Search Results - (( developing local evolution algorithm ) OR ( java implementation mining algorithm ))
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Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Thesis -
2
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Scalable approach for mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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4
Mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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5
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 -
6
A refined differential evolution algorithm for improving the performance of optimization process
Published 2011“…Among the latest Evaluation Algorithm (EA) have been developed is Differential Evolution (DE). …”
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Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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8
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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9
Differential evolution for neural networks learning enhancement
Published 2008“…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
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10
Selective harmonic elimination in cascaded H-bridge multilevel inverter using hybrid APSO algorithm / Mudasir Ahmed
Published 2019“…The simulation results show that the proposed algorithm calculates highly precise firing angles in less number of iterations with the very high capability of tackling the local optima then Bee Algorithm (BA), differential evolution (DE), GA and PSO. …”
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11
Seed disperser ant algorithm for optimization / Chang Wen Liang
Published 2018“…The Seed Disperser Ant Algorithm (SDAA) is developed based on the evolution or expansion process of Seed Disperser Ant (Aphaenogaster senilis) colony. …”
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12
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…Differential evolution (DE) is a simple yet powerful evolutionary algorithm (EA). …”
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13
Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)
Published 2019“…The results demonstrated the superiority of the IABO-trained algorithm in avoiding local minima, convergence speed, and accuracy compared to the benchmarking (BP and PSO) algorithms in water level forecasting tasks.…”
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14
Grey wolf optimization and differential evolution-based maximum power point tracking controller for photovoltaic systems under partial shading conditions
Published 2022“…To track the global maximum peak power (GMPP) instead of local maxima peak power (LMPP), the combination of gray wolf optimization (GWO) and differential evolution (DE) algorithm is hybridized (GWO-DE) in this work. …”
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Crossover and mutation operators of genetic algorithms
Published 2017“…Genetic algorithms (GA) are stimulated by population genetics and evolution at the population level where crossover and mutation comes from random variables. …”
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17
Crossover and mutation operators of genetic algorithms
Published 2017“…Genetic algorithms (GA) are stimulated by population genetics and evolution at the population level where crossover and mutation comes from random variables. …”
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A review on monocular tracking and mapping: from model-based to data-driven methods
Published 2022“…Finally, the popular benchmarks available for developing and evaluating these algorithms are presented along with a comparative study on a different class of algorithms. …”
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Data Management System for Local Entrepreneur
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Final Year Project Report / IMRAD -
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