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1
Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…To achieve this goal, an improved Teaching Learning-Based Optimization (ITLBO) algorithm was proposed in dealing with subset feature selection. …”
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Thesis -
2
A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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3
The influence of sentiments in digital currency prediction using hybrid sentiment-based Support Vector Machine with Whale Optimization Algorithm (SVMWOA)
Published 2021“…Support Vector Machine (SVM) technique is used with the Whale Optimization Algorithm (WOA) which is inspired by the swarm optimization algorithms. …”
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Proceeding Paper -
4
Leachate generation rate modeling using artificial intelligence algorithms aided by input optimization method for an MSW landfill
Published 2019“…These models included Artificial Neural Network (ANN)-Multi-linear perceptron (MLP) with single and double hidden layers, and support vector machine (SVM) regression time series algorithms. Various performance measures were applied to evaluate the developed model’s accuracy. …”
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5
Kinect-based human gait recognition using locally linear embedded and support vector machine
Published 2018“…Next, the extracted gait features were then optimized using LLE known as DG-LLE and further classified by multi-class SVM with Error Correcting Output Code (ECOC) algorithm. …”
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6
Mutable composite firefly algorithm for gene selection in microarray based cancer classification
Published 2022“…The results showed that the CFS-MCFA-SVM algorithm outperforms benchmark methods in terms of classification accuracy and genes subset size. …”
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Thesis -
7
Time series predictive analysis based on hybridization of meta-heuristic algorithms
Published 2018“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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8
Time series predictive analysis based on hybridization of meta-heuristic algorithms
Published 2018“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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9
Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer
Published 2023“…This algorithm named JAABC5ROC is the enhancement of Artificial Bee Colony (ABC) variant, JA-ABC5 by combining with Rate of Change (ROC)\. …”
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Thesis -
10
Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set
Published 2022“…The algorithms involved were K-Nearest Neighbor (KNN), Naïve Bayers, J48, Support Vector Machine (SVM), Sequential Minimal Optimization (SMO) and Multilayer Perceptron (MLP). …”
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Final Year Project / Dissertation / Thesis -
11
Radiomics analysis and supervised machine learning model for classification of cervical cancer images using diffusion weighted imaging-MRI
Published 2024“…Additionally, the SVM algorithm was evaluated based on its performance across different DWI bvalues, aiming to optimize scanning time. …”
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Thesis -
12
Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques
Published 2011“…The results show that proposed method provides an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.…”
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13
Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation
Published 2009“…A useful property of the statistical classifier like Bayesian is that, it is optimal in the sense that it minimizes the expected mis classification rate. …”
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Thesis -
14
Improved Direct Torque Control (DTC) Performances Of Induction Machine Using Cascaded H-Bridge Multilevel Inverter
Published 2017“…The proposed DTC control algorithm can be optimally executed at high computation rate by totally using C-coding with DS1104 controller board. …”
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Thesis -
15
Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques
Published 2011“…The results show that proposed method provides an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.…”
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Hospital site suitability assessment using three machine learning approaches: evidence from the Gaza strip in Palestine
Published 2021“…Identification of the most significant parameters (conditioning factors) that influence a suitable hospital location was achieved by employing correlation-based feature selection (CFS) with the search algorithm (greedy stepwise). …”
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Article -
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Improved Manta Ray Foraging Optimizer-based SVM for Feature Selection Problems: A Medical Case Study
Published 2024“…In this paper, the MRFO + SVM algorithm is introduced by investigating the recent manta ray foraging optimizer to fine-tune the SVM parameters and identify the optimal feature subset simultaneously. …”
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Article -
19
STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION
Published 2021“…In this paper, we proposed profound learning strategy to address three primary assignments developing in the zone of skin lesion picture preparation, i.e., dermoscopic highlight, extraction and detection. A profound algorithm comprising of preprocessing in CIELAB color space and Delaunay triangulation based clustering along with Particle Swarm Optimization (PSO) is proposed for the segmentation. …”
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Article -
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Rao-SVM machine learning algorithm for intrusion detection system
Published 2020“…Most of the intrusion detection systems are developed based on optimization algorithms as a result of the increase in audit data features; optimization algorithms are also considered for IDS due to the decline in the performance of the human-based methods in terms of their training time and classification accuracy. …”
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