Search Results - (( data classification system algorithm ) OR ( pattern detection method algorithm ))
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1
Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm
Published 2010“…In this work, we integrate artificial immune algorithm with non-linear classification of pattern recognition and machine learning methods to solve the problem of intrusion detection in network systems. …”
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Citation Index Journal -
2
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In comparison to different single algorithms for feature selection,experimental results show that the proposed ensemble method is able to reduce dimensionality, the number of irrelevant features and produce reasonable classifier accuracy. …”
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Thesis -
3
Swarm negative selection algorithm for electroencephalogram signals classification
Published 2009“…Such automated systems must rely on robust and effective algorithms for detection and prediction. …”
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Article -
4
Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023“…It provides an increased convergence and globally optimized solutions. The algorithm has been tested using actual customer consumption data from SESB. 10 fold cross validation method is used to confirm the consistency of the detection accuracy. …”
Conference Paper -
5
HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC
Published 2014“…This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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Final Year Project -
6
Artificial immune system based on real valued negative selection algorithms for anomaly detection
Published 2015“…Self data are regarded as the normal behavioral pattern of the monitored system. …”
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Thesis -
7
Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi
Published 2017“…This indicates that the performance of KNN is acceptable and promising in this classification problem. Since KNN is the simplest form of artificial intelligence, future work could combine this algorithm with other classification algorithm. …”
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8
Performance of Levenberg-Marquardt neural network algorithm in power quality disturbances classification / Adibah I’zzah Mohamad Kasim
Published 2025“…The increasing complexity of modern power systems necessitates advanced methods for detecting and classifying power quality disturbances (PQDs), which impact system reliability and equipment performance. …”
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9
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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Thesis -
10
HEp-2 cell images classification based on statistical texture analysis and fuzzy logic
Published 2014“…This paper proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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Conference or Workshop Item -
11
A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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Thesis -
12
Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…The algorithm enhances the recognition ability of the system compared to manual extraction and labeling of pattern classes. …”
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Thesis -
13
Neuro fuzzy classification and detection technique for bioinformatics problems
Published 2007“…It is very important to identify new integration of classification or clustering algorithm especially in neuro fuzzy domain as compared to conventional or traditional method. …”
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Book Section -
14
Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant
Published 2007“…In this research, a vision system algorithm has been developed to identify and locate base of young corn trees based upon robot vision technology, pattern recognition techniques, and knowledge-based decision theory. …”
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15
Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions
Published 2019“…Furthermore, the review presents different multiple classifier system design and fusion methods that were recently proposed in literature. …”
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Article -
16
Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq
Published 2024“…In this study, a method for the detection and classification of DR stages is proposed to determine whether it is in any of the non-proliferative stage or the proliferative stage. …”
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Thesis -
17
A hybrid interpretable deep structure based on adaptive neuro‑fuzzy inference system, decision tree, and K‑means for intrusion detection
Published 2022“…For generating an interpretable deep architecture for identifying deep intrusion patterns, this study proposes an approach that combines ANFIS (Adaptive Network-based Fuzzy Inference System) and DT (Decision Tree) for interpreting the deep pattern of intrusion detection. …”
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Article -
18
A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar
Published 2007“…The LVQ network was observed to have poor classification for the VOCs data with classification accuracy percentage below 80%. …”
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Research Reports -
19
Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm
Published 2015“…These classification algorithms are trained using the features extracted from the patient data in order for them to learn the relationship between the features and the end-result (FLD present or absent). …”
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Article -
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