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)

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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).


Original/Review Paper
Classification of sEMG Signals for Diagnosis of Unilateral Posterior Crossbite in Primary Dentition using Fast Fourier Transform and Logistic Regression

H. Kalani; E. Abbasi

Volume 10, Issue 2 , April 2022, Pages 151-158


  Posterior crossbite is a common malocclusion disorder in the primary dentition that strongly affects masticatory function. To the best of the author’s knowledge, for the first time, this article presents a reasonable and computationally efficient diagnostic system for detecting characteristics ...  Read More

Original/Review Paper
Clustering Methods to Analyze Social Media Posts during Coronavirus Pandemic in Iran

F. Amiri; S. Abbasi; M. Babaie mohamadeh

Volume 10, Issue 2 , April 2022, Pages 159-169


  During the COVID-19 crisis, we face a wide range of thoughts, feelings, and behaviors on social media that play a significant role in spreading information regarding COVID-19. Trustful information, together with hopeful messages, could be used to control people's emotions and reactions during pandemics. ...  Read More

Technical Paper
Abnormal Behavior Detection over Normal Data and Abnormal-augmented Data in Crowded Scenes

V. Fazel Asl; B. Karasfi; B. Masoumi

Volume 10, Issue 2 , April 2022, Pages 171-183


  In this article, we consider the problems of abnormal behavior detection in a high-crowded environment. One of the main issues in abnormal behavior detection is the complexity of the structure patterns between the frames. In this paper, social force and optical flow patterns are used to prepare the system ...  Read More

Original/Review Paper
Increasing Performance of Recommender Systems by Combining Deep Learning and Extreme Learning Machine

Z. Nazari; H.R. Koohi; J. Mousavi

Volume 10, Issue 2 , April 2022, Pages 185-195


  Nowadays, with the expansion of the internet and its associated technologies, recommender systems have become increasingly common. In this work, the main purpose is to apply new deep learning-based clustering methods to overcome the data sparsity problem and increment the efficiency of recommender systems ...  Read More

Applied Article
Distributed Online Pre-Processing Framework for Big Data Sentiment Analytics

M. Molaei; D. Mohamadpur

Volume 10, Issue 2 , April 2022, Pages 197-205


  Performing sentiment analysis on social networks big data can be helpful for various research and business projects to take useful insights from text-oriented content. In this paper, we propose a general pre-processing framework for sentiment analysis, which is devoted to adopting FastText with Recurrent ...  Read More

Automatic Detection of Lung Nodules on Computer Tomography Scans with a Deep Direct Regression Method

Kh. Aghajani

Volume 10, Issue 2 , April 2022, Pages 207-215


  Deep-learning-based approaches have been extensively used in detecting pulmonary nodules from computer Tomography (CT) scans. In this study, an automated end-to-end framework with a convolution network (Conv-net) has been proposed to detect lung nodules from CT images. Here, boundary regression has been ...  Read More

Original/Review Paper
Automatic Visual Inspection System based on Image Processing and Neural Network for Quality Control of Sandwich Panel

V. Torkzadeh; S. Toosizadeh

Volume 10, Issue 2 , April 2022, Pages 217-231


  In this study, an automatic system based on image processing methods using features based on convolutional neural networks is proposed to detect the degree of possible dipping and buckling on the sandwich panel surface by a colour camera. The proposed method, by receiving an image of the sandwich panel, ...  Read More

Original/Review Paper
A Hybrid Deep Network Representation Model for Detecting Researchers’ Communities

A. Torkaman; K. Badie; A. Salajegheh; M. H. Bokaei; Seyed F. Fatemi

Volume 10, Issue 2 , April 2022, Pages 233-243


  Recently, network representation has attracted many research works mostly concentrating on representing of nodes in a dense low-dimensional vector. There exist some network embedding methods focusing only on the node structure and some others considering the content information within the nodes. In this ...  Read More

Original/Review Paper
A new Approach to Estimate Motion and Structure of a Moving Rigid Object in a 3D Space with a Single Hand-Held Camera

R. Serajeh; A. Mousavinia; F. Safaei

Volume 10, Issue 2 , April 2022, Pages 245-256


  Classical SFM (Structure From Motion) algorithms are widely used to estimate the three-dimensional structure of a stationary scene with a moving camera. However, when there are moving objects in the scene, if the equation of the moving object is unknown, the approach fails. This paper first demonstrates ...  Read More

Original/Review Paper
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


  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

Original/Review Paper
Detecting Group Review Spammers in Social Media

Z. Teimoori; M. Salehi; V. Ranjbar; Saeed R. Shehnepoor; Sh. Najari

Volume 10, Issue 2 , April 2022, Pages 269-283


  Nowadays, some e-advice websites and social media like e-commerce businesses, provide not only their goods but a new way that their customers can give their opinions about products. Meanwhile, there are some review spammers who try to promote or demote some specific products by writing fraud reviews. ...  Read More

Original/Review Paper
AgriNet: a New Classifying Convolutional Neural Network for Detecting Agricultural Products’ Diseases

F. Salimian Najafabadi; M. T. Sadeghi

Volume 10, Issue 2 , April 2022, Pages 285-302


  An important sector that has a significant impact on the economies of countries is the agricultural sector. Researchers are trying to improve this sector by using the latest technologies. One of the problems facing farmers in the agricultural activities is plant diseases. If a plant problem is diagnosed ...  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


  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


  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


  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


  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

On improving APIT algorithm for better localization in WSN

Seyed M. Hosseinirad; M. Niazi; J Pourdeilami; S. K. Basu; A. A. Pouyan

Volume 2, Issue 2 , July 2014, , Pages 97-104


  In Wireless Sensor Networks (WSNs), localization algorithms could be range-based or range-free. The Approximate Point in Triangle (APIT) is a range-free approach. We propose modification of the APIT algorithm and refer as modified-APIT. We select suitable triangles with appropriate distance between anchors ...  Read More

Original/Review Paper
A Novel Classification and Diagnosis of Multiple Sclerosis Method using Artificial Neural Networks and Improved Multi-Level Adaptive Conditional Random Fields

Seyedeh R. Mahmudi Nezhad Dezfouli; Y. Kyani; Seyed A. Mahmoudinejad Dezfouli

Articles in Press, Accepted Manuscript, Available Online from 27 February 2022


  Due to the small size, low contrast, variable position, shape, and texture of multiple sclerosis lesions, one of the challenges of medical image processing is the automatic diagnosis and segmentation of multiple sclerosis lesions in Magnetic resonance images. Early diagnosis of these lesions in the first ...  Read More

Original/Review Paper F.2. Numerical Analysis
Upgrading the Human Development Index (HDI) to control pandemic mortality rates: A data mining approach to COVID-19

S. Sareminia

Articles in Press, Accepted Manuscript, Available Online from 04 May 2022


  In recent years, the occurrence of various pandemics (COVID-19, SARS, etc.) and their widespread impact on human life have led researchers to focus on their pathology and epidemiology components. One of the most significant inconveniences of these epidemics is the human mortality rate, which has highly ...  Read More

Original/Review Paper
Voice Activity Detection using Clustering-based Method in Spectro-Temporal Features Space

N. Esfandian; F. Jahani bahnamiri; S. Mavaddati

Articles in Press, Accepted Manuscript, Available Online from 14 May 2022


  This paper proposes a novel method for voice activity detection based on clustering in spectro-temporal domain. In the proposed algorithms, auditory model is used to extract the spectro-temporal features. Gaussian Mixture Model and WK-means clustering methods are used to decrease dimensions of the spectro-temporal ...  Read More

Q-LVS: A Q-learning-based algorithm for video streaming in peer-to-peer networks considering a token-based incentive mechanism

Z. Imanimehr

Articles in Press, Accepted Manuscript, Available Online from 21 May 2022


  Peer-to-peer video streaming has reached great attention during recent years. Video streaming in peer-to-peer networks is a good way to stream video on the Internet due to the high scalability, high video quality, and low bandwidth requirements. In this paper the issue of live video streaming in peer-to-peer ...  Read More

Original/Review Paper
A random scheme to implement m-connected k-covering wireless sensor networks

V. Ghasemi; A. Ghanbari

Articles in Press, Accepted Manuscript, Available Online from 01 June 2022


  Deploying m-connected k-covering (MK) wireless sensor networks (WSNs) is crucial for reliable packet delivery and target coverage. This paper proposes implementing random MK WSNs based on expected m-connected k-covering (EMK) WSNs. We define EMK WSNs as random WSNs mathematically expected to be both ...  Read More

Original/Review Paper H.3.8. Natural Language Processing
A Transformer-based Approach for Persian Text Chunking

P. Kavehzadeh; M. M. Abdollah Pour; S. Momtazi

Articles in Press, Accepted Manuscript, Available Online from 20 June 2022


  Over the last few years, text chunking has taken a significant part in sequence labeling tasks. Although a large variety of methods have been proposed for shallow parsing in English, most proposed approaches for text chunking in Persian language are based on simple and traditional concepts. In this paper, ...  Read More

Automatic Control and Guidance of Mobile Robot using Machine Learning Methods

S. Ghandibidgoli; H. Mokhtari

Articles in Press, Accepted Manuscript, Available Online from 25 June 2022


  In many applications of the robotics, the mobile robot should be guided from a source to a specific destination. The automatic control and guidance of a mobile robot is a challenge in the context of robotics. So, in current paper, this problem is studied using various machine learning methods. Controlling ...  Read More

Original/Review Paper
Energy-Efficient Timing Assignment of Tasks to Actors in WSANs

M. R. Okhovvat; M. T. Kheirabadi; A. Nodehi; M. Okhovvat

Articles in Press, Accepted Manuscript, Available Online from 25 June 2022


  Minimizing make-span and maximizing remaining energy are usually of chief importance in the applications of wireless sensor actor networks (WSANs). Current task assignment approaches are typically concerned with one of the timing or energy constraints. These approaches do not consider the types and various ...  Read More

Original/Review Paper
A Simulated Annealing-based Throughput-aware Task Mapping Algorithm for Manycore Processors

A.R. Tajary; H. Morshedlou

Articles in Press, Accepted Manuscript, Available Online from 02 July 2022


  With the advent of having many processor cores on a single chip in many-core processors, the demand for exploiting these on-chip resources to boost the performance of applications has been increased. Task mapping is the problem of mapping the application tasks on these processor cores to achieve lower ...  Read More

Original/Review Paper
Determining parameters of DBSCAN Algorithm in Dynamic Environments Automatically using Dynamic Multi-objective Genetic Algorithm

Z. Falahiazar; A.R. Bagheri; M. Reshadi

Articles in Press, Accepted Manuscript, Available Online from 17 July 2022


  Spatio-temporal (ST) clustering is a relatively new field in data mining with great popularity, especially in geographic information. Moving objects are a type of ST data where the available information on these objects includes their last position. The strategy of performing the clustering operation ...  Read More

Applied Article
Video prediction using multi-scale deep neural networks

Nima Shayanfar; Vali Derhami; Mehdi Rezaeian

Articles in Press, Accepted Manuscript, Available Online from 25 July 2022


  In video prediction it is expected to predict next frame of video by providing a sequence of input frames. Whereas numerous studies exist that tackle frame prediction, suitable performance is not still achieved and therefore the application is an open problem. In this article multiscale processing is ...  Read More

Methodologies H.3.11. Vision and Scene Understanding
A bilingual text detection in natural images using heuristic and unsupervised learning

Somayye Bayatpour; M. Sharghi

Articles in Press, Accepted Manuscript, Available Online from 03 August 2022


  Digital images are being produced in a massive number every day. Acomponent that may exist in digital images is text. Textual information can beextracted and used in a variety of fields. Noise, blur, distortions, occlusion, fontvariation, alignments, and orientation, are among the main challenges for ...  Read More

Applied Article
Classification of skin lesions By Tda alongside xception neural network

N. Elyasi; M. Hosseini Moghadam

Articles in Press, Accepted Manuscript, Available Online from 13 August 2022


  In this paper, we use the topological data analysis (TDA) mapper algorithm alongside a deep convolutional neural network in order to classify some medical images.Deep learning models and convolutional neural networks can capture the Euclidean relation of a data point with its neighbor data points like ...  Read More

Original/Review Paper
Whitened gradient descent, a new updating method for optimizers in deep neural networks

H. Gholamalinejad; H. Khosravi

Articles in Press, Accepted Manuscript, Available Online from 20 August 2022


  Optimizers are vital components of deep neural networks that perform weight updates. This paper introduces a new updating method for optimizers based on gradient descent, called whitened gradient descent (WGD). This method is easy to implement and can be used in every optimizer based on the gradient ...  Read More

Original/Review Paper
An Ensemble Convolutional Neural Networks for Detection of Growth Anomalies in Children with X-ray Images

H. Sarabi; F. Abdali-Mohammadi

Articles in Press, Accepted Manuscript, Available Online from 21 August 2022


  Bone age assessment is a method that is constantly used for investigating growth abnormalities, endocrine gland treatment, and pediatric syndromes. Since the advent of digital imaging, for several decades the bone age assessment has been performed by visually examining the ossification of the left hand, ...  Read More

Original/Review Paper
A UKF-based Approach for Indoor Camera Trajectory Estimation

Seyyed A. Hoseini; P. Kabiri

Articles in Press, Accepted Manuscript, Available Online from 21 August 2022


  When a camera moves in an unfamiliar environment, for many computer vision and robotic applications it is desirable to estimate camera position and orientation. Camera tracking is perhaps the most challenging part of Visual Simultaneous Localization and Mapping (Visual SLAM) and Augmented Reality problems. ...  Read More

Technical Paper H.5. Image Processing and Computer Vision
A Novel Content-based Image Retrieval System using Fusing Color and Texture Features

S. Asadi Amiri; Z. Mohammadpoory; M. Nasrolahzadeh

Articles in Press, Accepted Manuscript, Available Online from 22 August 2022


  Content based image retrieval (CBIR) systems compare a query image with images in a dataset to find similar images to a query image. In this paper a novel and efficient CBIR system is proposed using color and texture features. The color features are represented by color moments and color histograms of ...  Read More

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