D. Data
1. 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 , Autumn 2019, , Pages 617-630

http://dx.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.3.14. Knowledge Management
2. A New Algorithm for High Average-utility Itemset Mining

A. Soltani; M. Soltani

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

http://dx.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

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

A.R. Hatamlou; M. Deljavan

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

http://dx.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
4. 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 , Winter 2019, , Pages 47-58

http://dx.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
5. Impact of Patients’ Gender on Parkinson’s disease using Classification Algorithms

M. Abdar; M. Zomorodi-Moghadam

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

http://dx.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
6. 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 , Summer 2018, , Pages 417-437

http://dx.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.5.10. Applications
7. A case study for application of fuzzy inference and data mining in structural health monitoring

S. Shoorabi Sani

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

http://dx.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.3.2.5. Environment
8. Ensemble of M5 Model Tree Based Modelling of Sodium Adsorption Ratio

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

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

http://dx.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.4.6. Computational Geometry and Object Modeling
9. 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 , Summer 2017, , Pages 197-210

http://dx.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
10. 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 , Winter 2017, , Pages 67-77

http://dx.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
11. Introducing an algorithm for use to hide sensitive association rules through perturb technique

M. Sakenian Dehkordi; M. Naderi Dehkordi

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

http://dx.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

12. Employing data mining to explore association rules in drug addicts

Farzaneh Zahedi; Mohammad-Reza Zare-Mirakabad

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

http://dx.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

13. Data mining for decision making in engineering optimal design

Amir Mosavi

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

http://dx.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

14. 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 , Summer 2013, , Pages 119-129

http://dx.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