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

18

Article View

306,492

PDF Download

341,146

View Per Article

1326.81

PDF Download Per Article

1476.82

Reject Rate %

63

Acceptance Rate %

23

Number of Reviewers

3110

First Decision

(Approximately)

56(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 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).

J.10.3. Financial
1. Credit Card Fraud Detection using Data mining and Statistical Methods

S. Beigi; M.R. Amin Naseri

Volume 8, Issue 2 , Spring 2020, Pages 149-160

Abstract
  Due to today’s advancement in technology and businesses, fraud detection has become a critical component of financial transactions. Considering vast amounts of data in large datasets, it becomes more difficult to detect fraud transactions manually. In this research, we propose a combined method ...  Read More

H.5. Image Processing and Computer Vision
2. Sparse Structured Principal Component Analysis and Model Learning for Classification and Quality Detection of Rice Grains

S. Mavaddati

Volume 8, Issue 2 , Spring 2020, Pages 161-175

Abstract
  In scientific and commercial fields associated with modern agriculture, the categorization of different rice types and determination of its quality is very important. Various image processing algorithms are applied in recent years to detect different agricultural products. The problem of rice classification ...  Read More

H.3. Artificial Intelligence
3. Hand Gesture Recognition from RGB-D Data using 2D and 3D Convolutional Neural Networks: a comparative study

M. Kurmanji; F. Ghaderi

Volume 8, Issue 2 , Spring 2020, Pages 177-188

Abstract
  Despite considerable enhances in recognizing hand gestures from still images, there are still many challenges in the classification of hand gestures in videos. The latter comes with more challenges, including higher computational complexity and arduous task of representing temporal features. Hand movement ...  Read More

C.3. Software Engineering
4. A Hybrid Meta-heuristic Approach to Cope with State Space Explosion in Model Checking Technique for Deadlock Freeness

N. Rezaee; H. Momeni

Volume 8, Issue 2 , Spring 2020, Pages 189-199

Abstract
  Model checking is an automatic technique for software verification through which all reachable states are generated from an initial state to finding errors and desirable patterns. In the model checking approach, the behavior and structure of system should be modeled. Graph transformation system is a ...  Read More

D. Data
5. Community Detection using a New Node Scoring and Synchronous Label Updating of Boundary Nodes in Social Networks

M. Zarezade; E. Nourani; Asgarali Bouyer

Volume 8, Issue 2 , Spring 2020, Pages 201-212

Abstract
  Community structure is vital to discover the important structures and potential property of complex networks. In recent years, the increasing quality of local community detection approaches has become a hot spot in the study of complex network due to the advantages of linear time complexity and applicable ...  Read More

B.3. Communication/Networking and Information Technology
6. Improving Performance of Opportunistic Routing Protocol using Fuzzy Logic for Vehicular Ad-hoc Networks in Highways

A. Azimi Kashani; M. Ghanbari; A. M. Rahmani

Volume 8, Issue 2 , Spring 2020, Pages 213-226

Abstract
  Vehicular ad hoc networks are an emerging technology with an extensive capability in various applications including vehicles safety, traffic management and intelligent transportation systems. Considering the high mobility of vehicles and their inhomogeneous distributions, designing an efficient routing ...  Read More

H.3.8. Natural Language Processing
7. A Novel Approach to Conditional Random Field-based Named Entity Recognition using Persian Specific Features

L. Jafar Tafreshi; F. Soltanzadeh

Volume 8, Issue 2 , Spring 2020, Pages 227-236

Abstract
  Named Entity Recognition is an information extraction technique that identifies name entities in a text. Three popular methods have been conventionally used namely: rule-based, machine-learning-based and hybrid of them to extract named entities from a text. Machine-learning-based methods have good performance ...  Read More

H.6.3.2. Feature evaluation and selection
8. H-BwoaSvm: A Hybrid Model for Classification and Feature Selection of Mammography Screening Behavior Data

E. Enayati; Z. Hassani; M. Moodi

Volume 8, Issue 2 , Spring 2020, Pages 237-245

Abstract
  Breast cancer is one of the most common cancer in the world. Early detection of cancers cause significantly reduce in morbidity rate and treatment costs. Mammography is a known effective diagnosis method of breast cancer. A way for mammography screening behavior identification is women's awareness evaluation ...  Read More

9. Identification of Factors Affecting Quality of Teaching Engineering Drawing using a Hybrid MCDM Model

H. Haghshenas Gorgani; A. R. Jahantigh Pak

Volume 8, Issue 2 , Spring 2020, Pages 247-267

Abstract
  Identification of the factors affecting teaching quality of engineering drawing and interaction between them is necessary until it is determined which manipulation will improve the quality of teaching this course. Since the above issue is a Multi-Criteria Decision Making (MCDM) problem and on the other ...  Read More

F.3.3. Graph Theor
10. A New Reliable Controller Placement Model for Software-Defined WANs

A. Jalili; M. Keshtgari

Volume 8, Issue 2 , Spring 2020, Pages 269-277

Abstract
  Software-Defined Network (SDNs) is a decoupled architecture that enables administrators to build a customizable and manageable network. Although the decoupled control plane provides flexible management and facilitates the task of operating the network, it is the vulnerable point of failure in SDN. To ...  Read More

11. A Hybrid Business Success Versus Failure Classification Prediction Model: A Case of Iranian Accelerated Start-ups

Seyed M. Sadatrasoul; O. Ebadati; R. Saedi

Volume 8, Issue 2 , Spring 2020, Pages 279-287

Abstract
  The purpose of this study is to reduce the uncertainty of early stage startups success prediction and filling the gap of previous studies in the field, by identifying and evaluating the success variables and developing a novel business success failure (S/F) data mining classification prediction model ...  Read More

H.5. Image Processing and Computer Vision
12. Statistical Wavelet-based Image Denoising using Scale Mixture of Normal Distributions with Adaptive Parameter Estimation

M. Saeedzarandi; H. Nezamabadi-pour; S. Saryazdi

Volume 8, Issue 2 , Spring 2020, Pages 289-301

Abstract
  Removing noise from images is a challenging problem in digital image processing. This paper presents an image denoising method based on a maximum a posteriori (MAP) density function estimator, which is implemented in the wavelet domain because of its energy compaction property. The performance of the ...  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

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

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

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

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

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

H.4.7. Methodology and Techniques
1. Local Coordinate Exhaustive Search Hybridization Enhancing Big Bang-Big Crunch and Particle Swarm Optimization Algorithms

Osman K. Erol; Ibrahim Eksin

Articles in Press, Accepted Manuscript, Available Online from 26 October 2019

Abstract
  In general, all of the hybridized evolutionary optimization algorithms use “first diversification and then intensification” routine approach. In other words, these hybridized methods all begin with a global search mode using a highly random initial search population and then switch to intense ...  Read More

A.10. Power Management
2. Fuzzy Adaptive Granulation Multi-Objective Multi-microgrid Energy Management

F. Sabahi

Articles in Press, Accepted Manuscript, Available Online from 26 October 2019

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

3. Solving Traveling Salesman Problem based on Biogeography-based Optimization and Edge Assembly Cross-over

A. Salehi; B. Masoumi

Articles in Press, Accepted Manuscript, Available Online from 10 March 2020

Abstract
  Biogeography-Based Optimization (BBO) algorithm has recently been of great interest to researchers for simplicity of implementation, efficiency, and the low number of parameters. The BBO Algorithm in optimization problems is one of the new algorithms which have been developed based on the biogeography ...  Read More

4. Shuffled Frog-Leaping Programming for Solving Regression Problems

M. Abdollahi; M. Aliyari Shoorehdeli

Articles in Press, Accepted Manuscript, Available Online from 10 March 2020

Abstract
  There are various automatic programming models inspired by evolutionary computation techniques. Due to the importance of devising an automatic mechanism to explore the complicated search space of mathematical problems where numerical methods fails, evolutionary computations are widely studied and applied ...  Read More

5. Development of a Unique Biometric-based Cryptographic Key Generation with Repeatability using Brain Signals

M. Zeynali; H. Seyedarabi; B. Mozaffari Tazehkand

Articles in Press, Accepted Manuscript, Available Online from 04 April 2020

Abstract
  Network security is very important when sending confidential data through the network. Cryptography is the science of hiding information, and a combination of cryptography solutions with cognitive science starts a new branch called cognitive cryptography that guarantee the confidentiality and integrity ...  Read More

6. Vehicle Type Recognition based on Dimension Estimation and Bag of Word Classification

R. Asgarian Dehkordi; H. Khosravi

Articles in Press, Accepted Manuscript, Available Online from 04 April 2020

Abstract
  Fine-grained vehicle type recognition is one of the main challenges in machine vision. Almost all of the ways presented so far have identified the type of vehicle with the help of feature extraction and classifiers. Because of the apparent similarity between car classes, these methods may produce erroneous ...  Read More

7. Development of an Ensemble Multi-stage Machine for Prediction of Breast Cancer Survivability

J. Razmara; M. Salehi; Sh. Lotfi

Articles in Press, Accepted Manuscript, Available Online from 30 May 2020

Abstract
  Prediction of cancer survivability using machine learning techniques has become a popular approach in recent years. ‎In this regard, an important issue is that preparation of some features may need conducting difficult and costly experiments while these features have less significant impacts on the ...  Read More

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