Search Results - (( pre evaluation method algorithm ) OR ( fraud detection method algorithm ))

A comparative analysis of anti-phishing website techniques: identifying optimal approaches to enhance cybersecurity by Yau, Jia Xin

“…Consequently, it is critical to identify effective detection techniques for fraudulent websites. The research consists of analysing the characteristics of phishing websites, extracting their essential features using the wrapper method, and classifying websites as phishing or legitimate using supervised and unsupervised learning algorithms. …”
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Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff by Mohd Yusoff, Mohd Izhan

“…The new algorithm is tested on simulated and real data where the results show it is capable of detecting fraud activities. …”
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Fraud detection in telecommunication industry using Gaussian mixed model by Mohd Yusoff, Mohd Izhan, Mohamed, Ibrahim, Abu Bakar, Mohd Rizam

“…In this article, we propose a new fraud detection algorithm using Gaussian mixed model (GMM), a probabilistic model successfully used in speech recognition problem. …”
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Credit Card Fraud Detection Using AdaBoost and Majority Voting by Randhawa, Kuldeep, Loo, Chu Kiong, Seera, Manjeevan, Lim, Chee Peng, Nandi, Asoke K.

“…In this paper, machine learning algorithms are used to detect credit card fraud. Standard models are first used. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

“…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. …”

Improved expectation maximization algorithm for Gaussian mixed model using the kernel method by Mohd Yusoff, Mohd Izhan, Mohamed, Ibrahim, Abu Bakar, Mohd Rizam

“…Finally, for illustration, we apply the improved algorithm to real telecommunication data. The modified method will pave the way to introduce a comprehensive method for detecting fraud calls in future work.…”
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Employing Artificial Intelligence to Minimize Internet Fraud by Wong, E.S.K.

“…Following this, an a ttempt is made to propose using the MonITARS (Monitoring In sider Trading and Regulatory Surveillance) Systems framework which uses a combination of genetic algorithms, neural nets and statistical analysis in detecting insider dealing, to be used in the detection of transaction fraud. …”
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Outlier Detection Technique in Data Mining: A Research Perspective by Mansur, M. O., Md. Sap, Mohd. Noor

“…The identification of outliers can lead to the discovery of unexpected knowledge in areas such as credit card fraud detection, calling card fraud detection, discovering criminal behaviors, discovering computer intrusion, etc. …”
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A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh by Kuldeep Kaur , Ragbir Singh

“…The empirical results positively indicate that the hybrid model with the sliding window method is able to yield a good accuracy rate of 82.4% in detecting fraud cases in real world credit card transactions. …”
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SEDF: a spoofed email detection framework employed by a lightweight web browser plug-in for detecting the spoofed email / Al Ya@Geogiana Buja...[et al.] by Buja, Al Ya@Geogiana, Ahmad, Illiasaak, Zolkeply, Mohd Syafiq

“…The method used to detect fake e-mail is by tracing back the email header. …”
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EEG-and MRI-based epilepsy source localization using multivariate empirical mode decomposition and inverse solution method by Khosropanah, Pegah

“…The accuracy of ESL depends on all the stages of data processing including: head model reconstruction, signal pre-processing and inverse solution. Therefore, a standardized algorithm with less supervision is desired to utilize ESL for pre-surgical evaluation. …”
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Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream by Abdulateef, Alaa Fareed

“…The results indicate that the AGMB algorithm outperformed existing benchmark algorithms in terms of predefined evaluation criteria with an overall 72% accuracy compared to benchmark algorithms which is 11 % only. …”
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Intelligent deep machine learning cyber phishing URL detection based on BERT features extraction by Muna Elsadig, Ashraf Osman Ibrahim Elsayed, Shakila Basheer, Manal Abdullah Alohali, Sara Alshunaifi, Haya Alqahtani, Nihal Alharbi, Wamda Nagmeldin

“…The results showed that the proposed method was efficient and valid in detecting phishing websites’ URLs.…”
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Whole brain radiation therapy verification using 2D gamma analysis method by Zainodin, Nik Nurul Afina Wan

“…The CC algorithm gave the passing rate of 87.25% using 3 mm/3% (DTA/DD) method than PB algorithm with 79.95%. …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…The classification accuracy obtained from the CST method is compared to other selected classification methods such as Value Difference Metric (VDM), Pre-Category Feature Importance (PCF), Cross-Category Feature Importance (CCF), Instance-Based Algorithm (IB4), Decision Tree Algorithms such as Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5), Rough Set methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) and Neural Network methods such as the Multilayer method.…”
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Block based low complexity iterative QR precoder structure for Massive MIMO by Mok, Li Suet

“…In this thesis, we also study and evaluate different conventional linear pre-coding schemes as well as how they relate to optimal structure of the solution which maximize the system performances. …”
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Evaluation of sparsifying algorithms for speech signals by Kassim, Liban A., Khalifa, Othman Omran, Gunawan, Teddy Surya

“…Sparsity is important also in speech compression and coding, where the signal can be compressed in pre-processing stages. It leads to efficient and robust methods for compression, detection denoising and signal separation. …”
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Discovering optimal features using static analysis and a genetic search based method for Android malware detection by Firdaus, Ahmad, Anuar, Nor Badrul, Karim, Ahmad, Razak, Mohd Faizal Ab

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Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

“…Finally, the effectiveness of the algorithm is evaluated based on the accuracy performance. …”
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Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons by Yaseen, Zaher Mundher, Fu, Minglei, Wang, Chen, Mohtar, Wan Hanna Melini Wan, Deo, Ravinesh C., El-Shafie, Ahmed

“…In this study, the uncertainty and nonstationary characteristics of streamflow data has been treated using a set of coupled data pre-processing methods before being considered as input for an artificial neural network algorithm namely; rolling mechanism (RM) and grey models (GM). …”
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