Search Results - (( issues affecting selection 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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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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A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm
Published 2014“…The effective and efficient test case selection from the existing test suite becomes very critical issue in regression testing. …”
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An empirical study of double-bridge search move on subset feature selection search of bees algorithm
Published 2017“…This creates a heavy computational time, and in the same time could affect the overall accuracy subset selection.To rectify this issue, a double-bridge move proposed and benchmark dataset have been used to determine the performance of the proposed method. …”
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Mobile data gathering algorithms for wireless sensor networks
Published 2014“…In this algorithm, the user has to tune an appropriate variable which directly affects the power consumption and the data gathering latency. …”
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Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…Outlier detection and classification are critical issues that affect prediction accuracy if not handled correctly. …”
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Maximizing Lifetime of Homogeneous Wireless Sensor Network through Energy Efficient Clustering Method
Published 2010“…Energy efficiency is a very important issue for sensor nodes which affects the lifetime of sensor networks. …”
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Citation Index Journal -
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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. Although GA is successfully improved BPNN learning, there are still some issues such as longer training time to produce the output and usage of complex functions in selection, crossover and mutation calculation. …”
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Optimal QoS aware multiple paths web service composition using heuristic algorithms and data mining techniques
Published 2014“…Furthermore, prioritizing the selected QoS criteria is suggested in order to assist clients when choosing the right criteria. …”
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An Improved Diabetes Risk Prediction Framework : An Indonesian Case Study
Published 2018“…Pre-processing resolves the issue of missing data and hence normalizes the data.Outlier treatment employs k-mean clustering to validate the class.Suitable components were selected through comparison of classifier algorithms and feature selection.Attribute weighting based feature selection was selected for assigning weightage.Weighted risk factor was used on training dataset in order to improve accuracy and computation time of the prediction. …”
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An improved energy-efficient clustering protocol to prolong the wireless sensor network lifetime
Published 2021“…Lastly, cluster heads (CHs) are selected in optimal locations with the rotation of the CH function among members of the cluster based on a new CH selection-rotation algorithm by combining a back-off timer mechanism for CH selection and rotation mechanism for CH rotation. …”
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A Continuous Overlay Path Probing Algorithm For Overlay Networks
Published 2013“…Such an in-band probing algorithm reduces measurement overhead on the selected overlay path. …”
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