Search Results - (( developing refined learning algorithm ) OR ( java application mining algorithm ))

Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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A web-based implementation of k-means algorithms by Lee, Quan

“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Refinement of generated weighted fuzzy production rules by using fuzzy neural networks for stock market prediction. by Md. Sap, Mohd. Noor, Khokar, Rashid Hafeez

“…In this paper, we look into the solutions of the above problems by 1) enhancing the representation power of WFPRs by including local and global weights, 2) developing a fuzzy neural network (FNN) with enhanced learning algorithm, and 3) using this FNN to refine the local and global weights of WFPRs for stock market prediction. …”
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Development of a scaled conjugate gradient algorithm for significant RF neural signal processing by Mohd Norden, Muhammad Farid Akmal, Mohd Isa, Roshakimah, Mohd Isa, Mohd Roshalizi, S. Abdul Kadir, Ros Shilawani, Md Azli, Muhammad Hariz, Muhammad Akram, Amir Syarif

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Hotel recommendation system using machine learning by Wong, Wai On

“…There are three objectives in the study, which is to perform data preprocessing on the Google Reviews dataset for hotels in Perak using an instant data scraper, to develop three suitable machine learning models on the cleaned dataset and evaluate their performance, and to propose a recommendation system based on the developed machine learning models. …”
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Isolated digit speech recognition in Malay language using Neuro-Fuzzy approach by Sabah, R., Ainon, R.N.

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Prediction of COVID-19 outbbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman by Mohd Azman, Muhammad Qayyum

“…This research significantly contributes to the understanding of machine learning applications in the context of COVID-19 outbreak prediction, emphasizing the importance of algorithm and configuration selections for robust forecasting. …”
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Product design and development strategies for an automated Printed Circuit Board (PCB) defects detection systems by Kamaruddin, Shafie, Shamsulamri, Saiffaqrullah, Sharwazi, Muhammad Haziq Fakhri, Suhaimi, Muhammad Harith Ikhmal, Mohamad, Muhamad Ariff Othmani, Sukindar, Nor Aiman, Ahmad Azhar, Ahmad Zahirani

“…This work aims to design and develop a low-cost, automated PCB defects detection system utilizing modern machine learning methods. …”
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Smart Glove for Sign Language Translation by Ahmad Imran, Mohd Thaim, Norazlianie, Sazali, Kadirgama, Kumaran, Ahmad Shahir, Jamaludin, Faiz, Mohd Turan, Norhaida, Ab. Razak

“…Key objectives include designing a lightweight and ergonomic glove prototype, developing machine learning algorithms for sign language recognition, implementing real-time translation capabilities, evaluating the glove's accuracy and usability, and assessing the potential impact on facilitating communication for deaf people. …”
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Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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New bio-inspired barnacle optimizers based least-square support vector machine for time-series prediction of pandemic outbreaks by Marzia, Ahmed

“…Lastly, this study model various factors influencing the transmission dynamics of COVID-19 within the BMO and GBO variants, refining their predictive ability. The study demonstrates GBO's superiority over previous algorithms, including BMO and its variants, and other established methods. …”
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Face recognition using eigenfaces and smooth support vector machine by Mhd, Furqan

“…Support Vector Machine (SVM) is a new algorithm of data mining technique, recently received increasing popularity in machine learning community. …”
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Windows-Based bandwidth allocation on optical networks by Mahadevan, V., Yu, W., Zhou, J.

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Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer by Dele-Afolabi T.T., Ahmadipour M., Azmah Hanim M.A., Oyekanmi A.A., Ansari M.N.M., Sikiru S., Kumar N.

“…The presence of MWCNTs in the Sn-5Sb solder alloy significantly prevented IMC formation at the interface and enhanced the shear strength, according to empirical observations, which were supported by the excellent properties of MWCNTs. An extreme learning machine (ELM) prediction approach refined by Aquila optimizer (AO), a new cutting-edge metaheuristic optimization algorithm was utilized to develop a prediction model for the performance assessment of the developed solder composites. …”