Search Results - (( subset selection process algorithm ) OR ( using optimization method algorithm ))

Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences by Rajesvary Rajoo R., Salam R.A.

Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…One of the main steps after the data collection stage of any method is selecting a subset of the features to be used for the feature selection process. …”
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Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This paper presents two intelligent algorithms that hybridized between ant colony optimization (ACO) and SVM for tuning SVM parameters and selecting feature subset without having to discretize the continuous values. …”
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Automated recognition of Ficus deltoidea using ant colony optimization technique by Ishak, Asnor Juraiza, Che Soh, Azura, Marhaban, Mohammad Hamiruce, Khamis, Shamsul, Ghasab, Mohammad Ali Jan

“…At first, through image processing specified features are extracted from the Ficus deltoidea leaves such as vein, morphology and texture features and they construct a search space to be chosen for the optimal subset features that is selected by ACO algorithm as support vector machine (SVM) classify them. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through the use of Backtracking Search Algorithm (BSA) as an efficient optimization algorithm in learning process of ANFIS approach. …”
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

“…To achieve this goal, an improved Teaching Learning-Based Optimization (ITLBO) algorithm was proposed in dealing with subset feature selection. …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

“…Optimization algorithms are widely used for the identification of intrusion. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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A meta-heuristic algorithm for the minimal high-quality feature extraction of online reviews by Mat Zin, Harnani, Mustapha, Norwati, Azmi Murad, Masrah Azrifah, Mohd Sharef, Nurfadhlina

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Plant leaf recognition algorithm using ant colony-based feature extraction technique by Ghasab, Mohammad Ali Jan

“…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
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Two-stage feature selection using ranking self-adaptive differential evolution algorithm for recognition of acceleration activity by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Mohamed, Raihani

“…Consequently, this paper proposes a ranking self-adaptive differential evolution (rsaDE) feature selection algorithm. The proposed algorithm is capable of selecting the optimal feature subsets while improving the recognition of acceleration activity using a minimum number of features. …”
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Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem

“…A multi-objective feature selection approach comprises of multi-objective binary-valued backtracking search algorithm (MOBBSA) as an efficient evolutionary search algorithm and ANFIS method is developed in this paper to extract the most influential subsets of input variables with maximum relevancy and minimum redundancy. …”
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A Meta-heuristic Algorithm for the Minimal High-Quality Feature Extraction of Online Reviews by Mat Zin, Harnani, Mustapha, Norwati, Azmi Murad, Masrah Azrifah, Mohd Sharef, Nurfadhlina

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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

“…Cuckoo search), and evaluator or model inducing algorithms (e.g SVM) were utilized for feature subset selection, which further compared to select the optimal conditioning factors subset. …”
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Bat algorithm for rough set attribute reduction by Taha A.M., Tang A.Y.C.

“…AR techniques have recently attracted attention due to its importance in many areas such as pattern recognition, machine learning and signal processing. In this paper, a new optimization method has been introduced called bat algorithm for attribute reduction (BAAR), the proposed method is based mainly on the echolocation behavior of bats. …”

Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

“…Then, the proposed FS methods are employed to select the most informative feature subset. …”
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A Novel Feature Selection Method for Classification of Medical Data Using Filters, Wrappers, and Embedded Approaches by Saba Bashi, Irfan Ullah Khattak, Aihab Khan, Farhan Hassan Khan, Abdullah Gani, Muhammad Shiraz

“…For this purpose, the proposed research focused on analyzing and identifying effective feature selection algorithms. A novel framework is proposed which utilizes different feature selection methods from filters, wrappers, and embedded algorithms. …”
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