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Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System
Published 2021“…Several combinations of Harmony search algorithm, genetic algorithm, and particle swarm optimization algorithm are examined with K-means for feature selection. …”
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…In summary, this study advances the field by delivering an effective, optimized predictive algorithm for early heart disease detection, thereby offering valuable insights that could enhance healthcare outcomes, support proactive cardiovascular risk management, and pave the way for future innovations in personalized medicine…”
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol
Published 2023“…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 -
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Predicting bankruptcy using ant colony optimization / Nur Syafiqah Abdul Ghani
Published 2021“…In model development, Ant-Miner was used which consists of three steps. In model validation, to quantify accuracy by approving the informational collection, Ant Colony Optimization Algorithm was used and it was compared with the J48 algorithm. …”
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Student Project -
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Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana
Published 2018“…Most of researches in IDS which use k-centroids-based clustering methods like K-means, K-medoids, Fuzzy, Hierarchical and agglomerative algorithms to baseline network traffic suffer from high false positive rate compared to signature-based IDS, simply because the nature of these algorithms risk to force some network traffic into wrong profiles depending on K number of clusters needed. …”
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Metacarpal phantom radiograph edge detection using genetic algorithm gradient based genotype / Norharyati Md Ariff
Published 2007“…For the image segmentation, genetic algorithm are use to segment the bone image and it is a new method that applies in the image processing field. …”
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7
Early detection of dengue disease using extreme learning machine
Published 2018“…This study will use the Extreme Learning Machine (ELM) method to classify the dengue by using the clinical data so that first aid can be given which can decrease some death risk. …”
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Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…Also, six techniques: Ant Colony Optimization (ACO), Gain Ratio (GR), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), Random forest (RF), and Correlation-based Feature Selection (CFS) were used for the feature selection. …”
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9
A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah
Published 2022“…Finally, the proposed algorithm’s effectiveness regarding node coverage, energy consumption, Pareto-optimal value, and algorithm execution time is validated using three Pareto-optimal metrics: including inverted generation distance (IGD), hypervolume, and diversity. …”
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10
A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks
Published 2022“…Finally, the proposed algorithm's effectiveness regarding node coverage, energy consumption, Pareto-optimal value, and algorithm execution time is validated using three Pareto-optimal metrics: including inverted generation distance (IGD), hypervolume, and diversity. …”
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Detection of black hole attacks in mobile ad hoc networks via HSA-CBDS method
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Book Chapter -
13
Route optimization security in mobile IPv6 wireless networks: a test-bed experience
Published 2008“…This algorithm is able to detect and prevent the attacker from modifying the data with using an encryption algorithm by cost of little bit increase but tolerable delay. …”
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CT reconstruction algorithm and low contrast detectability of phantom study: a systematic review and meta-analysis
Published 2022“…Methods: In this study, a systematic review and a meta-analysis study were conducted on CT phantom for resolution study especially based on the low contrast detectability (LCD). …”
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Security enhancement of route optimization in mobile IPv6 networks
Published 2008“…This algorithm is able to detect and prevent the attacker from modifying the data with using an encryption algorithm by cost of little bit increase but tolerable delay. …”
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Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm
Published 2025“…The central purpose of this research is to significantly increase the predictability of these milestone dates, thereby eliminating the risks associated with high and dynamic fluctuations in schedules. …”
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Bioelectrical impedance analysis-derived phase angle as a pragmatic screening tool for assessing sarcopenia in multi-ethnic peritoneal dialysis patients
Published 2024“…Sarcopenia was assessed using Asian Working Group for Sarcopenia (AWGS) 2019 diagnostic algorithm. …”
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Integrating Information Gain and Chi-Square for Enhanced Malware Detection Performance
Published 2025“…Recent studies have shown that this challenge can be addressed by employing machine learning algorithms for detection. Some studies have also implemented various feature selection methods to optimize detection efficiency. …”
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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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Groundwater quality assessment and optimization of monitored wells using multivariate geostatistical techniques in Amol-Babol Plain, Iran
Published 2015“…A new optimization approach was proposed for redesign monitoring network wells using optimization algorithm based on the vulnerability of aquifer to contaminations, estimation error of sampling wells, nearest distance between wells, and source of contamination in the study area. …”
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