H.3. Artificial Intelligence
X-SHAoLIM: Novel Feature Selection Framework for Credit Card Fraud Detection

Sajjad Alizadeh Fard; Hossein Rahmani

Articles in Press, Accepted Manuscript, Available Online from 04 March 2024

https://doi.org/10.22044/jadm.2024.13630.2480

Abstract
  Fraud in financial data is a significant concern for both businesses and individuals. Credit card transactions involve numerous features, some of which may lack relevance for classifiers and could lead to overfitting. A pivotal step in the fraud detection process is feature selection, which profoundly ...  Read More

H.6.3.3. Pattern analysis
Hidden Pattern Discovery on Clinical Data: an Approach based on Data Mining Techniques

Meysam Roostaee; Razieh Meidanshahi

Volume 11, Issue 3 , July 2023, , Pages 343-355

https://doi.org/10.22044/jadm.2023.12855.2435

Abstract
  In this study, we sought to minimize the need for redundant blood tests in diagnosing common diseases by leveraging unsupervised data mining techniques on a large-scale dataset of over one million patients' blood test results. We excluded non-numeric and subjective data to ensure precision. To identify ...  Read More

BRTSRDM: Bi-Criteria Regression Test Suite Reduction based on Data Mining

Mohammad Reza Keyvanpour; Zahra Karimi Zandian; Nasrin Mottaghi

Volume 11, Issue 2 , April 2023, , Pages 161-186

https://doi.org/10.22044/jadm.2023.12208.2374

Abstract
  Regression testing reduction is an essential phase in software testing. In this step, the redundant and unnecessary cases are eliminated, whereas software accuracy and performance are not degraded. So far, various researches have been proposed in regression testing reduction field. The main challenge ...  Read More

F.4.18. Time series analysis
Time Series Clustering based on Aggregation and Selection of Extracted Features

Ali Ghorbanian; Hamideh Razavi

Volume 11, Issue 2 , April 2023, , Pages 303-314

https://doi.org/10.22044/jadm.2023.13089.2449

Abstract
  In time series clustering, features are typically extracted from the time series data and used for clustering instead of directly clustering the data. However, using the same set of features for all data sets may not be effective. To overcome this limitation, this study proposes a five-step algorithm ...  Read More

Investigating Revenue Smoothing Thresholds That Affect Bank Credit Scoring Models: An Iranian Bank Case Study

Seyed Mahdi Sadatrasoul; Omid Mahdi Ebadati; Amir Amirzadeh Irani

Volume 11, Issue 1 , January 2023, , Pages 131-148

https://doi.org/10.22044/jadm.2023.11982.2346

Abstract
  Companies have different considerations for using smoothing in their financial statements, including annual general meeting, auditing, Regulatory and Supervisory institutions and shareholders requirements. Smoothing is done based on the various possible and feasible choices in identifying company’s ...  Read More

WSAMLP: Water Strider Algorithm and Artificial Neural Network-based Activity Detection Method in Smart Homes

J. Barazande; N. Farzaneh

Volume 10, Issue 1 , January 2022, , Pages 1-13

https://doi.org/10.22044/jadm.2021.10781.2215

Abstract
  One of the crucial applications of IoT is developing smart cities via this technology. Smart cities are made up of smart components such as smart homes. In smart homes, a variety of sensors are used for making the environment smart, and the smart things, in such homes, can be used for detecting the activities ...  Read More

Data Mining-based Structural Damage Identification of Composite Bridge using Support Vector Machine

M. Gordan; Saeed R. Sabbagh-Yazdi; Z. Ismail; Kh. Ghaedi; H. Hamad Ghayeb

Volume 9, Issue 4 , November 2021, , Pages 415-423

https://doi.org/10.22044/jadm.2021.10430.2182

Abstract
  A structural health monitoring system contains two components, i.e. a data collection approach comprising a network of sensors for recording the structural responses as well as an extraction methodology in order to achieve beneficial information on the structural health condition. In this regard, data ...  Read More

Investigating Changes in Household Consumable Market Using Data Mining Techniques

A. Hasan-Zadeh; F. Asadi; N. Garbazkar

Volume 9, Issue 3 , July 2021, , Pages 341-349

https://doi.org/10.22044/jadm.2021.10024.2139

Abstract
  For an economic review of food prices in May 2019 to determine the trend of rising or decreasing prices compared to previous periods, we considered the price of food items at that time. The types of items consumed during specific periods in urban areas and the whole country are selected for our statistical ...  Read More

Detecting Breast Cancer through Blood Analysis Data using Classification Algorithms

Oladosu Oladimeji; Olayanju Oladimeji

Volume 9, Issue 3 , July 2021, , Pages 351-359

https://doi.org/10.22044/jadm.2021.9839.2116

Abstract
  Breast cancer is the second major cause of death and accounts for 16% of all cancer deaths worldwide. Most of the methods of detecting breast cancer are very expensive and difficult to interpret such as mammography. There are also limitations such as cumulative radiation exposure, over-diagnosis, false ...  Read More

H.3.14. Knowledge Management
A New Algorithm for High Average-utility Itemset Mining

A. Soltani; M. Soltani

Volume 7, Issue 4 , November 2019, , Pages 537-550

https://doi.org/10.22044/jadm.2019.7483.1893

Abstract
  High utility itemset mining (HUIM) is a new emerging field in data mining which has gained growing interest due to its various applications. The goal of this problem is to discover all itemsets whose utility exceeds minimum threshold. The basic HUIM problem does not consider length of itemsets in its ...  Read More

D. Data
Prediction and Diagnosis of Diabetes Mellitus using a Water Wave Optimization Algorithm

S. Taherian Dehkordi; A. Khatibi Bardsiri; M. H. Zahedi

Volume 7, Issue 4 , November 2019, , Pages 617-630

https://doi.org/10.22044/jadm.2018.6446.1758

Abstract
  Data mining is an appropriate way to discover information and hidden patterns in large amounts of data, where the hidden patterns cannot be easily discovered in normal ways. One of the most interesting applications of data mining is the discovery of diseases and disease patterns through investigating ...  Read More

H.3. Artificial Intelligence
Forecasting Gold Price using Data Mining Techniques by Considering New Factors

A.R. Hatamlou; M. Deljavan

Volume 7, Issue 3 , July 2019, , Pages 411-420

https://doi.org/10.22044/jadm.2018.6114.1727

Abstract
  Gold price forecast is of great importance. Many models were presented by researchers to forecast gold price. It seems that although different models could forecast gold price under different conditions, the new factors affecting gold price forecast have a significant importance and effect on the increase ...  Read More

G.3.9. Database Applications
Using Combined Descriptive and Predictive Methods of Data Mining for Coronary Artery Disease Prediction: a Case Study Approach

M. Shamsollahi; A. Badiee; M. Ghazanfari

Volume 7, Issue 1 , January 2019, , Pages 47-58

https://doi.org/10.22044/jadm.2017.4992.1599

Abstract
  Heart disease is one of the major causes of morbidity in the world. Currently, large proportions of healthcare data are not processed properly, thus, failing to be effectively used for decision making purposes. The risk of heart disease may be predicted via investigation of heart disease risk factors ...  Read More

D. Data
Impact of Patients’ Gender on Parkinson’s disease using Classification Algorithms

M. Abdar; M. Zomorodi-Moghadam

Volume 6, Issue 2 , July 2018, , Pages 277-285

https://doi.org/10.22044/jadm.2017.4673.1555

Abstract
  In this paper the accuracy of two machine learning algorithms including SVM and Bayesian Network are investigated as two important algorithms in diagnosis of Parkinson’s disease. We use Parkinson's disease data in the University of California, Irvine (UCI). In order to optimize the SVM algorithm, ...  Read More

H.3.2.3. Decision support
Analyzing and Investigating the Use of Electronic Payment Tools in Iran using Data Mining Techniques

F. Moslehi; A.R. Haeri; A.R. Moini

Volume 6, Issue 2 , July 2018, , Pages 417-437

https://doi.org/10.22044/jadm.2017.5352.1643

Abstract
  In today's world, most financial transactions are carried out using done through electronic instruments and in the context of the Information Technology and Internet. Disregarding the application of new technologies at this field and sufficing to traditional ways, will result in financial loss and customer ...  Read More

H.3.2.5. Environment
Ensemble of M5 Model Tree Based Modelling of Sodium Adsorption Ratio

M. T. Sattari; M. Pal; R. Mirabbasi; J. Abraham

Volume 6, Issue 1 , March 2018, , Pages 69-78

https://doi.org/10.22044/jadm.2017.5540.1663

Abstract
  This work reports the results of four ensemble approaches with the M5 model tree as the base regression model to anticipate Sodium Adsorption Ratio (SAR). Ensemble methods that combine the output of multiple regression models have been found to be more accurate than any of the individual models making ...  Read More

H.5.10. Applications
A case study for application of fuzzy inference and data mining in structural health monitoring

S. Shoorabi Sani

Volume 6, Issue 1 , March 2018, , Pages 105-120

https://doi.org/10.22044/jadm.2016.813

Abstract
  In this study, a system for monitoring the structural health of bridge deck and predicting various possible damages to this section was designed based on measuring the temperature and humidity with the use of wireless sensor networks, and then it was implemented and investigated. A scaled model of a ...  Read More

H.4.6. Computational Geometry and Object Modeling
A New Ontology-Based Approach for Human Activity Recognition from GPS Data

A. Mousavi; A. Sheikh Mohammad Zadeh; M. Akbari; A. Hunter

Volume 5, Issue 2 , July 2017, , Pages 197-210

https://doi.org/10.22044/jadm.2017.889

Abstract
  Mobile technologies have deployed a variety of Internet–based services via location based services. The adoption of these services by users has led to mammoth amounts of trajectory data. To use these services effectively, analysis of these kinds of data across different application domains is required ...  Read More

J.10.3. Financial
The application of data mining techniques in manipulated financial statement classification: The case of turkey

G. Ozdagoglu; A. Ozdagoglu; Y. Gumus; G. Kurt Gumus

Volume 5, Issue 1 , March 2017, , Pages 67-77

https://doi.org/10.22044/jadm.2016.664

Abstract
  Predicting financially false statements to detect frauds in companies has an increasing trend in recent studies. The manipulations in financial statements can be discovered by auditors when related financial records and indicators are analyzed in depth together with the experience of auditors in order ...  Read More

H.3.14. Knowledge Management
Introducing an algorithm for use to hide sensitive association rules through perturb technique

M. Sakenian Dehkordi; M. Naderi Dehkordi

Volume 4, Issue 2 , July 2016, , Pages 219-227

https://doi.org/10.5829/idosi.JAIDM.2016.04.02.10

Abstract
  Due to the rapid growth of data mining technology, obtaining private data on users through this technology becomes easier. Association Rules Mining is one of the data mining techniques to extract useful patterns in the form of association rules. One of the main problems in applying this technique on ...  Read More

Employing data mining to explore association rules in drug addicts

Farzaneh Zahedi; Mohammad-Reza Zare-Mirakabad

Volume 2, Issue 2 , July 2014, , Pages 135-139

https://doi.org/10.22044/jadm.2014.308

Abstract
  Drug addiction is a major social, economic, and hygienic challenge that impacts on all the community and needs serious threat. Available treatments are successful only in short-term unless underlying reasons making individuals prone to the phenomenon are not investigated. Nowadays, there are some treatment ...  Read More

Data mining for decision making in engineering optimal design

Amir Mosavi

Volume 2, Issue 1 , March 2014, , Pages 7-14

https://doi.org/10.22044/jadm.2014.125

Abstract
  Often in modeling the engineering optimization design problems, the value of objective function(s) is not clearly defined in terms of design variables. Instead it is obtained by some numerical analysis such as FE structural analysis, fluid mechanic analysis, and thermodynamic analysis, etc. Yet, the ...  Read More

Credit scoring in banks and financial institutions via data mining techniques: A literature review

Seyed Mahdi sadatrasoul; Mohammadreza gholamian; Mohammad Siami; Zeynab Hajimohammadi

Volume 1, Issue 2 , July 2013, , Pages 119-129

https://doi.org/10.22044/jadm.2013.124

Abstract
  This paper presents a comprehensive review of the works done, during the 2000–2012, in the application of data mining techniques in Credit scoring. Yet there isn’t any literature in the field of data mining applications in credit scoring. Using a novel research approach, this paper investigates ...  Read More