Search Results - (( problem implementation using algorithm ) OR ( parameter classification system algorithm ))
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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Undergraduates Project Papers -
2
Diagnosis of eyesight using Improved Clonal Selection Algorithm (ICLONALG) / Nor Khirda Masri
Published 2017“…This study aims to implement the classification algorithm using the Improved Clonal Selection Algorithm (ICLONALG) to classify the eyesight’s problems. …”
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Thesis -
3
Three-term backpropagation algorithm for classification problem
Published 2006“…Standard Backpropagation Algorithm (BP) is a widely used algorithm in training Neural Network that is proven to be very successful in many diverse application. …”
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol
Published 2023“…Children abandoned in vehicles is a critical issue that has led to numerous fatal injuries worldwide. To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
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Student Project -
6
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Lastly, a new hybrid technique suggests tackling the current image encryption application problem by using the estimated parameters of chaotic systems with an optimization algorithm, the SKF algorithm. …”
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Thesis -
7
An improved back propagation leaning algorithm using second order methods with gain parameter
Published 2018“…It has successfully been implemented in various practical problems. However, the algorithm still faces some drawbacks such as getting easily stuck at local minima and needs longer time to converge on an acceptable solution. …”
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Article -
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Power quality problem classification based on Wavelet Transform and a Rule-Based method
Published 2010“…The simulation produces satisfactory result in identifying the disturbance and proof that it is possible to use this model for power disturbance classification. Since the method can reduce the number of parameters needed in classification, less memory space and computing time are required for its implementation. …”
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Conference or Workshop Item -
9
Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method
Published 2010“…The simulation produces satisfactory result in identifying the disturbance and proof that it is possible to use this model for power disturbance classification. Since the method can reduce the number of parameters needed in classification, less memory space and computing time are required for its implementation. …”
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Conference or Workshop Item -
10
Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method
Published 2010“…The simulation produces satisfactory result in identifying the disturbance and proof that it is possible to use this model for power disturbance classification. Since the method can reduce the number of parameters needed in classification, less memory space and computing time are required for its implementation. …”
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Conference or Workshop Item -
11
Skin Cancer Classification using Convolutional Neural Network with Autoregressive Integrated Moving Average
Published 2021“…Machine Learning (ML) and Deep Neural Network (DNN) based Computer-aided decision (CAD) systems show the effective implementation in solving skin cancer classification problem. …”
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Proceeding -
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Detection of corneal arcus using rubber sheet and machine learning methods
Published 2019“…The elements extracted from the confusion matrix parameters (i.e. accuracy, specificity, sensitivity, AUC, precision and f-score) are used in benchmarking the optimal performance of classification algorithms. …”
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Thesis -
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Spiking Neural Network For Energy Efficient Learning And Recognition
Published 2020“…Therefore, an energy-efficient spiking feedforward computing system is presented to evaluate its performance. Common building blocks and techniques used to implement a spiking neural network are investigated to identify design parameters for hardware-based neuron implementations. …”
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Article -
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Skin Cancer Classification using Convolutional Neural Network with Autoregressive Integrated Moving Average
Published 2021“…Machine Learning (ML) and Deep Neural Network (DNN) based Computer-aided decision (CAD) systems show the effective implementation in solving skin cancer classification problem. …”
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Proceeding -
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Development of drift conversion algorithm for ISFET based pH sensor for continuous measurement system
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Research Report -
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Classification of transient disturbance using Wavelet based support vector machine / Fahteem Hamamy Anuwar
Published 2012“…In this research, two test systems have been used which is IEEE 13 bus system and IEEE 30 bus system for data generations. …”
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Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…The hierarchical fuzzy clustering method developed here is far better than a similar implementation of the hard k-means method. When used for overlapping structures, its performance improves significantly. …”
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Monograph -
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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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Article -
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Generating type 2 trapezoidal fuzzy membership function using genetic tuning
Published 2022“…This paper proposes Genetic tuning process, which is a part of genetic algorithm (GA), to adjust parameters in order to improve the behavior of existing system, especially to enhance the accuracy of the system model. …”
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Article -
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Generating type 2 trapezoidal fuzzy membership function using genetic tuning
Published 2022“…This paper proposes Genetic tuning process, which is a part of genetic algorithm (GA), to adjust parameters in order to improve the behavior of existing system, especially to enhance the accuracy of the system model. …”
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