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

12

Number of Articles

416

Number of Issues

33

Article View

673,694

PDF Download

568,431

View Per Article

1619.46

PDF Download Per Article

1366.42

Reject Rate %

56

Acceptance Rate %

26

Number of Reviewers

3269

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).

 

Applied Article H.3. Artificial Intelligence
Enhancing Aspect-based Sentiment Analysis with ParsBERT in Persian Language

Farid Ariai; Maryam Tayefeh Mahmoudi; Ali Moeini

Volume 12, Issue 1 , January 2024, Pages 1-14

https://doi.org/10.22044/jadm.2023.13666.2482

Abstract
  In the era of pervasive internet use and the dominance of social networks, researchers face significant challenges in Persian text mining, including the scarcity of adequate datasets in Persian and the inefficiency of existing language models. This paper specifically tackles these challenges, aiming ...  Read More

Original/Review Paper F.2.11. Applications
Low-order Robust Controller for DC-DC Quadratic Buck Converter: Design and Implementation

Ali Sedehi; Alireza Alfi; Mohammadreza Mirjafari

Volume 12, Issue 1 , January 2024, Pages 15-25

https://doi.org/10.22044/jadm.2024.13584.2475

Abstract
  This paper addresses a key challenge in designing a suitable controller for DC-DC converters to regulate the output voltage effectively within a limited time frame. In addition to non-minimum phase behavior of such type of converter, a significant issue, namely parametric uncertainty, can further complicate ...  Read More

Original/Review Paper H.5. Image Processing and Computer Vision
Automatic Brain Tumor Detection in Brain MRI Images using Deep Learning Methods

Farima Fakouri; Mohsen Nikpour; Abbas Soleymani Amiri

Volume 12, Issue 1 , January 2024, Pages 27-35

https://doi.org/10.22044/jadm.2024.13148.2452

Abstract
  Due to the increased mortality caused by brain tumors, accurate and fast diagnosis of brain tumors is necessary to implement the treatment of this disease. In this research, brain tumor classification performed using a network based on ResNet architecture in MRI images. MRI images that available in the ...  Read More

Technical Paper B.3. Communication/Networking and Information Technology
Intrusion Detection for IoT Network Security with Deep learning

Roya Morshedi; S. Mojtaba Matinkhah; Mohammad Taghi Sadeghi

Volume 12, Issue 1 , January 2024, Pages 37-55

https://doi.org/10.22044/jadm.2023.13539.2471

Abstract
  IoT devices has witnessed a substantial increase due to the growing demand for smart devices. Intrusion Detection Systems (IDS) are critical components for safeguarding IoT networks against cyber threats. This study presents an advanced approach to IoT network intrusion detection, leveraging deep learning ...  Read More

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

Sajjad Alizadeh Fard; Hossein Rahmani

Volume 12, Issue 1 , January 2024, Pages 57-66

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

Original/Review Paper 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

Original/Review Paper H.3.2.2. Computer vision
Enhancing Emotion Classification via EEG Signal Frame Selection

Masoumeh Esmaeiili; Kourosh Kiani

Volume 12, Issue 1 , January 2024, Pages 83-93

https://doi.org/10.22044/jadm.2024.13861.2502

Abstract
  The classification of emotions using electroencephalography (EEG) signals is inherently challenging due to the intricate nature of brain activity. Overcoming inconsistencies in EEG signals and establishing a universally applicable sentiment analysis model are essential objectives. This study introduces ...  Read More

Original/Review Paper H.3.15.3. Evolutionary computing and genetic algorithms
A Hybrid Machine Learning Approach and Genetic Algorithm for Malware Detection

Mahdieh Maazalahi; Soodeh Hosseini

Volume 12, Issue 1 , January 2024, Pages 95-104

https://doi.org/10.22044/jadm.2024.13895.2503

Abstract
  Detecting and preventing malware infections in systems is become a critical necessity. This paper presents a hybrid method for malware detection, utilizing data mining algorithms such as simulated annealing (SA), support vector machine (SVM), genetic algorithm (GA), and K-means. The proposed method combines ...  Read More

Technical Paper H.5. Image Processing and Computer Vision
A Novel Method for Fish Spoilage Detection based on Fish Eye Images using Deep Convolutional Inception-ResNet-v2

Sekine Asadi Amiri; Mahda Nasrolahzadeh; Zeynab Mohammadpoory; AbdolAli Movahedinia; Amirhossein Zare

Volume 12, Issue 1 , January 2024, Pages 105-113

https://doi.org/10.22044/jadm.2024.14091.2519

Abstract
  Improving the quality of food industries and the safety and health of the people’s nutrition system is one of the important goals of governments. Fish is an excellent source of protein. Freshness is one of the most important quality criteria for fish that should be selected for consumption. It ...  Read More

Original/Review Paper H.3.7. Learning
Automatic Configuration of Federated Learning Client in Graph Classification using Genetic Algorithms

Mohammad Rezaei; Mohsen Rezvani; Morteza Zahedi

Volume 12, Issue 1 , January 2024, Pages 115-126

https://doi.org/10.22044/jadm.2024.13688.2487

Abstract
  With the increasing interconnectedness of communications and social networks, graph-based learning techniques offer valuable information extraction from data. Traditional centralized learning methods faced challenges, including data privacy violations and costly maintenance in a centralized environment. ...  Read More

Original/Review Paper H.5. Image Processing and Computer Vision
Iranian Vehicle Images Dataset for Object Detection Algorithm

Pouria Maleki; Abbas Ramazani; Hassan Khotanlou; Sina Ojaghi

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

Original/Review Paper H.3. Artificial Intelligence
A Multi-View Model for Knowledge Graph Embedding in Link Prediction using GRU-RNN as Constraint Satisfaction Problem

Afrooz Moradbeiky; Farzin Yaghmaee

Volume 12, Issue 1 , January 2024, Pages 137-147

https://doi.org/10.22044/jadm.2024.13827.2498

Abstract
  Knowledge graphs are widely used tools in the field of reasoning, where reasoning is facilitated through link prediction within the knowledge graph. However, traditional methods have limitations, such as high complexity or an inability to effectively capture the structural features of the graph. The ...  Read More

H.5. Image Processing and Computer Vision
Iranian Vehicle Images Dataset for Object Detection Algorithm

Pouria Maleki; Abbas Ramazani; Hassan Khotanlou; Sina Ojaghi

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

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

H.5. Image Processing and Computer Vision
Multi-Focus Image Fusion in DCT Domain using Variance and Energy of Laplacian and Correlation Coefficient for Visual Sensor Networks

M. Amin-Naji; A. Aghagolzadeh

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

Mohammad Ahmadi Livani; mahdi Abadi; Meysam Alikhany; Meisam Yadollahzadeh Tabari

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

Mohammad AllamehAmiri; Vali Derhami; Mohammad Ghasemzadeh

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

Original/Review Paper D. Data
A Novel Combination of Segmentation, Ensemble Clustering and Genetic Algorithm for Clustering Time Series

Ali Ghorbanian; Zahra Ghorbani

Articles in Press, Accepted Manuscript, Available Online from 14 September 2024

https://doi.org/10.22044/jadm.2024.14170.2526

Abstract
  Increasing the accuracy of time-series clustering while reducing execution time is a primary challenge in the field of time-series clustering. Researchers have recently applied approaches, such as the development of distance metrics and dimensionality reduction, to address this challenge. However, using ...  Read More

Original/Review Paper H.3.9. Problem Solving, Control Methods, and Search
Event-Triggered Optimal Adaptive Leader-Follower Consensus Control for Unknown Input-Constrained Discrete-Time Nonlinear Systems

Zahra Jahan; Abbas Dideban; Farzaneh Tatari

Articles in Press, Accepted Manuscript, Available Online from 14 September 2024

https://doi.org/10.22044/jadm.2024.13779.2500

Abstract
  This paper introduces an adaptive optimal distributed algorithm based on event-triggered control to solve multi-agent discrete-time zero-sum graphical games for unknown nonlinear constrained-input systems with external disturbances. Based on the value iteration heuristic dynamic programming, the proposed ...  Read More

Original/Review Paper H.3. Artificial Intelligence
An Intelligent Blockchain-Based System Configuration for Screening, Monitoring, and Tracing of Pandemics

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

Articles in Press, Accepted Manuscript, Available Online from 14 September 2024

https://doi.org/10.22044/jadm.2024.14379.2541

Abstract
  This study proposes a high-level design and configuration for an intelligent dual (hybrid and private) blockchain-based system. The configuration includes the type of network, level of decentralization, nodes, and roles, block structure information, authority control, and smart contracts and intended ...  Read More

Original/Review Paper H.3. Artificial Intelligence
Selecting Optimal Moments of Chest Images by Partialized-Dual-Hybrid Feature Selection Scheme for Morphological-based COVID-19 Diagnosis

Seyed Alireza Bashiri Mosavi; Mohsen Javaherian; Omid Khalaf Beigi

Articles in Press, Accepted Manuscript, Available Online from 14 September 2024

https://doi.org/10.22044/jadm.2024.14359.2540

Abstract
  One way of analyzing COVID-19 is to exploit X-ray and computed tomography (CT) images of the patients' chests. Employing data mining techniques on chest images can provide in significant improvements in the diagnosis of COVID-19. However, in feature space learning of chest images, there exists a large ...  Read More

Applied Article H.5.7. Segmentation
Enhancing Image Segmentation with Darwinian Grey Wolf Optimizer: A Novel Multilevel Thresholding Approach

Ehsan Ehsaeyan

Articles in Press, Accepted Manuscript, Available Online from 15 September 2024

https://doi.org/10.22044/jadm.2024.14469.2550

Abstract
  This paper presents a novel approach to image segmentation through multilevel thresholding, leveraging the speed and precision of the technique. The proposed algorithm, based on the Grey Wolf Optimizer (GWO), integrates Darwinian principles to address the common stagnation issue in metaheuristic algorithms, ...  Read More

Original/Review Paper H.3.9. Problem Solving, Control Methods, and Search
Position Tracking Control of ASV based on Dynamic Inversion with Intelligent Methods

Heydar Toossian Shandiz; Mohsen Erfan Hajipour; Amir Ali Bagheri

Articles in Press, Accepted Manuscript, Available Online from 22 September 2024

https://doi.org/10.22044/jadm.2024.14081.2516

Abstract
  The aim of this paper is to create an efficient controller that can precisely track the position of autonomous surface vessels by utilizing the dynamic inversion control technique. One of the key objectives of this controller is to mitigate or eliminate the effects of environmental disturbances like ...  Read More

Original/Review Paper H.3.2.2. Computer vision
Exploring Object Detection Methods for Autonomous Vehicles Perception: A Comparative Study of Classical and Deep Learning Approaches

Zobeir Raisi; Valimohammad Nazarzehi; Rasoul Damani; Esmaeil Sarani

Articles in Press, Accepted Manuscript, Available Online from 22 September 2024

https://doi.org/10.22044/jadm.2024.14241.2529

Abstract
  This paper explores the performance of various object detection techniques for autonomous vehicle perception by analyzing classical machine learning and recent deep learning models. We evaluate three classical methods, including PCA, HOG, and HOG alongside different versions of the SVM classifier, and ...  Read More

Applied Article H.5. Image Processing and Computer Vision
BNPL-Dataset: A New Benchmark Dataset for Visual Disease Detection of Barberry, Jujube, and Pomegranate Trees

Jalaluddin Zarei; Mohammad Hossein Khosravi

Articles in Press, Accepted Manuscript, Available Online from 24 September 2024

https://doi.org/10.22044/jadm.2024.14480.2552

Abstract
  Agricultural experts try to detect leaf diseases in the shortest possible time. However, limitations such as lack of manpower, poor eyesight, lack of sufficient knowledge, and quarantine restrictions in the transfer of diseases to the laboratory can be acceptable reasons to use digital technology to ...  Read More

Original/Review Paper H.3.2.2. Computer vision
A Deep Learning-based Model for Fingerprint Verification

Mobina Talebian; Kourosh Kiani; Razieh Rastgoo

Articles in Press, Accepted Manuscript, Available Online from 25 September 2024

https://doi.org/10.22044/jadm.2024.14298.2531

Abstract
  Fingerprint verification has emerged as a cornerstone of personal identity authentication. This research introduces a deep learning-based framework for enhancing the accuracy of this critical process. By integrating a pre-trained Inception model with a custom-designed architecture, we propose a model ...  Read More

Other H.6.2. Models
Diagnosis and Classification of Tuberculosis Chest X-ray Images of Children Less Than 15 years at Mbarara Regional Referral Hospital Using Deep Learning

Simon Kawuma; Elias Kumbakumba; Vicent Mabirizi; Deborah Nanjebe; Kenneth Mworozi; Adolf Oyesigye Mukama; Lydia Kyasimire

Articles in Press, Accepted Manuscript, Available Online from 26 September 2024

https://doi.org/10.22044/jadm.2024.14270.2530

Abstract
  Tuberculosis (TB) is an underestimated cause of death in children, with only 45% of cases correctly diagnosed and reported. It is estimated that 1.12 million TB cases occurred among newborns, children, and adolescents aged less or equal 14 years. In Uganda, TB prevalence is 8.5% in children and 16.7% ...  Read More

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