Search Results - (( programming model normalization algorithm ) OR ( java data selection algorithm ))
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1
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Then canonical Polyadic decomposition-based attribute reduction is applied to the offload-able task to reduce the data size. Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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2
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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3
Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection
Published 2008“…The results also show that in Java, A Arraylist is the most suitable choice for storing Object and Arraylnt list is the most suitablec choice for storing integer data. …”
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4
Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection
Published 2008“…The results also show that in Java, A Arraylist is the most suitable choice for storing Object and Arraylnt list is the most suitablec choice for storing integer data. …”
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5
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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6
Reducing of Inconsistent Data using Fuzzy Multi Attribute Decision Making for Accessing Data from Database
Published 2013“…Sample data was selected for experiments purposes. The result indicates fuzzy multi attribute decision making is a suitable technique in reducing inconsistent data from database. …”
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7
Agent-based extraction algorithm for computational problem solving
Published 2015“…Modeling Computational Problem Solving (CPS) is the main issue in teaching programming where the given text is needed to be transformed into a model then later into a programming language. …”
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8
Statistical approach on grading: mixture modeling
Published 2006“…A solution to this problem is using the Markov Chain Monte Carlo method namely Gibbs sampler algorithm. The Gibbs sampler algorithm is applied using the WinBUGS programming package. …”
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9
Logic Programming In Radial Basis Function Neural Networks
Published 2013“…The analysis revealed that performance of particle swarm optimization algorithm and Prey predator algorithm are better to use in training the networks. …”
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10
Data mining in network traffic using fuzzy clustering
Published 2003“…These various application make it difficult for the network administrator to model certain network traffic. The network traffic model is very important to know whether that particular network traffic is normal or abnormal. …”
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11
Data mining in network traffic using fuzzy clustering
Published 2003“…These various application make it difficult for the network administrator to model certain network traffic. The network traffic model is very important to know whether that particular network traffic is normal or abnormal. …”
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12
Enhanced dynamic security assessment for power system under normal and fake tripping contingencies.
Published 2019“…The hybrid logistic model tree (hybrid LMT) approach proposed in this study combines the symmetrical uncertainties (SU) algorithm and the logistic model tree (LMT) algorithm. …”
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13
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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14
Neural network based model predictive control for a steel pickling process
Published 2009“…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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15
A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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16
Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Fuzzy state space modeling for solving inverse problems in multivariable dynamic systems
Published 2005“…To facilitate the implementation of these algorithms, a semi-automated computational tool using Matlab® programming facilities is developed. …”
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18
Flock optimization algorithm-based deep learning model for diabetic disease detection improvement
Published 2024“…Hence, the research objective is to create an improved diabetic disease detection system using a Flock Optimization Algorithm-Based Deep Learning Model (FOADLM) feature modeling approach that leverages the PIMA Indian dataset to predict and classify diabetic disease cases. …”
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19
Academic Achievement Prediction Model Using Neural Networks
Published 2002“…This model allows the system administrator to train and normalize data as well as trains. …”
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20
Utilizing self-organization systems for modeling and managing risk based on maintenance and repair in petrochemical industries
Published 2018“…In order to evaluate the accuracy of the model, we compare it with the fuzzy model, and the results indicate that self-organizing systems optimized with the genetic algorithm have higher ability, flexibility and accuracy than the fuzzy model in predicting risk.…”
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