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)

Facts & Figures

(Up to Date)

Number of Volumes

13

Number of Articles

466

Number of Issues

39

Article View

751,098

PDF Download

638,596

View Per Article

1611.8

PDF Download Per Article

1370.38

Reject Rate %

55

Acceptance Rate %

27

Number of Reviewers

3336

First Decision

(Approximately)

40(Days)

 

The Journal of Artificial Intelligence & Data Mining (JAIDM) is a scientific journal that aims to develop the international exchange of scientific and technical information in all areas of Artificial Intelligence and Data Mining.

 All manuscripts with significant research results in the scope of the journal are welcome if they are not published or not being considered for publication elsewhere.

Journal of Artificial Intelligence & Data Mining appears quarterly considering the increasing importance of rapid, effective, international communication. JAIDM offers:

  • Publication within a short period after acceptance
  • On-line publication in advance of the printed journal
  • One journal copy  will be sent to the corresponding author
  • Printing, Processing and Delivery without any charges

Topics of interest include, but are not limited to, the following:

  • Artificial Intelligence Algorithms, Tools & Applications
  • Data Mining and Machine Learning Tools
  • Semantic Web Techniques and Technologies
  • Soft computing theory and applications
  • Web Intelligence Applications & Search
  • Bioinformatics
  • Natural Language Processing
  • Computer Vision and Image Processing
  • Speech Understanding
  • Fuzzy Logic
  • Information Retrieval
  • Intelligent System Architectures
  • Knowledge-based/ Expert Systems
  • Automatic Control
  • Neural Networks
  • Parallel Processing
  • Pattern Recognition
  •  Software & Hardware Architectures
   

All accepted papers will be checked by iThenticate against plagiarism. 

 

All type papers published by JAIDM are made freely and permanently accessible online immediately upon publication. JAIDM is an "Open access" publishing allows an immediate, world-wide, barrier-free, open access to the full text of research papers, which is in the best interests of the scientific community.

High visibility for maximum global exposure with open access publishing model rigorous peer review (blind peer-review) of research papers prompt faster publication.

JAIDM has no publication charges and no submission fees.

All corresponding authors of each manuscript should be download "COPYRIGHT RELEASE FORM" from above this page then complete and sign this form by all authors and submit this form with all mandatory files which mentioned in bellow. By signing this form, copyright transfer to JAIDM.

Submission of a manuscript implies that:

1) The work described has not been published before (except in the form of an abstract or as part of a published lecture, review, or thesis).

2) It is not under consideration for publication elsewhere.

3) Its publication has been approved by all coauthors, if any, as well as by the responsible authorities at the institute where the work has been carried out.

4) Authors agree to automatic transfer of the copyright to the publisher, if and when their manuscript is accepted for publication.

5) The manuscript will not be published elsewhere.

 

JAIDM respect all aspects of publication ethics of the Committee on Publication Ethics (COPE). COPE is a forum for editors and publishers of peer reviewed journals to discuss all aspects of publication ethics. COPE provides advice to editors and publishers on all aspects of publication ethics and, in particular, how to handle cases of research and publication misconduct. COPE does not investigate individual cases but encourages editors to ensure that cases are investigated by the appropriate authorities (usually a research institution or employer).

 

Technical Paper H.3. Artificial Intelligence
Robust Persian Digit Recognition in Noisy Environments Using Hybrid CNN-BiGRU Model

Ali Nasr-Esfahani; Mehdi Bekrani; Roozbeh Rajabi

Volume 13, Issue 3 , July 2025, Pages 337-345

https://doi.org/10.22044/jadm.2025.15932.2707

Abstract
  Artificial intelligence (AI) has significantly advanced speech recognition applications. However, many existing neural network-based methods struggle with noise, reducing accuracy in real-world environments. This study addresses isolated spoken Persian digit recognition (zero to nine) under noisy conditions, ...  Read More

Original/Review Paper H.3. Artificial Intelligence
Discrete Rotated Isolation Forest in High Dimensions

Vahideh Monemizadeh; Kourosh Kiani

Volume 13, Issue 3 , July 2025, Pages 347-358

https://doi.org/10.22044/jadm.2025.15883.2704

Abstract
  Anomaly detection is becoming increasingly crucial across various fields, including cybersecurity, financial risk management, and health monitoring. However, it faces significant challenges when dealing with large-scale, high-dimensional, and unlabeled datasets. This study focuses on decision tree-based ...  Read More

Review Article H.3. Artificial Intelligence
Attention Mechanisms in Transformers: A General Survey

Rasoul Hosseinzadeh; Mahdi Sadeghzadeh

Volume 13, Issue 3 , July 2025, Pages 359-368

https://doi.org/10.22044/jadm.2025.15584.2679

Abstract
  The attention mechanisms have significantly advanced the field of machine learning and deep learning across various domains, including natural language processing, computer vision, and multimodal systems. This paper presents a comprehensive survey of attention mechanisms in Transformer architectures, ...  Read More

Original/Review Paper H.6.5.13. Signal processing
Valvular Heart Disease Classification through Hierarchical Decomposition via Matrix Factorization of Scalogram-Based Phonocardiogram Representations

Samira Moghani; Hossein Marvi; Zeynab Mohammadpoory

Volume 13, Issue 3 , July 2025, Pages 369-378

https://doi.org/10.22044/jadm.2025.16092.2726

Abstract
  This study introduces a novel classification framework based on Deep Orthogonal Non-Negative Matrix Factorization (Deep ONMF), which leverages scalogram representations of phonocardiogram (PCG) signals to hierarchically extract structural features crucial for detecting valvular heart diseases (VHDs). ...  Read More

Iranian Vehicle Images Dataset for Object Detection Algorithm
Volume 12, Issue 1 , January 2024, , Pages 127-136

https://doi.org/10.22044/jadm.2024.13858.2501

Abstract
  Providing a dataset with a suitable volume and high accuracy for training deep neural networks is considered to be one of the basic requirements in that a suitable dataset in terms of the number and quality of images and labeling accuracy can have a great impact on the output accuracy of the trained ...  Read More

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

Multi-Focus Image Fusion in DCT Domain using Variance and Energy of Laplacian and Correlation Coefficient for Visual Sensor Networks
Volume 6, Issue 2 , July 2018, , Pages 233-250

https://doi.org/10.22044/jadm.2017.5169.1624

Abstract
  The purpose of multi-focus image fusion is gathering the essential information and the focused parts from the input multi-focus images into a single image. These multi-focus images are captured with different depths of focus of cameras. A lot of multi-focus image fusion techniques have been introduced ...  Read More

Outlier Detection in Wireless Sensor Networks Using Distributed Principal Component Analysis
Volume 1, Issue 1 , March 2013, , Pages 1-11

https://doi.org/10.22044/jadm.2013.98

Abstract
  Detecting anomalies is an important challenge for intrusion detection and fault diagnosis in wireless sensor networks (WSNs). To address the problem of outlier detection in wireless sensor networks, in this paper we present a PCA-based centralized approach and a DPCA-based distributed energy-efficient ...  Read More

QoS-Based web service composition based on genetic algorithm
Volume 1, Issue 2 , July 2013, , Pages 63-73

https://doi.org/10.22044/jadm.2013.97

Abstract
  Quality of service (QoS) is an important issue in the design and management of web service composition. QoS in web services consists of various non-functional factors, such as execution cost, execution time, availability, successful execution rate, and security. In recent years, the number of available ...  Read More

Technical Paper
Improving the Hierarchical Classification of Protein Families and Model Interpretation with the Grad-CAM Method and Transformers

Naeimeh Mohammad Karimi; Mehdi Rezaeian

Articles in Press, Accepted Manuscript, Available Online from 30 April 2025

https://doi.org/10.22044/jadm.2025.15493.2667

Abstract
  In the era of massive data, analyzing bioinformatics fields and discovering its functions are very important. The rate of sequence generation using sequence generation techniques is increasing rapidly, and researchers are faced with many unknown functions. One of the essential operations in bioinformatics ...  Read More

Original/Review Paper
A Phenology Based Paddy Rice Mapping by Correlation Analysis on Sentinel-1/2 Imagery in Fragmented Lands Using GEE Platform

Fateme Namazi; Mehdi Ezoji; Ebadat Ghanbari Parmehr

Articles in Press, Accepted Manuscript, Available Online from 03 May 2025

https://doi.org/10.22044/jadm.2025.15379.2639

Abstract
  Paddy fields in the north of Iran are highly fragmented, leading to challenges in accurately mapping them using remote sensing techniques. Cloudy weather often degrades image quality or renders images unusable, further complicating monitoring efforts. This paper presents a novel paddy rice mapping method ...  Read More

Technical Paper
Anomaly Detection in IoT Traffic in the Presence of Gaussian Noise Using Deep Neural Networks

Roya Morshedi; S. Mojtaba Matinkhah

Articles in Press, Accepted Manuscript, Available Online from 06 May 2025

https://doi.org/10.22044/jadm.2025.15672.2684

Abstract
  The Internet of Things (IoT) is a rapidly growing domain essential for modern smart services. However, resource limitations in IoT nodes create significant security vulnerabilities, making them prone to cyberattacks. Deep learning models have emerged as effective tools for detecting anomalies in IoT ...  Read More

Applied Article
Attention-HAR: Advanced Human Activity Recognition Using a Deep ‎Learning Model with an Integrated Attention Mechanism

Navid Raisi; Mahdi Rezaei; Behrooz Masoumi

Articles in Press, Accepted Manuscript, Available Online from 28 May 2025

https://doi.org/10.22044/jadm.2025.15658.2683

Abstract
  Human Activity Recognition (HAR) using computer vision is an ‎expanding field with diverse applications, including healthcare, ‎transportation, and human-computer interaction. While classical ‎approaches such as Support Vector Machines (SVM), Histogram ‎of Oriented Gradients (HOG), and ...  Read More

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