Search Results - (( variable using optimization algorithm ) OR ( based applications classification algorithm ))
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1
Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
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2
Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…For this purpose, we implemented four types of variable length meta-heuristic searching algorithms, namely VLBHO-Fitness, VLBHO-Position, variable length particle swarm optimization (VLPSO) and genetic variable length (GAVL), and we compared them in terms of classification metrics. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…For this purpose, we implemented four types of variable length meta-heuristic searching algorithms, namely VLBHO-Fitness, VLBHO-Position, variable length particle swarm optimization (VLPSO) and genetic variable length (GAVL), and we compared them in terms of classification metrics. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…For this purpose, we implemented four types of variable length meta-heuristic searching algorithms, namely VLBHO-Fitness, VLBHO-Position, variable length particle swarm optimization (VLPSO) and genetic variable length (GAVL), and we compared them in terms of classification metrics. …”
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5
Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…This optimization problem has a number of characteristics that make it challenging: it has many local minimum, the optimization variables can be either continuous or categorical, and there are no exact analytical derivatives. …”
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6
Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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Image-based air quality estimation using convolutional neural network optimized by genetic algorithms: A multi-dataset approach
Published 2025“…These improvements underscore the effectiveness of Genetic Algorithms in optimizing the model.…”
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9
Modeling forest fires risk using spatial decision tree
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10
Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012“…The ARTMAP system is dependent on training sequence presentation to determine the effectiveness of the learning processes, as well as the strength of the biasing parameter, lambda λ. The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. …”
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11
A Comparative Performance Analysis of Gaussian Distribution Functions in Ant Swarm Optimized Rough Reducts
Published 2011“…This paper proposed to generate solution for Particle Swarm Optimization (PSO) algorithms using Ant Colony Optimization approach, which will satisfy the Gaussian distributions to enhance PSO performance. …”
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12
An evolutionary based features construction methods for data summarization approach
Published 2015“…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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Research Report -
13
A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping
Published 2014“…An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications. …”
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14
Statistical band selection for descriptors of MBSE and MFCC-based features for accent classification of Malaysian English / Yusnita M. A. ...[et al.]
Published 2013“…A simple algorithm to select bands so called statistical band selection (SBS) method using smallest variances within class scores was developed to optimize the presentation of speech features. …”
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15
Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration
Published 2014“…LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. …”
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16
Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients
Published 2017“…This is followed by the clustering of the liver tissues using particle swarm optimized spatial FCM algorithm. …”
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17
Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm
Published 2019“…The results include flood probabilities and prediction analysis using proposed algorithm.…”
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Proceeding Paper -
18
Study of hand gesture recognition using impulse radio ultra wideband (IRUWB) radar sensor
Published 2023“…Seven classification algorithms (K-Nearest Neighbour, Logistic Regression, Naive Bayes, Gradient Boosting, AdaBoost, Bagging, and Linear Discriminant Analysis) were meticulously explored for hand gesture recognition. …”
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19
Variable Global Optimization min-sum (VGOMS) algorithm of decode-and forward-protocol for the relay node in the cooperative channel
Published 2020“…In this study, a straightforward Particle Swarm Optimization approach was used to determine the optimal scaling factor to obtain optimized error corrective performance of the algorithm. …”
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Variable Global Optimization min-sum (VGOMS) algorithm of decodeand-forward protocol for the relay node in the cooperative channel
Published 2019“…In this study, a straightforward Particle Swarm Optimization approach was used to determine the optimal scaling factor to obtain optimized error corrective performance of the algorithm. …”
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