Search Results - (( java application mining algorithm ) OR ( changes evaluation machine 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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Postsurgery classification of best-corrected visual acuity changes based on Pterygium Characteristics using the Machine Learning Technique
Published 2021“…Conclusion. Machine learning algorithms can produce a highly accurate postsurgery classification model of BCVA changes using pterygium characteristics.…”
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Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram
Published 2021“…The parameters involved to estimate the mangrove age are differences feature selection and different supervised machine learning algorithm. The support vector machine (SVM) which is one of the machines learning algorithms for object-based image analysis (OBIA) method is used in this study for the classification of the mangrove from other LULC. …”
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Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions
Published 2024“…Furthermore, the taxonomy was used to evaluate the most recent machine learning algorithm and analysis. …”
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Advanced machine learning algorithm to predict the implication of climate change on groundwater level for protecting aquifer from depletion
Published 2025“…Ultimately, the results obtained in this study serve as a great benchmark for future GWL prediction using LSTM and XGBoost algorithm and give an insight into the influence of climate change on future GWL. …”
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Extreme learning machine classification of file clusters for evaluating content-based feature vectors
Published 2018“…The methods are Byte Frequency Distribution, Entropy, and Rate of Change. Consequently, an Extreme Learning Machine (ELM) neural network algorithm is used to evaluate the performance of the three methods in which it classifies the class label of the feature vectors to JPEG and Non-JPEG images for files in different file formats. …”
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Classification of JPEG files by using extreme learning machine
Published 2018“…The algorithm automatically classifies the files based on evaluation measures of three methods Entropy, Byte Frequency Distribution and Rate of Change. …”
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Intelligent Manufacturing Planning System Using Dispatch Rules: A Case Study in Roofing Manufacturing Industry
Published 2022“…Tests based on real data have been set up to evaluate the performance of the proposed algorithm in sorting the received orders. …”
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Refinement of Tuned Mass Damper parameters on machine support structure using dynamic Cuckoo Search algorithm
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Adaptive intelligence job online scheduling within dynamic grid environment based on gridsim
Published 2008“…The idea behind the adaptive job scheduling algorithm is the hybrid algorithms that consist of Ant Colony Optimization (ACO) and Tabu algorithms. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…Algorithmic level based methods however are based on introducing new optimization task to improve the minority class classification rate, without changing the data characteristics. …”
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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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Combination of perturb and observe with online sequential extreme learning machine for photovoltaic system maximum power point tracking
Published 2018“…From different MPPT techniques previously proposed, the online sequential extreme learning machine algorithm and conventional perturb and observe are combined together as a proposed MPPT algorithm. …”
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