Search Results - (( variable learning mode 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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Article -
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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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Conference or Workshop Item -
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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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Final Year Project / Dissertation / Thesis -
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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA
Published 2012“…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble 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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The Effects Of Segmenting And Computational Thinking In Digital Video Courseware On Knowledge Achievement, Self-Efficacy And Motivation Among Students With Different Thinking Style...
Published 2023“…This research used a quasi-experimental design using a 2 x 3 factorial. This study's variables include (i) two treatment modes, "DVC: Learner-paced predefined segment (DVC-LS)" and "DVC: System predefined segment (DVC-SS)"; (ii) knowledge achievement, self-efficacy, and motivation; and (iii) thinking style, which includes legislative, executive, and judicial. …”
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Short lead time standard precipitation index forecasting: Extreme learning machine and variational mode decomposition
Published 2025“…Study focus: This study focused on creating a novel hybrid VMD-ELM approach, established by combining the Variational Mode Decomposition (VMD) technique and the Extreme Learning Machine (ELM) algorithm as a preprocessing technique for predicting future droughts. …”
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Air quality forecasting and mapping in Malaysian urban areas: A hybrid deep learning approach
Published 2025text::Thesis -
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Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: a systematic review
Published 2021“…We conducted a systematic review aimed at determining the diagnostic power of rs-fMRI to identify FC abnormalities in the DMN of patients with AD or MCI compared with healthy controls (HCs) using machine learning (ML) methods. Multimodal support vector machine (SVM) algorithm was the commonest form of ML method utilized. …”
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Evaluation of arima and ann stream analytics for air quality monitoring system
Published 2021“…It is observed that the data in MySQL are successfully exported to the R query table based on the similar number of variables between those two tables. The data stored in the query table act as input to the analytics algorithm, which runs in R-server as well. …”
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Thesis -
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Improvement of an integrated global positioning system and inertial navigation system for land navigation application
Published 2012“…The integrated GPSIINS system is able to maintain satisfactory accuracy with the maximum error less than 0.82, 0.78, and 0.83 m for position and 0.0414, 0.0273, and 0.0415 m1s for velocity in all directions during maximum GPS outages of 200 second while it requires less than 9 and 5 seconds for learning mode in position and velocity respectively.…”
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