Search Results - (( using evolutionary based algorithm ) OR ( learning classification using algorithm ))
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1
Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…As a family of evolutionary based algorithm, the effectiveness of Genetic Programming in providing the best machine learning pipelines for a given problem or dataset is substantially depending on the algorithm parameterizations including the mutation and crossover rates. …”
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2
Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…As a family of evolutionary based algorithm, the effectiveness of Genetic Programming in providing the best machine learning pipelines for a given problem or dataset is substantially depending on the algorithm parameterizations including the mutation and crossover rates. …”
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3
Sentiment analysis using negative selection algorithm for Twitter’s messages / Nazirah Che Alhadi
Published 2012“…In order to develop this model classification and prototype, 480 Twitter’s messages were used as training data and 120 Twitter’s messages for testing data to determine the accuracy of the classification model. …”
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4
Hyper-heuristic framework for sequential semi-supervised classification based on core clustering
Published 2020“…This article presents a prominent framework that integrates each of the NN, a meta-heuristic based on evolutionary genetic algorithm (GA) and a core online-offline clustering (Core). …”
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5
Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…The first improvement includes using Elite Opposition-Based Learning (EOBL) at initialization phase of WOA. …”
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An efficient anomaly intrusion detection method with evolutionary neural network
Published 2020“…The third proposed method is a new Evolutionary Neural Network (ENN) algorithm with a combination of Genetic Algorithm and Multiverse Optimizer (GAMVO) as a training part of ANN to create efficient anomaly-based detection with low false alarm rate. …”
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7
An evolutionary based features construction methods for data summarization approach
Published 2015“…A data summarization approach is proposed due to its capability to learn data stored in multiple tables. In other words, this research will discuss the application of genetic algorithm to optimize the feature construction process from the Coral Reefs data to generate input data for the data summarization method called Dynamic Aggregation of Relational Attributes (DARA). …”
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8
Differential evolution for neural networks learning enhancement
Published 2008“…These algorithms have widely been used to optimize the learning mechanism of classifiers, particularly on Artificial Neural Network (ANN) Classifier. …”
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9
Feature selection optimization using hybrid relief-f with self-adaptive differential evolution
Published 2017“…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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10
An ensemble of neural network and modified grey wolf optimizer for stock prediction
Published 2019“…Widespread models like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Evolutionary Strategy (ES) and Population-Based Incremental Learning (PBIL) dealing with the specified problems are also explored and compared. …”
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11
Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Published 2023“…Two main aspects are used to classify the evolutionary algorithm variants: population-based and evolutionary strategies (variation and replacement). …”
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Towards Software Product Lines Optimization Using Evolutionary Algorithms
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Efficient transmission based on genetic evolutionary algorithm
Published 2022“…Through the simulation of the transmission performance of genetic optimization algorithm, the comparison of transmission energy consumption between GA and evolutionary algorithm is analyzed, and the evolutionary algorithm with higher transmission performance is obtained. …”
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Proceedings -
14
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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Case Slicing Technique for Feature Selection
Published 2004“…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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16
Reservoir operation based on evolutionary algorithms and multi-criteria decision-making under climate change and uncertainty
Published 2018“…Results showed the volume of water to be released for the future period, based on all evolutionary algorithms used, was less than for the base period, and the bat algorithm with high-reliability index and low vulnerability index performed better among other evolutionary algorithms.…”
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17
Design of digital circuit structure based on evolutionary algorithm method
Published 2008“…Evolutionary Algorithms (EAs) cover all the applications involving the use of Evolutionary Computation in electronic system design. …”
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Phylogenetic tree classification system using machine learning algorithm
Published 2015“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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Final Year Project Report / IMRAD -
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Hence, this situation is believed in yielding of decreasing the classification accuracy. In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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