Search Results - (( variable activation genetic algorithm ) OR ( java implementation mining algorithm ))
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1
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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3
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
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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7
Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approach
Published 2016“…The results are then compared with branch and bound method and simulated annealing algorithm and it is found the proposed genetic algorithm can provide results with better quality. …”
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8
Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…On the other hand, the superior performance of the genetic algorithm that implements an extended diversity control mechanism demonstrates that more competent genetic algorithms can be designed through customized operators. …”
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9
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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10
Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models
Published 2019“…Finally, this research concluded that a genetic algorithm is useful for selecting input variables in oil palm production. …”
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11
Bees algorithm for Forest transportation planning optimization in Malaysia
Published 2021“…Examples of algorithm that are finding their way to the forest transportation planning problem include Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm, Simulated Annealing (SA) algorithm and Tabu Search (TS) algorithm. …”
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12
Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…The performance of ANNs depend on many factors, including the network structure, the selection of activation function, the learning rate of the training algorithm, and initial synaptic weight values, the number of input variables, and the number of units in the hidden layer. …”
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13
An evolutionary based features construction methods for data summarization approach
Published 2015“…In the process of summarizing relational data, a genetic algorithm is also applied and several feature scoring measures are evaluated in order to find the best set of relevant constructed features. …”
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Research Report -
14
A high-performance democratic political algorithm for solving multi-objective optimal power flow problem
Published 2025“…Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”
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15
Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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16
DESIGN AND IMPLEMENTATION OF INTELLIGENT MONITORING SYSTEMS FOR THERMAL POWER PLANT BOILER TRIPS
Published 2011“…The encoding and optimization process using genetic algorithms has been applied successfully. …”
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17
Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…Modeling of hydrological process has been increasingly complicated since we need to take into consideration an increasing number of descriptive variables. In recent years soft computing methods like fuzzy logic and genetic algorithm are being used in modeling complex processes of hydrologic events. …”
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Literature Review of Optimization Techniques for Chatter Suppression In Machining
Published 2011“…In this paper, it can be observed that for chatter suppression, optimization focuses on spindle design, tool path, cutting process, and variable pitch. Various algorithms can be applied in the optimization of machining problems; however, Differential Evolution is the most appropriate for use in chatter suppression, being less time consuming, locally optimal, and more robust than both Genetic Algorithms, despite their wide applications, and Sequential Quadratic Programming, which is a famous conventional algorithm.…”
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20
A high-performance democratic political algorithm for solving multi-objective optimal power flow problem
Published 2024“…Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”
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