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1
An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Various classification algorithms have been developed to produce classification models with high accuracy. …”
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2
A conceptual model for the E-commerce application recommendation framework using exploratory search
Published 2024journal::journal article -
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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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4
Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network
Published 2024“…It was shown that our proposed model exhibits stronger search ability compared to other metaheuristic algorithms and Exhaustive Search. …”
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5
Solving SVM model selection problem using ACOR and IACOR
Published 2013“…In applying ACO for optimizing SVM parameters which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretize process would result in loss of some information and hence affect the classification accuracy.In order to enhance SVM performance and solving the discretization problem, this study proposes two algorithms to optimize SVM parameters using Continuous ACO (ACOR) and Incremental Continuous Ant Colony Optimization (IACOR) without the need to discretize continuous value for SVM parameters.Eight datasets from UCI were used to evaluate the credibility of the proposed integrated algorithm in terms of classification accuracy and size of features subset.Promising results were obtained when compared to grid search technique, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM. …”
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6
Solving Support Vector Machine Model Selection Problem Using Continuous Ant Colony Optimization
Published 2013“…Ant Colony Optimization has been used to solve Support Vector Machine model selection problem.Ant Colony Optimization originally deals with discrete optimization problem.In applying Ant Colony Optimization for optimizing Support Vector Machine parameters which are continuous variables, there is a need to discretize the continuously value into discrete value.This discretize process would result in loss of some information and hence affect the classification accuracy and seeking time.This study proposes an algorithm that can optimize Support Vector Machine parameters using Continuous Ant Colony Optimization without the need to discretize continuous value for Support Vector Machine parameters.Eight datasets from UCI were used to evaluate the credibility of the proposed hybrid algorithm in terms of classification accuracy and size of features subset.Promising results were obtained when compared to grid search technique, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.…”
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7
Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection
Published 2020“…We model the recently established feature selection method, competitive binary grey wolf optimizer (CBGWO), into a continuous version (CGWO), which enables it to perform the search on continuous search space. …”
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Incremental continuous ant colony optimization technique for support vector machine model selection problem
Published 2012“…Ant Colony Optimization has been used to solve Support Vector Machine model selection problem.Ant Colony Optimization originally deals with discrete optimization problem. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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11
An efficient anomaly intrusion detection method with feature selection and evolutionary neural network
Published 2020“…A proposed model has been practically used to the problem of intrusion detection as well as been validated using the NSL-KDD dataset. …”
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12
Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…Hence, a methodological approach that could provide the solution is essential to reduce the misplaced issues and thus reduce the problem in searching the products in a large-scale setting. …”
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13
Ringed seal search for global optimization via a sensitive search model / Younes Saadi
Published 2018“…The proposed algorithm is characterized by a search model namely the sensitive search model, where the exploitation-exploration is adaptively balanced. …”
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14
Recommendation System Model For Decision Making in the E-Commerce Application
Published 2024thesis::doctoral thesis -
15
Parametric modelling of twin rotor system using chaotic fractal search algorithm
Published 2016“…This paper presents the application of enhanced Fractal Search algorithms with chaos in parametric modelling of a twin rotor system (TRS). …”
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16
Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems
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17
Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm
Published 2021“…This article presents a new modified cuckoo search algorithm with dynamic discovery probability and step-size factor for optimizing the Bouc–Wen Model in magnetorheological damper application. …”
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Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…This project can be improved by making a comparative study on Artificial Immune System and other techniques or algorithms used to solve dengue classification problems.…”
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19
Electricity demand forecasting in Turkey and Indonesia using linear and nonlinear models based on real-value genetic algorithm and extended Nelder-Mead local search
Published 2014“…The actual electricity demand data of Turkey and Indonesia were used in the experiments to evaluate the performance of the proposed model. Results of the proposed model were compared to the hybrid GA and Nelder-Mead local search, Real Code Genetic Algorithm and Particle Swarm Optimisation. …”
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20
A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting
Published 2020“…Hence, to enhance the search ability of Cuckoo Search, it is integrated with Bat algorithm that offers a balanced search between global and local. …”
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