Search Results - (( structures vector learning algorithm ) OR ( java application path algorithm ))

Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

“…In creating this application, NetBeans IDE 6.5and Java Micro Edition (Java ME) are used. …”
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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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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…The experimental results demonstrate that the proposed algorithm is competitive compared to the state-of-the-art semi-supervised learning algorithms in terms of accuracy. …”
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Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

“…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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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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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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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.

A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classification by Madanan M., Gunasekaran S.S., Mahmoud M.A.

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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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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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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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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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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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.

“…There are many known machine learning algorithms for character recognition, but not all can classify Chinese characters with high speed and accuracy. …”

Integration of GWO-LSSVM for time series predictive analysis by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Bariah, Yusob, Ernawan, Ferda

“…The emergence of Statistical Learning Theory (SLT) based algorithm namely Least Squares Support Vector Machines (LSSVM) has evidenced its efficacy in solving regression and classification problems. …”
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A Constrained Optimization based Extreme Learning Machine for noisy data regression by Yuong Wong S., Siah Yap K., Jen Yap H.

Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms by Ziyad Sami B.H., Ziyad Sami B.F., Kumar P., Ahmed A.N., Amieghemen G.E., Sherif M.M., El-Shafie A.

“…In this research, machine learning algorithms including regression models, tree regression models, support vector regression (SVR), ensemble regression (ER), and gaussian process regression (GPR) were utilized to predict the compressive and tensile concrete strength. …”

Web service applications and consumer environments based on ICT-driven optimization by Fan, Chaozhi, Law, Siong Hook, Ibrahim, Saifuzzaman, Ahmad, Mohd Naseem

“…Therefore, this paper proposes a service recommendation model based on the hybrid embedding of multiple networks and designs a multinetwork hybrid embedding recommendation algorithm. First, the user social relationship network and the user service heterogeneous information network are constructed; then, the embedding vectors of users and services in the same vector space are obtained through multinetwork hybrid embedding learning; finally, the representation vectors of users and services are applied to recommend services to target users. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

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