Search Results - (( using solution based algorithm ) OR ( quality classification based algorithm ))
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Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems
Published 2015“…This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions.The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems
Published 2015“…The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions. …”
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Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection
Published 2022“…The first modification enhances the initial population of the MBGWO using a heuristic based Ant Colony Optimisation algorithm. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…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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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms
Published 2018“…The latter drawbacks are consequences of the difficulty in balancing the exploration and exploitation processes which directly affect the final quality of the clustering solutions. Hence, this research has proposed three enhanced frameworks, namely, Optimized Gravitational-based (OGC), Density-Based Particle Swarm Optimization (DPSO), and Variance-based Differential Evolution with an Optional Crossover (VDEO) frameworks for data clustering. …”
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An enhanced soft set data reduction using decision partition order technique
Published 2017“…Furthermore, the decomposition based on previous algorithms could not achieve better parameter reduction in available domain space. …”
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An improved genetic-fuzzy system for classification and data analysis
Published 2017“…In addition, feature-based selection method applied in the second variant classifier allowed this method to successfully obtain high-quality solutions as it has consistently achieved the best error rates for all the data sets compared to the original method and the first variant classifier.…”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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Enhancement Of Cover Selection – Based Audio Steganography (CAS) Using Block-Based Chaotic Multi – Level Lsb (BCM– LSB) For Balanced Performance
Published 2024thesis::doctoral thesis -
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Poverty risk prediction based on socioeconomic factors using machine learning approach
Published 2025“…This study seeks to develop a predictive model of measuring poverty risk using socioeconomic factors based on a machine learning framework. …”
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Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…The performance of most metaheuristic algorithms depends on parameters whose settings essentially serve as a key function in determining the quality of the solution and the efficiency of the search. …”
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Underwater Image Recognition using Machine Learning
Published 2024“…Machine Learning is the branch of Artificial Intelligence in which a computer is fed with data and based on that data it tries to find out solution on its own. …”
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Stage of maturity banana fruit classification using image processing / Nadia Kasim ... [et al.]
Published 2019“…This study attempted to propose a system that uses image processing to detect the maturity stage of banana based on its color and size using Support Vector Machine (SVM) learning algorithm. …”
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Minimizing the number of stunting prevalence using the euclid algorithm clustering approach
Published 2023“…Superior and quality human resources are based on healthy human resources with indicators of adequate nutritional intake according to age development. …”
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Footwear quality evaluation using decision tree and logistic regression models
Published 2022“…The objectives of the study are to determine the rank factors that affect the quality of footwear using decision tree methods. Then, various types of decision trees and logistic regression model are developed to gain the best classification model for predicting footwear quality performance. …”
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Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying
Published 2019“…An ensemble of these algorithms is an intelligent and adaptive solution, producing a clean output, while preserving significant pixel information. …”
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An enhanced gated recurrent unit with auto-encoder for solving text classification problems
Published 2020“…Classification has become an important task for categorizing documents automatically based on their respective groups. …”
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