Search Results - (( data relational learning algorithm ) OR ( java application testing algorithm ))*

Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…Iris data set has been taken from UCO machine learning to assist in testing phase. …”
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RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…In these experiments, all the training and testing data are represented as feature vectors. By using the proposed algorithm, the sparse coefficients are learned by exploiting the relationships among different multi-view features and leveraging the knowledge from multiple related tasks. …”
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Dimensionality reduction in data summarization approach to learning relational data by Kheau, Chung Seng, Rayner Alfred, Lau, Hui Keng

“…Based on the experimental results, the DARA algorithm is proven to be very effective in learning relational data. …”
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Analysis of Chinese patents associated with incremental clustering algorithms: A review / Archana Chaudhari by Chaudhari, Archana, Mulay, Preeti, Kumar Tiwari, Amit

“…To achieve learning from such dynamic data sources, incremental clustering algorithms are used mandatorily. …”
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Meta-heuristics and deep learning for energy applications: Review and open research challenges (2018?2023) by Hosseini E., Al-Ghaili A.M., Kadir D.H., Gunasekaran S.S., Ahmed A.N., Jamil N., Deveci M., Razali R.A.

“…The synergy between deep learning and meta-heuristic algorithms presents a promising avenue for tackling the complexities of energy-related modeling and forecasting tasks. …”

Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia by Ahmad, M.T., Qaiyum, S., Alamri, A., Islam, S.

“…In this study we have applied several machine learning algorithms to analyse time-series data related to COVID-19 in Saudi Arabia. …”
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Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia by Ahmad, M.T., Qaiyum, S., Alamri, A., Islam, S.

“…In this study we have applied several machine learning algorithms to analyse time-series data related to COVID-19 in Saudi Arabia. …”
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Java based expert system for selection of natural fibre composite materials by Ahmed Ali, Basheer A., Salit, Mohd Sapuan, Zainudin, Edi Syams, Othman, Mohamed

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Machine learning model for performance prediction in mobile network management / Muhammad Hazim Wahid by Wahid, Muhammad Hazim

“…The methodology includes drive test measurement for data collection, exploratory data analysis, data preparation, and applying machine learning algorithms to predict mobile network performance. …”
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Development of a diversified ensemble data summarization (DDS) tool for learning medical data in a multi relational environment by Rayner Alfred, Leau, Yu Beng, Tan, Soo Fun

“…With this new algorithm, one could facilitate the task of data modelling for data stored in a multi-relational setting by improving the predictive accuracy of the data modelling task. …”
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k-nearest neighbour using ensemble clustering based on feature selection approach to learning relational data by Alfred, Rayner, Shin, Kung Ke, Sainin, Mohd Shamrie, On, Chin Kim, Pandiyan, Paulraj Murugesa, Ag Ibrahim, Ag Asri

“…Due to the growing amount of data generated and stored in relational databases, relational learning has attracted the interest of researchers in recent years.Many approaches have been developed in order to learn relational data.One of the approaches used to learn relational data is Dynamic Aggregation of Relational Attributes (DARA).The DARA algorithm is designed to summarize relational data with one-to-many relations. …”
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Implementation of (AES) Advanced Encryption Standard algorithm in communication application by Moh, Heng Huong

“…The concept of ABS algorithm was firstly studied, including the definition, historical background, and a brief comparison was made between the ABS algorithm with other types of algorithm. …”
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Linear and stratified sampling-based deep learning models for improving the river streamflow forecasting to mitigate flooding disaster by Afan H.A., Yafouz A., Birima A.H., Ahmed A.N., Kisi O., Chaplot B., El-Shafie A.

Bot detection using machine learning algorithms on social media platforms by Gannarapu, Sainath, Dawoud, Ahmed, Ali, Rasha S., Alwan, Ali Amer

“…The components of the study are data, feature selection, and bot detection. The research performs web development and hosting on the collected data with a machine-learning algorithm to perform bot detection in social media networks. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

“…There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
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Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions by Gorment N.Z., Selamat A., Cheng L.K., Krejcar O.

Classification System for Heart Disease Using Bayesian Classifier by Magendram, Anusha

“…This system was developing base on to three main part which is data processing, testing and implementation of the algorithm. In this system a Bayesian algorithm was used in order to implement the system. …”
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Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks by Krishnasamy, Ganesh, Paramesran, Raveendran

“…Recently, considerable advancement has been achieved in semisupervised multitask feature selection methods, which they exploit the shared information from multiple related tasks. Besides, these algorithms have adopted manifold learning to leverage both the unlabeled and labeled data since its laborious to obtain adequate labeled training data. …”
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