymanpour H., Kibria S.

Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

“…These results can be seen as further explanation on the success of Truncated Newton method in TR-KLR and TR Iteratively Re-weighted Least Square (TR-IRLS) algorithm respectively, because of the equivalence of iterative method used by these algorithms. …”
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Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

“…The proposed algorithm has been evaluated using 24 benchmark functions. …”
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Enhanced Ad Hoc On-Demand Distance Vector Routing Protocol For Mobile Ad Hoc Network Internet Connectivity by Gurusamy, Gobi

“…This evaluation is done by means of simulation using NS-2 developed by University California Berkeley. …”
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

“…The rationale behind developing algorithms using real encoding of chromosome representations is the limitations of binary encoding. …”
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Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation by Kumar, A., Ridha, S., Ganet, T., Vasant, P., Ilyas, S.U.

“…The impact of each input parameter affecting the pressure drop is quantified using the RF algorithm. © 2020 by the authors.…”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

“…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

“…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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Data stream clustering by divide and conquer approach based on vector model by Khalilian, Madjid, Mustapha, Norwati, Sulaiman, Nasir

“…In this paper, DCSTREAM method is proposed with regard to the mentioned issues to cluster big datasets using the vector model and k-Means divide and conquer approach. …”
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Prediction of device performance in SnO2 based inverted organic solar cells using machine learning framework by Aidil Zulkafli, Nadhirah, Elyca Anak Bundak, Caceja, Amiruddin Abd Rahman, Mohd, Chin Yap, Chi, Chong, Kok-Keong, Tee Tan, Sin

“…The accuracy of the prediction was controlled using the root-mean-square error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R2). …”
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Enhancing clustering algorithm with initial centroids in tool wear region recognition by Kasim, Nur Adilla, Nuawi, Mohd Zaki, Abdul Ghani, Jaharah, Ngatiman, Nor Azazi, Che Haron, Che Hassan, Muhammad Rizal

“…Nevertheless, the algorithm is sensitive to the initial centroids giving various solution every time the system updating. …”
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Subspace Techniques for Brain Signal Enhancement by Kamel , Nidal, Yusoff, Mohd Zuki

“…Next, the validity and the effectiveness of the algorithms to detect the P100's (used in objective assessment of visual pathways) are evaluated using real patient data collected from a hospital. …”
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Generalizations and Some Applications of Kronecker and Hadamard Products of Matrices by Mah'd Al Zhour, Zeyad Abdel Aziz

“…The analysis indicates also that the algorithms can be easily to find the common exact solutions to the coupled matrix and matrix differential equations for partitioned matrices by using the connections between Tracy-Singh, Block Kronecker and Khatri -Rao products and partitioned vector row (column) and our definition which is the so-called partitioned diagonal extraction operators. …”
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Machine learning techniques for reference evapotranspiration and rice irrigation requirements prediction: a case study of Kerian irrigation scheme, Malaysia by Mohd Nasir, Muhammad Adib, Harun, Sobri, Zainuddin, Zaitul Marlizawati, Kamal, Md Rowshon, Che Rose, Farid Zamani

“…Two machine learning algorithms, named Support Vector Regression (SVR) and Random Forest (RF), were applied to predict ETo and rice irrigation requirements using only climatic data (rainfall, temperature, relative humidity, and wind speed). …”
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