Search Results - (( parameter optimization method algorithm ) OR ( fraud detection using algorithm ))*

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. …”

Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff by Mohd Yusoff, Mohd Izhan

“…We introduce a new algorithm that could detect fraud activities in telecommunication industry (e.g. intrusion fraud which occurs when legitimate account is comprised by an intruder who makes or sells calls on this account) that uses Gaussian Mixed Model (or GMM), a probabilistic model normally used in fraud detection via speech recognition. …”
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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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Detection of Fraud and Non-Fraud Transaction using Machine Learning Algorithm by Sujang Karing, Darryl

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Fraud Detection in Shipping Industry using K-NN Algorithm by Subramaniam G., Mahmoud M.A.

Fraud detection in shipping industry based on location using machine learning comparison techniques by Ganesan Subramaniam, Mr.

“…This research discusses fraud detection specifically within the shipping industry using data analytics techniques. …”

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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Online Transaction Fraud Detection Using Backlogging On E-Commerce Website: A Review by Atiqah, S.M.T., Nurdiana, A.

A Location-Based Fraud Detection in Shipping Industry Using Machine Learning Comparison Techniques by Subramaniam G.A.L., Mahmoud M.A., Abdulwahid S.N., Gunasekaran S.S.

“…A study reviewed existing fraud detectionFraud detection models and identified the most effective algorithm for the shipping industry. …”

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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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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Building classification models from imbalanced fraud detection data / Terence Yong Koon Beh, Swee Chuan Tan and Hwee Theng Yeo by Terence, Yong Koon Beh, Swee, Chuan Tan, Hwee, Theng Yeo

“…This paper reports our experience in applying data balancing techniques to develop a classifier for an imbalanced real-world fraud detection data set. We evaluated the models generated from seven classification algorithms with two simple data balancing techniques. …”
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RFID-enabled supply chain detection using clustering algorithms by Azahar, T.F., Mahinderjit-Singh, M., Hassan, R.

“…Furthermore, RFID data nature characteristics faces the issues likes RFID just carry simple information, in-flood of data, inaccuracy data from RFID readers and difficulties to track spatial and place. We propose to use clustering algorithms in order to detect counterfeit in supply chain management. …”
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Credit Card Fraud Detection Using New Preprocessing And Hybrid Machine Learning Techniques by Gasim, Esraa Faisal Malik

“…The second contribution to this research is to develop multiple hybrid machine learning models in order to enhance the detection of fraudulent activities in the credit card fraud detection domain.…”
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Forensic accountants, auditors and fraud capability and competence requirements in the Nigerian public sector by Popoola, Oluwatoyin Muse Johnson

“…The ten out of fifteen hypotheses were tested through the use of PLS-SEM algorithm and bootstrap techniques on the hypothesized relationships while the remaining five hypotheses of differences among groups were tested using the Mann-Whitney U Test. …”
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Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

“…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
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Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization by Nur Iffah, Mohamed Azmi

“…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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Optimization of turning parameters using ant colony optimization by Mohamad Nazri, Semoin

“…The project objectives are to develop Ant Colony Optimization (ACO) algorithm for CNC turning process and to optimize turning parameters for minimized production cost per unit. …”
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Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail by Foo, Fong Yeng, Lau, Gee Choon, Ismail, Zuhaimy

“…Trial and error often serves as the best method to determine the parameter. Therefore, a good optimization technique is required for identify the best parameter in minimizing the forecast errors. …”
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