Search Results - (( quality classification based algorithm ) OR ( variable optimization techniques algorithm ))
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1
A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…Moreover, K-Nearest Neighbor (KNN) classifier was used to evaluate the effectiveness of the features identified by the proposed SCSO algorithm. The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…The improvement process involved segmentation, feature selection and classification techniques. A spatio-statistical optimization technique that combines the Taguchi statistical method and a spatial plateau objective function (POF) was presented to improve the segmentation procedures for building footprint extraction. …”
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3
Feature Ranking Techniques For 3D ATS Drug Molecular Structure Identification
Published 2018“…All the performance is evaluated in term of the number of features selected and classification accuracy. Paired t-test also carry out to further validated the quality of the FEFR based on the classification accuracy performance metric. …”
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4
A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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5
Study of nature inspired computing (NIC) technique for optimal reactive power dispatch problems
Published 2017“…In this research, new nature-inspired meta-heuristic optimization algorithms namely moth-flame optimizer (MFO) and Ant Lion Optimizer (ALO) were implemented to address the optimal reactive power dispatch (ORPD) problems. …”
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Research Report -
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Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…This study compares four machine learning algorithms Logistic Regression, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) in water quality classification based on contaminant parameters. …”
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An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…The algorithm’s performance was compared with other variants of Ant-Miner and state-of-the-art rules-based classification algorithms based on classification accuracy and model complexity. …”
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8
Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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9
Classification model for water quality using machine learning techniques
Published 2015“…This article proposes a suitable classification model for classifying water quality based on the machine learning algorithms. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…Experimental results show that the developed methods and model are able to classify the Harumanis quality with accuracy of 79% using fuzzy classification based on shape and size.…”
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11
A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
Published 2015“…As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. …”
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Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach
Published 2009“…The quality of a given classification technique is measured by the computational complexity, execution time of algorithms, and the number of patterns that can be classified correctly despite any distribution. …”
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13
Performance of Levenberg-Marquardt neural network algorithm in power quality disturbances classification / Adibah I’zzah Mohamad Kasim
Published 2025“…Confusion matrix analysis confirmed the robustness of the LM-based classifier across varying input data ratios. …”
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14
Aco-based feature selection algorithm for classification
Published 2022“…The proposed EGCACO algorithm can be utilised for FS in DNA microarray classification tasks that involve large dataset size in various application domains.…”
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15
Mixed variable ant colony optimization technique for feature subset selection and model selection
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River
Published 2025“…This study combined models such as the artificial neural network (ANN) algorithm with the Firefly algorithm (FA) and Artificial Bee Colony (ABC) optimization techniques for the estimation of monthly SL values in the �oruh River in Northeastern Turkey. …”
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Development Of An Intelligent System For River Water Quality Classification Based On Algae Composition
Published 2006“…Throughout the years, many researches have been conducted on the potential applications of Artificial Intelligence (AI) in the biological monitoring of river quality. This project will provide an overview regarding the feasibility of the application of neural networks for direct classification of river water quality based on algae composition. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…(i) what decision making models and (ii) what computational techniques, provide an optimal manufacturing process planning solution in a multidimensional decision variables space? …”
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20
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…The advantage of the cluster labelling algorithm compared to co-spectral plot and maximum-likelihood classifier was the algorithm provided a rapid production of high accuracy classification map.…”
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