Search Results - (( evolution optimization sensor algorithm ) OR ( features detection model algorithm ))
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1
Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm
Published 2020“…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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2
A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles
Published 2017“…In a previous research, a relocating algorithm for mobile sensor network had been introduced and the goal was to save energy and prolong the lifetime of the sensor networks using Particle Swarm Optimization (PSO) where both of sensing radius and travelled distance had been optimized in order to save energy in long-term and shortterm. …”
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Thesis -
3
Optimised content-social based features for fake news detection in social media using text clustering approach
Published 2025“…The accuracy of fake news detection models relies mainly on the quality of the extracted features and the method used in detection. …”
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4
Design, optimization and fabrication of a climbing six articulated-wheeled robot using artificial evolution and 3D printing
Published 2015“…In this research, an artificial evolution approach utilizing Single-Objective Evolutionary Algorithm (SOEA) and Multi-Objective Evolutionary Algorithm (MOEA) respectively are investigated in the automatic design and optimization of the morphology of a Six Articulated-Wheeled Robot (SAWR) with climbing ability. …”
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5
Feature selection algorithms for Malaysian dengue outbreak detection model
Published 2017“…Based on the selected features, three predictive modeling techniques (J48, DTNB and Naive Bayes) were applied for dengue outbreak detection. …”
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6
An improved gbln-pso algorithm for indoor localization problem in wireless sensor network
Published 2022“…Then, we compared the result with Particle Swarm Optimization (PSO), Differential Evolution Particle Swarm Optimization (DEPSO), Health Particle Swarm Optimization (HPSO) and Global best Local Neigborhood Particle Swarm Optimization (GbLN-PSO) algorithm. …”
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7
Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system
Published 2022“…In future, the HW-DBN algorithm can be proposed as an integrated deep Learning for the classification performance of attack detection models.…”
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SVM for network anomaly detection using ACO feature subset
Published 2016“…But irrelevant and redundant features are the obstacle for classification algorithm to build an efficient detection model. …”
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Conference or Workshop Item -
9
Security alert framework using dynamic tweet-based features for phishing detection on twitter
Published 2019“…This model is then embedded into the detection algorithm together with the inclusion of dynamic tweet-based features which are not as part of the features used to train a classification model for phishing tweet detection. …”
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10
Malware Classification and Detection using Variations of Machine Learning Algorithm Models
Published 2025“…The purpose of the study is to detect, classify malware attacks using a variety of ML Algorithm models such as SVM, KNN and Neural Network and testing detection performance. …”
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11
Automated Face Detection Using Skin Color Segmentation and Viola-Jones Algorithm
Published 2019“…Other color model such as HSV and benchmarked algorithm are having slightly low detection rates due to some false face detection. …”
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Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques
Published 2011“…The transductive conformal prediction and outlier detection have been employed for feature selection algorithm. …”
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13
K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm
Published 2025“…This research utilises the web page phishing detection dataset, which consists of 11,430 URLs with 87 features. …”
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An enhanced binary bat and Markov clustering algorithms to improve event detection for heterogeneous news text documents
Published 2022“…To address such a problem, this research presents an enhanced ED model that includes improved methods for the crucial phases of the ED model such as Feature Selection (FS), ED, and summarization. …”
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15
Extremal region detection and selection with fuzzy encoding for food recognition
Published 2019“…Three algorithms were used to accomplish the task of feature representation. …”
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16
Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms
Published 2022“…The machine learning models employed automated features selection with hybrid two metaheuristics algorithms namely particle swarm optimization (PSO) and genetic algorithm (GA). …”
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Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms
Published 2022“…The machine learning models employed automated features selection with hybrid two metaheuristics algorithms namely particle swarm optimization (PSO) and genetic algorithm (GA). …”
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A YOLO-based deep learning model for Real-Time face mask detection via drone surveillance in public spaces
Published 2024“…A data augmentation algorithm is used for feature generation to enhance the model’s training robustness. …”
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Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin
Published 2022“…The objective of this project is to develop the Windows malware detection model using supervised machine learning in Decision Tree, K-NN and Naïve Bayes, to evaluate the performance of malware detection in term of testing and training of the features selection and to compare the accuracy detection model in all three machine learning algorithms. …”
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Student Project -
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Bayesian Network Classifiers for Damage Detection in Engineering Material
Published 2007“…The methodology used in the thesis to implement the Bayesian network for the damage detection provides a preliminary analysis used in proposing a novel fea- ture extraction algorithm (f-FFE: the f-folds feature extraction algorithm). …”
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Thesis
