Volume 12 (2024)
Volume 11 (2023)
Volume 10 (2022)
Volume 9 (2021)
Volume 8 (2020)
Volume 7 (2019)
Volume 6 (2018)
Volume 5 (2017)
Volume 4 (2016)
Volume 3 (2015)
Volume 2 (2014)
Volume 1 (2013)
H.3. Artificial Intelligence
Application of Stacked Ensemble Techniques in Head and Neck Squamous Cell Carcinoma Prognostic Feature Subsets

Damianus Kofi Owusu; Christiana Cynthia Nyarko; Joseph Acquah; Joel Yarney

Volume 12, Issue 1 , January 2024, , Pages 67-81

https://doi.org/10.22044/jadm.2023.12420.2388

Abstract
  Head and neck cancer (HNC) recurrence is ever increasing among Ghanaian men and women. Because not all machine learning classifiers are equally created, even if multiple of them suite very well for a given task, it may be very difficult to find one which performs optimally given different distributions. ...  Read More

H.3. Artificial Intelligence
Fast COVID-19 Infection Prediction with In-House Data Using Machine Learning Classification Algorithms: A Case Study of Iran

Ali Rebwar Shabrandi; Ali Rajabzadeh Ghatari; Nader Tavakoli; Mohammad Dehghan Nayeri; Sahar Mirzaei

Volume 11, Issue 4 , November 2023, , Pages 573-585

https://doi.org/10.22044/jadm.2023.13291.2458

Abstract
  To mitigate COVID-19’s overwhelming burden, a rapid and efficient early screening scheme for COVID-19 in the first-line is required. Much research has utilized laboratory tests, CT scans, and X-ray data, which are obstacles to agile and real-time screening. In this study, we propose a user-friendly ...  Read More

Learning a Nonlinear Combination of Generalized Heterogeneous Classifiers

M. Rahimi; A. A. Taheri; H. Mashayekhi

Volume 11, Issue 1 , January 2023, , Pages 77-93

https://doi.org/10.22044/jadm.2022.12403.2387

Abstract
  Finding an effective way to combine the base learners is an essential part of constructing a heterogeneous ensemble of classifiers. In this paper, we propose a framework for heterogeneous ensembles, which investigates using an artificial neural network to learn a nonlinear combination of the base classifiers. ...  Read More

A Hybridization Method of Prototype Generation and Prototype Selection for K-NN rule Based on GSA

M. Rezaei; H. Nezamabadi-pour

Volume 10, Issue 2 , April 2022, , Pages 257-268

https://doi.org/10.22044/jadm.2021.10159.2154

Abstract
  The present study aims to overcome some defects of the K-nearest neighbor (K-NN) rule. Two important data preprocessing methods to elevate the K-NN rule are prototype selection (PS) and prototype generation (PG) techniques. Often the advantage of these techniques is investigated separately. In this paper, ...  Read More

An Efficient Hybrid Method for Semantic Web Service Discovery

P. Farzi; R. Akbari

Volume 9, Issue 4 , November 2021, , Pages 525-541

https://doi.org/10.22044/jadm.2021.9958.2132

Abstract
  Abstract: Web service is a technology for defining self-describing objects, structural-based, and loosely coupled applications. They are accessible all over the web and provide a flexible platform. Although service registries such as Universal Description, Discovery, and Integration (UDDI) provide facilities ...  Read More

Feature Selection based on Particle Swarm Optimization and Mutual Information

Z. Shojaee; Seyed A. Shahzadeh Fazeli; E. Abbasi; F. Adibnia

Volume 9, Issue 1 , January 2021, , Pages 39-44

https://doi.org/10.22044/jadm.2020.8857.2020

Abstract
  Today, feature selection, as a technique to improve the performance of the classification methods, has been widely considered by computer scientists. As the dimensions of a matrix has a huge impact on the performance of processing on it, reducing the number of features by choosing the best subset of ...  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

G.3.5. Systems
Assessment Methodology for Anomaly-Based Intrusion Detection in Cloud Computing

M. Rezvani

Volume 6, Issue 2 , July 2018, , Pages 387-397

https://doi.org/10.22044/jadm.2017.5581.1668

Abstract
  Cloud computing has become an attractive target for attackers as the mainstream technologies in the cloud, such as the virtualization and multitenancy, permit multiple users to utilize the same physical resource, thereby posing the so-called problem of internal facing security. Moreover, the traditional ...  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.6.4. Clustering
Grouping Objects to Homogeneous Classes Satisfying Requisite Mass

M. Manteqipour; A.R. Ghaffari Hadigheh; R. Mahmoodvand; A. Safari

Volume 6, Issue 1 , March 2018, , Pages 163-175

https://doi.org/10.22044/jadm.2017.988

Abstract
  Grouping datasets plays an important role in many scientific researches. Depending on data features and applications, different constrains are imposed on groups, while having groups with similar members is always a main criterion. In this paper, we propose an algorithm for grouping the objects with random ...  Read More

H.6.3.2. Feature evaluation and selection
Feature extraction of hyperspectral images using boundary semi-labeled samples and hybrid criterion

M. Imani; H. Ghassemian

Volume 5, Issue 1 , March 2017, , Pages 39-53

https://doi.org/10.22044/jadm.2017.787

Abstract
  Feature extraction is a very important preprocessing step for classification of hyperspectral images. The linear discriminant analysis (LDA) method fails to work in small sample size situations. Moreover, LDA has poor efficiency for non-Gaussian data. LDA is optimized by a global criterion. Thus, it ...  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.6.3.2. Feature evaluation and selection
Feature reduction of hyperspectral images: Discriminant analysis and the first principal component

Maryam Imani; Hassan Ghassemian

Volume 3, Issue 1 , March 2015, , Pages 1-9

https://doi.org/10.5829/idosi.JAIDM.2015.03.01.01

Abstract
  When the number of training samples is limited, feature reduction plays an important role in classification of hyperspectral images. In this paper, we propose a supervised feature extraction method based on discriminant analysis (DA) which uses the first principal component (PC1) to weight the scatter ...  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