Search Results - (( fraud detection model algorithm ) OR ( based optimization _ algorithm ))*

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

“…There were also identification of factors that influence fraud activity, review existing fraud detection models, develop the detection model and implement it using a well-known tool in the market namely Rapidminer. …”

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

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

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

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.…”
Get full text
Get full text
Get full text

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. …”

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.…”
Get full text
Get full text

The performance of expectation maximization (EM) algorithm in Gaussian Mixed Models (GMM) by Mohd Yusoff, Mohd Izhan, Abu Bakar, Mohd. Rizam, Mohd Nor, Abu Hassan Shaari

“…In this paper, the performance of the said algorithm in finding the Maximum Likelihood for the Gaussian Mixed Models (GMM), a probabilistic model normally used in fraud detection and recognizing a person’s voice in speech recognition field, is shown and discussed. …”
Get full text
Get full text
Get full text

A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh by Kuldeep Kaur , Ragbir Singh

“…While financial losses from credit card fraud amount to billions of dollars each year, investigations on effective predictive models to identify fraud cases using real credit card data are limited currently, mainly due to confidentiality of customer information. …”
Get full text
Get full text
Get full text

Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms by Lei, X., Mohamad, U.H., Sarlan, A., Shutaywi, M., Daradkeh, Y.I., Mohammed, H.O.

“…In the financial sector, machine learning algorithms are used to detect fraud, automate trading, and provide financial advice to investors. …”
Get full text
Get full text

Detection of energy theft and defective smart meters in smart grids using linear regression by Yip, S.C., Wong, K., Hew, W.P., Gan, M.T., Phan, R.C.W., Tan, S.W.

“…Categorical variables and detection coefficients are also introduced in the model to identify the periods and locations of energy frauds as well as faulty smart meters. …”
Get full text
Get full text

Efficient ML technique in blockchain-based solution in carbon credit for mitigating greenwashing by Raja Segaran, Bama, Mohd Rum, Siti Nurulain, Hafez Ninggal, Mohd Izuan, Mohd Aris, Teh Noranis

“…However, while blockchain ensures transparency, it lacks real-time anomaly detection capabilities. ML algorithms, particularly supervised models such as Random Forest, XGBoost, and Neural Networks, are well-suited for detecting fraudulent patterns and verifying the authenticity of forest carbon credit transactions. …”
Get full text
Get full text
Get full text

Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

“…Applications and improvements to the HKA algorithm suggest that optimization algorithm based on estimation principle has a huge potential in solving a wide variety of optimization problems. …”
Get full text
Get full text

Opposition-based Whale Optimization Algorithm by Alamri, Hammoudeh S., Alsariera, Yazan A., Kamal Z., Zamli

“…In order to improve solution accuracy and reliability, this paper proposes a new algorithm based on WOA. The new algorithm called Opposition-based Whale Optimization (OWOA). …”
Get full text
Get full text
Get full text

Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

“…Finally, a crowding distance and non-dominated-sorting-based multi-objective hybrid firefly & particle swarm optimization (MOHFPSO) algorithm is designed for MOOPF problems. …”
Get full text
Get full text

Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem by Ismail, Ibrahim, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

“…In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. …”
Get full text
Get full text
Get full text
Get full text

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.…”
Get full text
Get full text
Get full text
Get full text

Metaheuristic multi-hop clustering optimization for energy-efficient wireless sensor network by Vincent Chung, Norah Tuah, Kit Guan Lim, Min Keng Tan, Ismail Saad, Kenneth Tze Kin Teo

“…Based on the performance evaluation, GACS outperforms both Genetic Algorithm (GA)-based cluster optimization algorithm and Cuckoo Search (CS)-based multi-hop optimization algorithm.…”
Get full text
Get full text