Search Results - (( developing learning elements algorithm ) OR ( java application mining algorithm ))
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Direct approach for mining association rules from structured XML data
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…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
Published 2007“…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
Published 2022“…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
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Virtual reality in algorithm programming course: practicality and implications for college students
Published 2024“…Overall, the VR products developed have proven to be practical and effective in learning programming algorithms. …”
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Particle swarm optimization for neural network learning enhancement
Published 2006“…All these elements will affect the speed of neural network learning. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…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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Performance of correlational filtering and deep learning based single target tracking algorithms / ZhongMing Liao and Azlan Ismail
Published 2023“…Therefore, reviewing the visual target tracking algorithms based on deep learning from different perspectives is important. …”
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Differential evolution for neural networks learning enhancement
Published 2008“…These elements will affect the speed of neural network learning. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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Forecasting of photovoltaic output using hybrid particle swarm optimization-artificial neural network model / Muhamad Faizol Adli Abdullah
Published 2010“…These entire elements will affect the speed of natural network learning. …”
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Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu
Published 2005“…The project used Back-propagation Neural Network for the algorithm to classified images. Images that capture using digital camera will perform through the algorithm to classified images. …”
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K-means Clustering Analysis for EEG Features of Situational Interest Detection in Classroom Learning
Published 2021“…This paper proposes a method to detect situational interest in classroom learning using k-means algorithms. The developed algorithm in this paper had been tested on features from ten students who experienced mathematics learning in a classroom. …”
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Implementing Aproiri Algorithm for Predicting Result Analysis
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Implementing Aproiri Algorithm for Predicting Result Analysis
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Campus study buddy : collaborative learning and resource sharing app
Published 2024“…The application is developed using Flutter and uses a tag recommendation algorithm to push content that users may be interested in, thereby intelligently providing users with an online learning environment that suits them and improving their learning efficiency. …”
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Final Year Project / Dissertation / Thesis -
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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…The results are used to develop the hybrid learning algorithm based on the AdaBoost, Bagging, and RUSBoost methods to predict the damage in the tower based on dynamic frequency domain. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…The reason is that, SRT algorithm is sensitive to the accuracy of the learned preferences while MGT algorithm can generate Pareto-optimal offers even with an approximation of the learned preferences.…”
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