Search Results - (( effective classification system algorithm ) OR ( using function method algorithm ))
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1
Breast cancer disease classification using fuzzy-ID3 algorithm based on association function
Published 2022“…The FID3-AF algorithm is a hybridisation of the fuzzy system, the iterative dichotomizer 3 (ID3) algorithm, and the association function. …”
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2
Classification of Mammogram Images Using Radial Basis Function Neural Network
Published 2020“…This paper presents the classification method for mammogram Image using Radial Basis Function Network (RBF) technique. …”
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Book Chapter -
3
Logistic regression methods for classification of imbalanced data sets
Published 2012“…This thesis aims to develop the simple and effective imbalanced classification algorithms by previously improving the algorithms performance of general classifiers i.e. …”
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4
Feature fusion using a modified genetic algorithm for face and signature recognition system
Published 2015“…Several approaches and benchmark data were used to validate the effectiveness of the proposed method compared to the unimodal system and normal feature selection method. …”
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5
A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…One of these tools is Artificial Immune Recognition System (AIRS), which has been used increasingly. Results of AIRS have shown its potential for classification purposes. …”
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6
Modified anfis architecture with less computational complexities for classification problems
Published 2018“…Furthermore, researchers have mainly used metaheuristic algorithms to avoid the problem of local minima in standard learning method. …”
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7
Improved GART neural network model for pattern classification and rule extraction with application to power systems
Published 2023“…To assess the effectiveness of IGART and to compare its performances with those from other methods, three datasets that are related to power systems are employed. …”
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8
Measuring height of high-voltage transmission poles using unmanned aerial vehicle (UAV) imagery
Published 2023“…Aerial photography; Classification (of information); Cost effectiveness; Electric power transmission; Graphic methods; Object detection; Poles; Remote sensing; Stereo image processing; Vehicle transmissions; Depth Map; Disparity map; Global information systems; Graph cut; High voltage transmissions; Ortho-rectification; Remote sensing applications; Stereo matching algorithm; Unmanned aerial vehicles (UAV)…”
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9
Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…Five state-of-the-art FS methods are used to evaluate the effectiveness of proposed methods in this work. …”
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10
Genetic algorithms-based quality of service service selection in cloud computing using multilayer perceptron
Published 2014“…The attribute selection method is based genetic algorithms (GA) and is designed to rank the cloud services before the attributes are being fed into a multi-layer perceptron (MLP) classification system. …”
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11
Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield.
Published 2005“…At the core of our system is a method for unsupervised partitioning of data for finding spatio-temporal patterns in climate data using kernel methods which offer strength to deal with complex data non-linearly separable in input space. …”
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12
Leveraging CQT-VMD and pre-trained AlexNet architecture for accurate pulmonary disease classification from lung sound signals
Published 2025“…The results, showing high accuracy, a sensitivity of 91.21%, and a specificity of 94.9%, highlight the robustness and effectiveness of the proposed method, paving the way for its clinical adoption and the development of lightweight deep-learning algorithms for portable diagnostic tools.…”
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13
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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14
Task-state EEG signal classification for spatial cognitive evaluation based on multiscale high-density convolutional neural network
Published 2022“…The MHCNN classification method proposed in this research could be used as an effective biological indicator of spatial cognitive training effect and could be extended to other brain function evaluations.…”
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15
Odour based human identification and classification using neural networks
Published 2019“…The unsurpassed framework for algorithm learning to be used for human identification can be back propagation learning algorithm named the Levenberg-Marquardt. …”
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16
Hybrid conjugate gradient using exact line search in photovoltaic system / Muhammad Ariiq Iqbaal Azizul Firdaus
Published 2025“…There are a few classifications of CG method such as classical, hybrid, three-term and parametric CG methods. …”
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17
A framework for predicting oil-palm yield from climate data
Published 2006“…At the core of our system is a method for unsupervised partitioning of data for finding spatio-temporal patterns in climate data using kernel methods which offer strength to deal with complex data. …”
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18
Measuring height of high-voltage transmission poles using unmanned aerial vehicle (UAV) imagery
Published 2017“…Results were compared with well-known algorithms; including, for example, global and local stereo matching algorithms. …”
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19
A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. …”
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20
Enhanced Reinforcement Learning Model for Extraction of Objects in Complex Imaging
Published 2022“…The visualization and classification of the area of interest in any picture is therefore an important function in order to segment the image. We examine a variety of image segmentation algorithms and give our reinforcement learning algorithm that uses Deep Convolutional Neural Networks for the detection of irregular objects, which has been tested on four datasets. …”
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