Search Results - intelligence system ((research algorithm) OR (svm algorithm))

Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

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Intrusion Detection Systems, Issues, Challenges, and Needs by Aljanabi, Mohammad, Mohd Arfian, Ismail, Ali, Ahmed Hussein

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Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

“…By implementing soft computing techniques in data mining especially in HR field can enhance the knowledge discovery process for intelligent decision system. Support Vector Machine (SVM) is among the popular learning algorithm for classification in soft computing techniques. …”
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Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions by Kalantari, Ali, Kamsin, Amirrudin, Shamshirband, Shahaboddin, Gani, Abdullah, Alinejad-Rokny, Hamid, Chronopoulos, Anthony T.

“…On the other hand, the hybridization of SVM with other methods such as SVM-Genetic Algorithm (SVM-GA), SVM-Artificial Immune System (SVM-AIS), SVM-AIRS and fuzzy support vector machine (FSVM) had great performances achieving better results in terms of accuracy, sensitivity and specificity.…”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

“…The FSR-AIRS2 is a new hybrid algorithm that incorporates the FRA, RRC, and the SVM into AIRS2 in order to produce a stronger classifier. …”
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Ozone Concentration Forecasting Based on Artificial Intelligence Techniques: A Systematic Review by Yafouz A., Ahmed A.N., Zaini N., El-Shafie A.

A preliminary lightweight random forest approach-based image classification for plant disease detection by Mashitah Ibrahim, Muzaffar Hamzah, Mohammad Fadhli Asli

“…Random Forest is a special kind of ensemble learning technique and it turns out to perform very well compared to other classification algorithms such as Support Vector Machines (SVM) and Artificial Neural Networks (ANN). …”
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Applications of machine learning to friction stir welding process optimization by Nasir, Tauqir, Asmaela, Mohammed, Zeeshan, Qasim, Solyali, Davut

“…Machine learning (ML) is a branch of artificial intelligent which involve the study and development of algorithm for computer to learn from data. …”
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Artificial Intelligence (AI) to predict dental student academic performance based on pre-university results by Ahmad Amin, Afifah Munirah, Abdullah, Adilah Syahirah, Lestari, Widya, Sukotjo, Cortino, Utomo, Chandra Prasetyo, Ismail, Azlini

“…Classifiers employed for the system include Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and Support Vector Machine (SVM) techniques. …”
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Prognostic Health Management of Pumps Using Artificial Intelligence in the Oil and Gas Sector: A Review by Aliyu, R., Mokhtar, A.A., Hussin, H.

“…In comparison to the algorithmic approach, the data approach has not received significant research attention. …”
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Intelligent decision support systems: transforming smart cities management by Ahmed, Zeinab E., Hassan Abdalla Hashim, Aisha, Mokhtar, Rania A., Saeed, Mamoon M.

“…A comparison of the energy used by promised by these algorithms including LSTM, SVM, KNN, and the OPTIMUS, a system is developed that enables smart cities to significantly save energy hence highlighting its efficiency. …”
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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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Feature extraction and supervised learning for volatile organic compounds gas recognition by Mohd Tombel, Nor Syahira, Mohd Zaki, Hasan Firdaus, Mohd Fadglullah, Hanna Farihin

“…A preliminary dataset was used to predict VOC classification through the application of five supervised machine learning algorithms: k-Nearest Neighbors (kNN), Random Forest (RF), Support Vector Machines (SVM), Logistic Regression (LR), and Artificial Neural Networks (ANN). …”
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Big data analytics and classification of cardiovascular disease using machine learning by Narejo, S., Shaikh, A., Memon, M.M., Mahar, K., Aleem, Z., Zardari, B.

“…Living in an advanced era full of intelligent systems, the increasing number of deaths can be reduced. …”
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Big data analytics and classification of cardiovascular disease using machine learning by Narejo, S., Shaikh, A., Memon, M.M., Mahar, K., Aleem, Z., Zardari, B.

“…Living in an advanced era full of intelligent systems, the increasing number of deaths can be reduced. …”
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Time series data intelligent clustering algorithm for landslide displacement prediction by Han, Liu, Shang, Tao, Shu, Jisen, Khan Chowdhury, Ahmed Jalal

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Acoustic Emission and Artificial Intelligent Methods in Condition Monitoring of Rotating Machine – A Review by Yasir , Hassan Ali, Salah, M. Ali, Roslan, Abd Rahman, Raja Ishak, Raja Hamzah

“…Furthermore, the paper attempts to summarize and evaluate the recent condition monitoring research that utilizing AI includes fuzzy logic, artificial neural network (ANN), support vector machine (SVM), and genetic algorithms (GA) in fault diagnosis, fault classification, fault localization and fault size estimation in gear and bearing based on features extraction from AE signal. …”
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Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui by Muhammad Faisal , Siddiqui

“…Complex multiplier, complex matrix multiplier and pseudo-inverse modules are designed according to the algorithmic needs to increase the efficiency of the system. …”
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Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation by Illias, Hazlee Azil, Wee, Zhao Liang

“…In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. …”
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Development of colorization of grayscale images using CNN-SVM by Abualola, Abdallah, Gunawan, Teddy Surya, Kartiwi, Mira, Ambikairajah, Eliathamby, Habaebi, Mohamed Hadi

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