Search Results - (( parameters deviations based algorithm ) OR ( using classification using algorithm ))
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1
Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…The performance of FESSIC was evaluated against ten benchmark image classification algorithms and six classifiers on four ground-based sky image datasets. …”
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Thesis -
2
HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC
Published 2014“…This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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Final Year Project -
3
On equivalence of FIS and ELM for interpretable rule-based knowledge representation
Published 2023Article -
4
Classification of transient disturbance using Wavelet based support vector machine / Fahteem Hamamy Anuwar
Published 2012“…Cross validation is used to find the best parameters related to kernels used followed by training and testing of the data sets. …”
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Thesis -
5
Intelligent fault diagnosis for broken rotor bar using wavelet packet signature analysis
Published 2016“…The fault detection and classification algorithm is carried out under the unknown dataset and the off-line testing results with 98.8% classification accuracy indicate good reliability of the proposed method in identifying broken rotor bars severity.…”
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Thesis -
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PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems
Published 2016“…Based on the simulated results, MS_ISE has better settling time, lesser peak time, and lower maximum deviation as compared with GA_ISE. …”
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Conference or Workshop Item -
8
Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links
Published 2022“…The quantum calculus provides an extra degree of freedom to search the local and global minima by inducing a q-parameter. Motivated by this fact, a quantum calculus-based noisy links incremental least mean squares (NL-qILMS) algorithm is proposed. …”
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Article -
9
Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm
Published 2018“…In this study, a hybrid of the bat algorithm (BA) and the particle swarm optimization (PSO) algorithm, i.e., the hybrid bat-swarm algorithm (HBSA), was developed for the optimal determination of these four parameters. …”
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10
Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
Published 2018“…The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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11
Evaluation of new rotor angle deviation regulator for synchronous generator using nonlinear swing equation
Published 2024“…In order to obtain stabilization upon rotor angle deviation, a regulator based on the Lypapunov algorithm for a synchronous generator is proposed in this research. …”
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Thesis -
12
Investigation of firefly algorithm and chaos firefly algorithm for load prequency control / Zaid Najid
Published 2015“…In order to obtain the best controller parameter values for LFC, Firefly Algorithm (FA) and Chaos Firefly Algorithm (CFA) are used. …”
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Thesis -
13
Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending
Published 2006“…To validate the finite element model physical experiments were conducted. A neural network algorithm based on the backpropagation algorithm has been developed. …”
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Thesis -
14
On the problem formulation for parameter extraction of the photovoltaic model: novel integration of hybrid evolutionary algorithm and Levenberg Marquardt based on adaptive damping...
Published 2022“…This paper presents an approach to determine the nine parameters of the three diode (TD) PV model based on the integration of the guaranteed convergence arithmetic optimization algorithm and Levenberg-Marquardt with adaptive damping nonlinear parameter method named as GCAOAAdLM. …”
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Article -
15
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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Thesis -
16
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…The comparison showed that, the accuracy of the unsupervised classification map with value of 88.4% that was generated by using the cluster labelling algorithm was slightly more than the maximum-likelihood supervised classification map with value of 87.5%. …”
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17
ABC: android botnet classification using feature selection and classification algorithms
Published 2017“…The Information Gain algorithm is used to select the most significant permissions, then the classification algorithms Naïve Bayes, Random Forest and J48 used to classify the Android apps as botnet or benign apps. …”
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18
An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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Thesis -
19
Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor
Published 2019“…Thehighest accuracy for classification map of Gunung Basor is by using maximum likelihood algorithm with an accuracy of 82.90%. …”
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Undergraduate Final Project Report -
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Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA)
Published 2024“…Competency of the proposed algorithm in generating the optimal parameters for TEMs was appraised based on 21 benchmarked design parameters, following the objective of root mean square error (RMSE) minimization between the temperature of both actual and estimated models. …”
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