Search Results - (( parallel segmentation model algorithm ) OR ( java application mining algorithm ))
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Direct approach for mining association rules from structured XML data
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Thesis -
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Efficient hardware design for palm-dorsa vein image enhancement
Published 2018“…For hardware design of thinning, parallel pipelined with Concurrent Condition Check Unit hardware architecture has been developed to enable the parallelism of the thinning algorithm. …”
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4
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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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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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Existing literature relies on offline trained models or incremental learning models. The former suffers from partially or fully outdated knowledge after drift occurrence, and the latter suffers from the constraints of the pre-defined hyper-parameter of the model. …”
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Thesis -
10
Hybrid intelligent methods for parameter identification and load frequency control in power system
Published 2014“…For example, the classical methods for parameter identification (LSE and MLE), the classical methods for LFC (PI, PD and PID) and the intelligent methods (fuzzy logic, neural network, genetic algorithm, and PSO). Thus, motivated from the topics, this Thesis is brought to present the improvement of the parameter identification of power system model and the response of the LFC in power system. …”
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