Search Results - (( using deviation 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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Article -
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A Standard Deviation Selection in Evolutionary Algorithm for Grouper Fish Feed Formulation
Published 2016“…Results shown that the fitness of standard deviation selection in evolutionary algorithm is applicable. …”
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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 -
8
A standard deviation selection in evolutionary algorithm for grouper fish feed formulation
Published 2016“…Malaysia is one of the major producer countries for fishery production due to its location in the equatorial environment.Grouper fish is one of the potential markets in contributing to the income of the country due to its desirable taste, high demand and high price.However, the demand of grouper fish is still insufficient from the wild catch.Therefore, there is a need to farm grouper fish to cater to the market demand.In order to farm grouper fish, there is a need to have prior knowledge of the proper nutrients needed because there is no exact data available.Therefore, in this study, primary data and secondary data are collected even though there is a limitation of related papers and 30 samples are investigated by using standard deviation selection in Evolutionary algorithm.Thus, this study would unlock frontiers for an extensive research in respect of grouper fish feed formulation.Results shown that the fitness of standard deviation selection in evolutionary algorithm is applicable.The feasible and low fitness, quick solution can be obtained. …”
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Conference or Workshop Item -
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Grouper fish feed formulation using enhanced evolutionary algorithm with fibonacci rabbit initialization and binary-standard deviation tournament selection
Published 2023“…The main contribution of this research is the development of feed formulation using Evolutionary Algorithm (EA) with four variations of EA, which are Semi-Random Initialization – Binary Tournament Selection - EA (SR-BT-EA), Fibonacci Rabbit Initialization – Binary Tournament Selection - EA (FR-BT-EA), Semi-Random Initialization - Binary- Standard Deviation Tournament Selection - EA (SR-SD-EA) and Fibonacci Rabbit Initialization - Binary-Standard Deviation Tournament Selection - EA (FR-SD-EA). …”
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Thesis -
10
Fault diagnostic algorithm for precut fractionation column
Published 2004“…Hazard and Operability Study (HAZOP) is used to support the diagnosis task. The algorithm has been successful in detecting the deviations of each variable by testing the data set. …”
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11
Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…In this respect, we propose to incorporate our proposed DRBLTS in the bootstrap model selection technique. We also proposed to use an alternative robust location and scale estimates which are less affected by outliers instead of using the classical mean and classical standard deviation. …”
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Thesis -
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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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Thesis -
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Optimal input features selection of wavelet-based EEG signals using GA
Published 2004“…A combination of genetic algorithm (GA) and artificial neural network (ANN) are used to select the relevant features. …”
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…The ant colony optimisation (ACO) algorithm have been used to select feature subset. …”
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Thesis -
15
Development of a rule-based fault diagnostic advisory system for precut fractionation column
Published 2005“…The advisory system algorithm used process history based method and presented by rule-based approach. …”
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Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending
Published 2006“…The training data required to train the two-metamodeling techniques were generated using a verified nonlinear finite element algorithm developed in the current research. …”
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Fault diagnostic advisory system using moving-range chart and hazard operability study.
Published 2007“…Firstly, a plant model was simulated by using commercial HYSYS. PlantTM stimulator. Moving-Range (x-MR) Chart and (HAZOP) study were used to define the causes and consequences of process deviation based on selected parameter for each study node. …”
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The Development of an Algorithm to Determine Axial Capacity of Piles from SPT N-Values
Published 2000“…The combined calibrated formulae (The Algorithm) were later tested using five static loading test results. …”
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Thesis -
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Penalized LAD-SCAD estimator based on robust wrapped correlation screening method for high dimensional models
Published 2021“…The widely used least absolute deviation (LAD) estimator with the smoothly clipped absolute deviation (SCAD) penalty function (abbreviated as LAD-SCAD) is known to produce corrupt estimates in the presence of outlying observations. …”
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Article -
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Fault diagnostic advisory system using moving-range chart and hazard operability study
Published 2007“…Firstly, a plant model was simulated by using commercial HYSYS. PlantTM simulator. Moving-Range (x-MR) Chart and HAZOP study were used to define the causes and consequences of process deviation based on selected parameter for each study node. …”
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