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Electricity Price Prediction with Support Vector Machine and Bacterial Foraging Optimization Algorithm for Day-Ahead model by Intan Azmira W.A.R., Ahmad A., Abidin I.Z., Yap K.S., Nasir M.N.M., Upkli W.R.

Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

“…In this project, Support Vector Machines (SVM) is studied and experimented by the implementation ofa textual extractor. …”
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Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

“…In this project, Support Vector Machines (SVM) is studied and experimented by the implementation ofa textual extractor. …”
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Protein structure prediction using robust principal component analysis and support vector machine by Zakaria, Nur Aini, Ali Shah, Zuraini, Kasim, Shahreen

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Extreme learning machine classification of file clusters for evaluating content-based feature vectors by Ali, Rabei Raad, Mohamad, Kamaruddin Malik, Jamel, Sapiee, Ahmad Khalid, Shamsul Kamal

“…Consequently, an Extreme Learning Machine (ELM) neural network algorithm is used to evaluate the performance of the three methods in which it classifies the class label of the feature vectors to JPEG and Non-JPEG images for files in different file formats. …”
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CHINESE CHARACTER RECOGNITION USING SUPPORT VECTOR MACHINE by Baharum A., Ismail R., Wahab S.H.A., Deris F.D., Noor N.A.M., Kasihmuddin M.S.M.

“…Therefore, this paper proposes recognizing Chinese characters using support vector machines. Support vector machines are a classification of two classes widely used in classification. …”

Implementation of advanced techniques in production and manufacturing sectors through support vector machine algorithm with embedded system by Rayner Alfred, Narender Chinthamu, T. Jayanthy, Elangovan Muniyandy, Tarun Kumar Dhiman, Nimmy John T.

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A Hybrid of Functional Networks and Support Vector Machine Models for the Prediction of Petroleum Reservoir Properties by Fatai Adesina, Anifowose, Jane, Labadin, Abdulazeez, Abdulraheem

“…This paper presents an innovative hybrid of Functional Networks and Support Vector Machines (FN-SVM) as an improvement over an existing Functional Networks and Type-2 Fuzzy Logic (FN-T2FL) hybrid model. …”
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Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

“…To bridge this gap, a five-phase research methodology is structured to propose and evaluate an algorithm enabling the external modification of LLM-generated word vectors using scalar values as the focus weightage. …”
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A WEB-BASED SYSTEM FOR THE PREDICTION OF STUDENT PERFORMANCE IN UPCOMING PUBLIC EXAMS BASED ON ACADEMIC RECORDS by DELLON, NELSON BRUNNIE

“…Teachers will be able to precisely forecast their students' impending grades utilizing the system's web-based application integration and machine learning algorithms. The machine learning algorithms that will be used and compared are Support Vector Machines (SVM), Random Forest (RF), K-Nearest Neighbors (KNN), Artificial Neural Network (ANN), and Linear Regression (LR). …”
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Hybrid Algorithm for Hand Gesture Recognition by Gupta, Shikha, Jaafar, J., Wan Ahmad, Wan Fatimah

“…For the classification purpose Support vector machine has been used as a classifier.…”
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Machine learning methods for multi-rotor UAV structural damage detection based on MEMS sensor by Ma, Y., Mustapha, F., Ishak, M.R., Abdul Rahim, S., Mustapha, M.

“…An independent data acquisition device with a Micro Electro Mechanical Systems (MEMS) sensor is designed and fixed onto the multi-rotor UAVs to acquire the vibration data. Four machine learning algorithms, namely Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Decision Tree, and Random Forest, are employed for damage detection. …”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

“…After evaluating the results of these algorithms, a hybrid Artificial Neural Network-based Imperial Competitive Algorithm (ANN-ICA) was presented in the deployment step of the proposed methodology to identify the structural damage of illustrative structures. …”
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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.

Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…The selected features are then fed into a linear support vector machine (SVM) for classification. The experimental results show that the proposed feature selection framework performed better when compared to other state-of-the-art feature selection algorithms. …”
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Reduced torque ripple and switching frequency using optimal DTC switching strategy for open-end winding induction machines by Abd Rahim, Muhd Khairi

“…This thesis proposes an optimal DTC switching strategy to reduce torque ripple and switching frequency for open-end winding induction machines. The open-end winding induction machine is supplied by a dual-inverter which can offer a greater number of voltage vectors and hence, gives more options to select the most optimal voltage vectors to minimize the problems. …”
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Exploring brain structure differences and male/female classification: a machine learning study on Huffaz and non-Huffaz by Sapuan, Abdul Halim, Abdul Majid, Zafri Azran, Mohd Tamrin, Mohd Izzuddin, Che Azemin, Mohd Zulfaezal

“…This study investigates the potential of machine learning (ML) to classify sex based on brain structural features, incorporating the unique perspective of cognitive training through Quran memorization. …”
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A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classification by Madanan M., Gunasekaran S.S., Mahmoud M.A.

Improved Direct Torque Control (DTC) Performances Of Induction Machine Using Cascaded H-Bridge Multilevel Inverter by Ramahlingam, Sundram

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Prediction of lattice constant of pyrochlore compounds using optimized machine learning model by Mohamad Zamri, Isma Uzayr, Abd Rahman, Mohd Amiruddin, Bundak, Caceja Elyca

“…In this study, we used an optimized machine learning technique based on Particle Swarm Optimization-Support Vector Regression (PSO-SVR) to learn the relationship between its structural properties with its lattice constants. …”
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