Search Results - (( variable integration based algorithm ) OR ( variable detection using algorithm ))
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1
Artificial immune system based on real valued negative selection algorithms for anomaly detection
Published 2015“…With respect to all the algorithms, V-Detector proved to be superior and surpassed all other algorithms based on performance and execution time.…”
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Thesis -
2
Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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3
An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection
Published 2018“…Real-Valued Negative Selection Algorithm with Variable-Sized Detectors (V-Detectors) is an offspring of AIS and demonstrated its potentials in the field of anomaly detection. …”
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4
Haar cascade algorithm for microsleep detection
Published 2025“…Based on these results, future research should focus on enhancing the core algorithm to be more resilient to variable lighting and distance, thereby reducing false positives and negatives. …”
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A real-time integrated fire detection and alarm (FDA) system for network based building automation
Published 2017“…The framework shares information through the algorithm and communicates with each fire alarm panels connected in peer to peer configuration to declare the network state in every second using network address. …”
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A simple model-free butterfly shape-based detection (BSD) method integrated with deep learning CNN for valve stiction detection and quantification
Published 2020“…In most methods for shape-based stiction detection, they rely heavily on the traditional controller output (OP) and process variable (PV) plot (i.e. …”
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Modelling of cupping suction system based on system identification method
Published 2022“…The detection of cupped suction system plants using a standard model based on a modified Sine Cosine Algorithm (mSCA) is presented in this research. …”
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Conference or Workshop Item -
8
HABC: Hybrid artificial bee colony for generating variable T-way test sets
Published 2020“…This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
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HABC: Hybrid artificial bee colony for generating variable T-way test sets
Published 2020“…This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
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10
Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi
Published 2020“…The successfully achieved four set objectives inclusive of (1) a new classification model to detect water leakage, (2) analysis of the effects of leakage size on the variables within a WDS, i.e. flow, pressure, pipe volume, velocity and water demand, (3) locating and specifying the leakage size in the WDS, and (4) evaluate the performance of the designed K-NN algorithm for accurate leak detection. …”
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11
Predicting Cheaters in PlayerUnknown’s Battlegrounds (PUBG) using Random Forest Algorithm
Published 2023“…The primary goal is to use the Random Forest algorithm, an effective machine learning technique, to predict instances of cheating based on the behavioural patterns of participants. …”
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Final Year Project Report / IMRAD -
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An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach
Published 2015“…The proposed scheme integrates an ADS and signature-based detection system (SDS) approach for better and rapid intrusion detection. …”
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13
Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration
Published 2014“…Pearson chi-squared value was used to find the best classification fit between the dependent variable and conditioning factors. …”
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Conference or Workshop Item -
14
Anomaly detection of denial-of-service network traffic attacks using autoencoders and isolation forest
Published 2026“…This paper presents an unsupervised network-based anomaly detection framework that integrates deep autoencoders with the Isolation Forest algorithm. …”
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15
Enhancing safety of micro-mobility and powered mobility devices using YOLOv12-based real-time obstacle detection
Published 2025“…Future work will address lighting variability and braking integration.…”
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Proceeding Paper -
16
Modeling of cupping suction system based on system identification method
Published 2022“…The input and output data were used to create this modeling output variable of the cupping suction system is detected by connecting a differential pressure sensor to the cup, while the input variable is determined by the speed of the pump applied in various locations. …”
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Undergraduates Project Papers -
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Google the earth: what's next?
Published 2010“…Satellite imagery/data can be used for everything from ground truthing and change detection, to more sophisticated analyses, including feature extraction and natural hazard prediction. …”
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Inaugural Lecture -
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients
Published 2017“…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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20
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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