Search Results - (( parameter classification system algorithm ) OR ( using solution mining algorithm ))
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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…The model limitation is in retraining for new knowledge with changes in the power system network topology and lacks robustness. This current study proposes an intelligent data mining approach for the Machine Learning- Adaptive Distance Relay (ML-ADR) fault classification model using novel extracted 1-cycle transient voltage and current signals hidden knowledge from both healthy and faulty lines parameters. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…In this paper, an improved intrusion detection algorithm for multiclass classification was presented and discussed in detail. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023Subjects:Conference Paper -
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An accurate infant cry classification system based on continuos hidden Markov model
Published 2023Subjects:Conference Paper -
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Adaptive parameter control strategy for ant-miner classification algorithm
Published 2020“…This paper presents a new hybrid Ant-Miner classification algorithm and ant colony system (ACS), called ACS-Ant Miner. …”
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…FESSIC outperforms other algorithms for average classification accuracy for the KSVM, MLP, RF and DT classifiers. …”
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Fuzzy modeling using Bat Algorithm optimization for classification
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Accelerated mine blast algorithm for ANFIS training for solving classification problems
Published 2016“…Mine Blast Algorithm (MBA) is newly developed metaheuristic technique. …”
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Affect classification using genetic-optimized ensembles of fuzzy ARTMAPs
Published 2015“…In addition, manual design of classification tasks often uses sub-optimum classifier parameter settings, leading to average classification performance. …”
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Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength
Published 2015“…Many researchers have trained ANFIS parameters using metaheuristic algorithms but very few have considered optimizing the ANFIS rule-base. …”
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An Ar Natural Marker Similarities Measurement Algorithm For E-Biodiversity
Published 2018“…The objective of this research is to comparatively evaluate the effectiveness of different algorithms, method combination procedure, and their parameters towards classification accuracy. …”
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Development of an intelligent prediction tool for rice yield based on machine learning techniques
Published 2006“…Support vector machine algorithm is developed for classification of rice plantation data. …”
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Using the bees algorithm to optimise a support vector machine for wood defect classification
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A numerical method for frequent pattern mining
Published 2009“…The PC_Miner algorithm traverses the PC_Tree by using an efficient pruning technique. …”
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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah
Published 2021“…To improve the performance from current systems, this work has investigation on different of image pre-processing enhancement technique to support accuracy on deep learning for DR classification. …”
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee
Published 2023“…By integrating with the HS (or GSA) algorithm, the proposed metaheuristic neural networks (i.e., RBFN-DDA-HS and RBFN-DDA-GSA) can optimize the RBFN-DDA parameters and improve classification performances from the original RBFN-DDA up to 28.69% in two benchmarks datasets, which are numerical records from a bearing and steel plate system and a condition-monitoring system in a power plant (i.e., the circulating water (CW) system). …”
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Classification System for Wood Recognition using K-Nearest Neighbor with Optimized Features from Binary Gravitational Algorithm
Published 2014“…The project proposes a classification system using Gray Level Co-Occurrence Matrix (GLCM) as feature extractor, K-Nearest Neighbor (K-NN) as classifier and Binary Gravitational Search Algorithm (BGSA) as the optimizer for GLCM’s feature selection and parameters. …”
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