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

8

Number of Issues

20

Article View

345,151

PDF Download

371,293

View Per Article

1297.56

PDF Download Per Article

1395.84

Reject Rate %

61

Acceptance Rate %

23

Number of Reviewers

3155

First Decision

(Approximately)

49(Days)

 

The Journal of Artificial Intelligence & Data Mining (JAIDM) is an international 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 A.10. Power Management
1. Fuzzy Adaptive Granulation Multi-Objective Multi-microgrid Energy Management

F. Sabahi

Volume 8, Issue 4 , Autumn 2020, Pages 481-489

http://dx.doi.org/10.22044/jadm.2019.6985.1828

Abstract
  This paper develops an energy management approach for a multi-microgrid (MMG) taking into account multiple objectives involving plug-in electric vehicle (PEV), photovoltaic (PV) power, and a distribution static compensator (DSTATCOM) to improve power provision sharing. In the proposed approach, there ...  Read More

Original/Review Paper
2. A Deep Model for Super-resolution Enhancement from a Single Image

N. Majidi; K. Kiani; R. Rastgoo

Volume 8, Issue 4 , Autumn 2020, Pages 451-460

http://dx.doi.org/10.22044/jadm.2020.9131.2052

Abstract
  This study presents a method to reconstruct a high-resolution image using a deep convolution neural network. We propose a deep model, entitled Deep Block Super Resolution (DBSR), by fusing the output features of a deep convolutional network and a shallow convolutional network. In this way, our model ...  Read More

Original/Review Paper
3. Multi-View Face Detection in Open Environments using Gabor Features and Neural Networks

R. Mohammadian; M. Mahlouji; A. Shahidinejad

Volume 8, Issue 4 , Autumn 2020, Pages 461-470

http://dx.doi.org/10.22044/jadm.2020.8853.2019

Abstract
  Multi-view face detection in open environments is a challenging task, due to the wide variations in illumination, face appearances and occlusion. In this paper, a robust method for multi-view face detection in open environments, using a combination of Gabor features and neural networks, is presented. ...  Read More

Original/Review Paper
4. A Monte Carlo-Based Search Strategy for Dimensionality Reduction in Performance Tuning Parameters

A. Omondi; I.A. Lukandu; G.W. Wanyembi

Volume 8, Issue 4 , Autumn 2020, Pages 471-480

http://dx.doi.org/10.22044/jadm.2020.9403.2076

Abstract
  Redundant and irrelevant features in high dimensional data increase the complexity in underlying mathematical models. It is necessary to conduct pre-processing steps that search for the most relevant features in order to reduce the dimensionality of the data. This study made use of a meta-heuristic search ...  Read More

Original/Review Paper
5. Optimizing Membership Functions using Learning Automata for Fuzzy Association Rule Mining

Z. Anari; A. Hatamlou; B. Anari; M. Masdari

Volume 8, Issue 4 , Autumn 2020, Pages 491-514

http://dx.doi.org/10.22044/jadm.2020.8928.2029

Abstract
  The Transactions in web data often consist of quantitative data, suggesting that fuzzy set theory can be used to represent such data. The time spent by users on each web page is one type of web data, was regarded as a trapezoidal membership function (TMF) and can be used to evaluate user browsing behavior. ...  Read More

Original/Review Paper
6. A Fuzzy C-means Algorithm for Clustering Fuzzy Data and Its Application in Clustering Incomplete Data

J. Tayyebi; E. Hosseinzadeh

Volume 8, Issue 4 , Autumn 2020, Pages 515-523

http://dx.doi.org/10.22044/jadm.2020.9021.2038

Abstract
  The fuzzy c-means clustering algorithm is a useful tool for clustering; but it is convenient only for crisp complete data. In this article, an enhancement of the algorithm is proposed which is suitable for clustering trapezoidal fuzzy data. A linear ranking function is used to define a distance for trapezoidal ...  Read More

Original/Review Paper
7. A Combinatorial Algorithm for Fuzzy Parameter Estimation with Application to Uncertain Measurements

M. Danesh; S. Danesh

Volume 8, Issue 4 , Autumn 2020, Pages 525-533

http://dx.doi.org/10.22044/jadm.2020.8610.1996

Abstract
  This paper presents a new method for regression model prediction in an uncertain environment. In practical engineering problems, in order to develop regression or ANN model for making predictions, the average of set of repeated observed values are introduced to the model as an input variable. Therefore, ...  Read More

Original/Review Paper
8. Modeling Length of Hydraulic Jump on Sloping Rough Bed using Gene Expression Programming

I Pasandideh; A. Rajabi; F. Yosefvand; S. Shabanlou

Volume 8, Issue 4 , Autumn 2020, Pages 535-544

http://dx.doi.org/10.22044/jadm.2020.7444.1886

Abstract
  Generally, length of hydraulic jump is one the most important parameters to design stilling basin. In this study, the length of hydraulic jump on sloping rough beds was predicted using Gene Expression Programming (GEP) for the first time. The Monte Carlo simulations were used to examine the ability of ...  Read More

Applied Article
9. DINGA: A Genetic-algorithm-based Method for Finding Important Nodes in Social Networks

H. Rahmani; H. Kamali; H. Shah-Hosseini

Volume 8, Issue 4 , Autumn 2020, Pages 545-555

http://dx.doi.org/10.22044/jadm.2020.9025.2040

Abstract
  Nowadays, a significant amount of studies are devoted to discovering important nodes in graph data. Social networks as graph data have attracted a lot of attention. There are various purposes for discovering the important nodes in social networks such as finding the leaders in them, i.e. the users who ...  Read More

Methodologies
10. A New Incentive Mechanism to Detect and Restrict Sybil Nodes in P2P File-Sharing Networks with a Heterogeneous Bandwidth

M. Babazadeh Shareh; H.R. Navidi; H. Haj Seyed Javadi; M. HosseinZadeh

Volume 8, Issue 4 , Autumn 2020, Pages 557-571

http://dx.doi.org/10.22044/jadm.2020.9063.2049

Abstract
  In cooperative P2P networks, there are two kinds of illegal users, namely free riders and Sybils. Free riders are those who try to receive services without any sort of cost. Sybil users are rational peers which have multiple fake identities. There are some techniques to detect free riders and Sybil users ...  Read More

Original/Review Paper
11. A Recommendation System for Finding Experts in Online Scientific Communities

S. Javadi; R. Safa; M. Azizi; Seyed A. Mirroshandel

Volume 8, Issue 4 , Autumn 2020, Pages 573-584

http://dx.doi.org/10.22044/jadm.2020.9087.2045

Abstract
  Online scientific communities are bases that publish books, journals, and scientific papers, and help promote knowledge. The researchers use search engines to find the given information including scientific papers, an expert to collaborate with, and the publication venue, but in many cases due to search ...  Read More

Applied Article
12. Joint Burst Denoising and Demosaicking via Regularization and an Efficient Alignment

R. Azizi; A. M. Latif

Volume 8, Issue 4 , Autumn 2020

http://dx.doi.org/10.22044/jadm.2020.9193.2055

Abstract
  In this work, we show that an image reconstruction from a burst of individually demosaicked RAW captures propagates demosaicking artifacts throughout the image processing pipeline. Hence, we propose a joint regularization scheme for burst denoising and demosaicking. We model the burst alignment functions ...  Read More

1. 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

H.5. Image Processing and Computer Vision
2. 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 , Summer 2018, , Pages 233-250

http://dx.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

3. 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 , Winter 2013, , Pages 1-11

http://dx.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

4. 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 , Summer 2014, , Pages 97-104

http://dx.doi.org/10.22044/jadm.2014.148

Abstract
  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

5. QoS-Based web service composition based on genetic algorithm

Mohammad AllamehAmiri; Vali Derhami; Mohammad Ghasemzadeh

Volume 1, Issue 2 , Summer 2013, , Pages 63-73

http://dx.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
1. IRVD: A Large-Scale Dataset for Classification of Iranian Vehicles in Urban Streets

H. Gholamalinejad; H. Khosravi

Articles in Press, Accepted Manuscript, Available Online from 09 June 2020

http://dx.doi.org/10.22044/jadm.2020.8438.1982

Abstract
  In recent years, vehicle classification has been one of the most important research topics. However, due to the lack of a proper dataset, this field has not been well developed as other fields of intelligent traffic management. Therefore, the preparation of large-scale datasets of vehicles for each country ...  Read More

Original/Review Paper
2. Probabilistic Reasoning and Markov Chains as Means to Improve Performance of Tuning Decisions under Uncertainty

A. Omondi; I. Lukandu; G. Wanyembi

Articles in Press, Accepted Manuscript, Available Online from 09 September 2020

http://dx.doi.org/10.22044/jadm.2020.8920.2027

Abstract
  Variable environmental conditions and runtime phenomena require developers of complex business information systems to expose configuration parameters to system administrators. This allows system administrators to intervene by tuning the bottleneck configuration parameters in response to current changes ...  Read More

Original/Review Paper
3. A Novel Hierarchical Attention-based Method for Aspect-level Sentiment Classification

A. Lakizadeh; Z. Zinaty

Articles in Press, Accepted Manuscript, Available Online from 12 September 2020

http://dx.doi.org/10.22044/jadm.2020.9579.2091

Abstract
  Aspect-level sentiment classification is an essential issue in sentiment analysis that intends to resolve the sentiment polarity of a specific aspect mentioned in the input text. Recent methods have discovered the role of aspects in sentiment polarity classification and developed various techniques to ...  Read More

Original/Review Paper
4. Detecting Sinkhole Attack in RPL-based Internet of Things Routing Protocol

M. Yadollahzadeh Tabari; Z. Mataji

Articles in Press, Accepted Manuscript, Available Online from 12 September 2020

http://dx.doi.org/10.22044/jadm.2020.9253.2060

Abstract
  The Internet of Things (IoT) is a novel paradigm in computer networks which is capable to connect things to the internet via a wide range of technologies. Due to the features of the sensors used in IoT networks and the unsecured nature of the internet, IoT is vulnerable to many internal routing attacks. ...  Read More

Original/Review Paper
5. A No-Reference Blur Metric based on Second-Order Gradients of Image

T. Askari; A. Alidadi; S.R. Arab

Articles in Press, Accepted Manuscript, Available Online from 13 December 2020

http://dx.doi.org/10.22044/jadm.2020.9309.2068

Abstract
  Estimation of blurriness value in image is an important issue in image processing applications such as image deblurring. In this paper, a no-reference blur metric with low computational cost is proposed, which is based on the difference between the second order gradients of a sharp image and the one ...  Read More

Original/Review Paper
6. An Image Restoration Architecture using Abstract Features and Generative Models

A. Fakhari; K. Kiani

Articles in Press, Accepted Manuscript, Available Online from 14 December 2020

http://dx.doi.org/10.22044/jadm.2020.9691.2101

Abstract
  Image restoration and its different variations are important topics in low-level image processing. One of the main challenges in image restoration is dependency of current methods to the corruption characteristics. In this paper, we have proposed an image restoration architecture that enables us to address ...  Read More

Technical Paper
7. Face Recognition using Color and Edge Orientation Difference Histogram

S. Asadi Amiri; M. Rajabinasab

Articles in Press, Accepted Manuscript, Available Online from 09 January 2021

http://dx.doi.org/10.22044/jadm.2020.9376.2072

Abstract
  Face recognition is a challenging problem because of different illuminations, poses, facial expressions, and occlusions. In this paper, a new robust face recognition method is proposed based on color and edge orientation difference histogram. Firstly, color and edge orientation difference histogram is ...  Read More

Original/Review Paper
8. A Novel Approach to Communicate with Video Game Character using Cascade Classifiers

M. Mohammadzadeh; H. Khosravi

Articles in Press, Accepted Manuscript, Available Online from 09 January 2021

http://dx.doi.org/10.22044/jadm.2020.9788.2110

Abstract
  Today, video games have a special place among entertainment. In this article, we have developed an interactive video game for mobile devices. In this game, the user can control the game’s character by his face and hand gestures. Cascading classifiers along with Haar-like features and local binary ...  Read More

Original/Review Paper
9. Estimating Pier Scour Depth: Comparison of Empirical Formulations with ANNs, GMDH, MARS, and Kriging

M. Zarbazoo Siahkali; A.A. Ghaderi; Abdol H. Bahrpeyma; M. Rashki; N. Safaeian Hamzehkolaei

Articles in Press, Accepted Manuscript, Available Online from 13 January 2021

http://dx.doi.org/10.22044/jadm.2020.10085.2147

Abstract
  Scouring, occurring when the water flow erodes the bed materials around the bridge pier structure, is a serious safety assessment problem for which there are many equations and models in the literature to estimate the approximate scour depth. This research is aimed to study how surrogate models estimate ...  Read More

Original/Review Paper
10. Automatic Persian Text Emotion Detection using Cognitive Linguistic and Deep Learning

Seyedeh S. Sadeghi; H. Khotanlou; M. Rasekh Mahand

Articles in Press, Accepted Manuscript, Available Online from 18 January 2021

http://dx.doi.org/10.22044/jadm.2020.9992.2136

Abstract
  In the modern age, written sources are rapidly increasing. A growing number of these data are related to the texts containing the feelings and opinions of the users. Thus, reviewing and analyzing of emotional texts have received a particular attention in recent years. A System which is based on combination ...  Read More

Original/Review Paper
11. Convolutional Neural Network Equipped with Attention Mechanism and Transfer Learning for Enhancing Performance of Sentiment Analysis

H. Sadr; Mir M. Pedram; M. Teshnehlab

Articles in Press, Accepted Manuscript, Available Online from 07 February 2021

http://dx.doi.org/10.22044/jadm.2021.9618.2100

Abstract
  With the rapid development of textual information on the web, sentiment analysis is changing to an essential analytic tool rather than an academic endeavor and numerous studies have been carried out in recent years to address this issue. By the emergence of deep learning, deep neural networks have attracted ...  Read More

Original/Review Paper
12. Feature Selection based on Particle Swarm Optimization and Mutual Information

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

Articles in Press, Accepted Manuscript, Available Online from 17 February 2021

http://dx.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

Original/Review Paper
13. Facial Expression Recognition based on Image Gradient and Deep Convolutional Neural Network

M. R. Fallahzadeh; F. Farokhi; A. Harimi; R. Sabbaghi-Nadooshan

Articles in Press, Accepted Manuscript, Available Online from 17 February 2021

http://dx.doi.org/10.22044/jadm.2021.9898.2121

Abstract
  Facial Expression Recognition (FER) is one of the basic ways of interacting with machines and has been getting more attention in recent years. In this paper, a novel FER system based on a deep convolutional neural network (DCNN) is presented. Motivated by the powerful ability of DCNN to learn features ...  Read More

Original/Review Paper
14. GroupRank: Ranking Online Social Groups Based on User Membership Records

A. Hashemi; M. A. Zare Chahooki

Articles in Press, Accepted Manuscript, Available Online from 22 February 2021

http://dx.doi.org/10.22044/jadm.2020.8337.1973

Abstract
  Social networks are valuable sources for marketers. Marketers can publish campaigns to reach target audiences according to their interest. Although Telegram was primarily designed as an instant messenger, it is used as a social network in Iran due to censorship of Facebook, Twitter, etc. Telegram neither ...  Read More

Original/Review Paper
15. Bio-inspired Computing Paradigm for Periodic‎ Noise Reduction in Digital Images

N. Alibabaie; A.M. Latif

Articles in Press, Accepted Manuscript, Available Online from 22 February 2021

http://dx.doi.org/10.22044/jadm.2020.9358.2071

Abstract
  Periodic noise reduction is a fundamental problem in image processing, which severely affects the visual quality and subsequent application of the data. Most of the conventional approaches are only dedicated to either the frequency or spatial domain. In this research, we propose a dual-domain approach ...  Read More

Original/Review Paper
16. A Distributed Sailfish Optimizer Based on Multi-Agent Systems for Solving Non-Convex and Scalable Optimization Problems Implemented on GPU

S. Shadravan; H. Naji; V. Khatibi

Articles in Press, Accepted Manuscript, Available Online from 27 February 2021

http://dx.doi.org/10.22044/jadm.2020.9389.2075

Abstract
  The SailFish Optimizer (SFO) is a metaheuristic algorithm inspired by a group of hunting sailfish that alternates their attacks on group of prey. The SFO algorithm takes advantage of using a simple method for providing the dynamic balance between exploration and exploitation phases, creating the swarm ...  Read More

Original/Review Paper
17. Online Recommender System Considering Changes in User's Preference

J. Hamidzadeh; M. Moradi

Articles in Press, Accepted Manuscript, Available Online from 06 March 2021

http://dx.doi.org/10.22044/jadm.2020.9518.2085

Abstract
  Recommender systems extract unseen information for predicting the next preferences. Most of these systems use additional information such as demographic data and previous users' ratings to predict users' preferences but rarely have used sequential information. In streaming recommender systems, the emergence ...  Read More

Original/Review Paper
18. ParsNER-Social: A Corpus for Named Entity Recognition in Persian Social Media Texts

M. Asgari-Bidhendi; B. Janfada; O. R. Roshani Talab; B. Minaei-Bidgoli

Articles in Press, Accepted Manuscript, Available Online from 08 March 2021

http://dx.doi.org/10.22044/jadm.2020.9949.2143

Abstract
  Named Entity Recognition (NER) is one of the essential prerequisites for many natural language processing tasks. All public corpora for Persian named entity recognition, such as ParsNERCorp and ArmanPersoNERCorpus, are based on the Bijankhan corpus, which is originated from the Hamshahri newspaper in ...  Read More

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