Search Results - (( based optimization means algorithm ) OR ( based optimization svm algorithm ))

A hybrid novel SVM model for predicting CO2 emissions using Multiobjective Seagull Optimization by Ehteram M., Sammen S.S., Panahi F., Sidek L.M.

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

“…However, the imbalanced LR-based methods are not extensively developed such as imbalanced SVM-based methods. …”
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Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

“…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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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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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom, Sampe, Jahariah

“…First, the base of the algorithm is developed based on counting the peak of the chewing signal. …”
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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom

“…First, the base of the algorithm is developed based on counting the peak of the chewing signal. …”
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Prediction of photovoltaic system output using hybrid Cuckoo Search Least Square Support Vector Machine / Muhammad Aidil Adha Aziz by Aziz, Muhammad Aidil Adha

“…Therefore, Cuckoo Search Algorithm (CS) is hybrid with LS-SVM in order to optimize the RBF parameters for a better prediction performance. …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms by Mustaffa, Zuriani, Sulaiman, Mohd Herwan, Rohidin, Dede, Ernawan, Ferda, Kasim, Shahreen

“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

“…By using clustering method K-Means, we have found the best center point position to calculate Kernel matrix. at last, we have employed Quantum-behaved Particle Swarm Optimization (QPSO) to get the optimal kernel parameter in the proposed model. …”
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Support vector machine and neural network based model for monthly stream flow forecasting by Zaini N., Malek M.A., Yusoff M., Osmi S.F.C., Mardi N.H., Norhisham S.

Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

“…This study proposed a hybrid algorithm, based on Artificial Bee Colony (ABC) and LSSVM, that consists of three algorithms; ABC-LSSVM, lvABC-LSSVM and cmABC-LSSVM. …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms by Zuriani, Mustaffa, M. H., Sulaiman, Rohidin, Dede, Ernawan, Ferda, Shahreen, Kasim

“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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Enhancing time series prediction with Hybrid AFSA-TCN: A unified approach to temporal data and optimization by Nur Alia Shahira, Mohd Zaidi, Zuriani, Mustaffa, Muhammad Arif, Mohamad

“…The study introduces a hybrid model that integrates TCN with Artificial Fish Swarm Algorithm (AFSA), a bio-inspired optimization technique designed to fine-tune TCN parameters. …”
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Short-term PV power forecasting using hybrid GASVM technique by VanDeventer, William, Jamei, Elmira, Thirunavukkarasu, Gokul Sidarth, Seyedmahmoudian, Mehdi, Tey, Kok Soon, Horan, Ben, Mekhilef, Saad, Stojcevski, Alex

“…The GASVM model classifies the historical weather data using an SVM classifier initially and later it is optimized by the genetic algorithm using an ensemble technique. …”
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A study on component-based technology for development of complex bioinformatics software by Ali Shah, Zuraini, Deris, Safaai, Othman, Muhamad Razib, Zakaria, Zalmiyah, Saad, Puteh, Hassan, Rohayanti, Muda, Mohd. Hilmi, Kasim, Shahreen, Roslan, Rosfuzah

“…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
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Comparative Assessment of Improved SVM Method under Different Kernel Functions for Predicting Multi-scale Drought Index by Pande C.B., Kushwaha N.L., Orimoloye I.R., Kumar R., Abdo H.G., Tolche A.D., Elbeltagi A.

Evaluation of deep learning algorithm for inflow forecasting: a case study of Durian Tunggal Reservoir, Peninsular Malaysia by Latif S.D., Ahmed A.N., Sathiamurthy E., Huang Y.F., El-Shafie A.