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

19

Article View

325,964

PDF Download

360,340

View Per Article

1293.51

PDF Download Per Article

1429.92

Reject Rate %

61

Acceptance Rate %

23

Number of Reviewers

3144

First Decision

(Approximately)

47(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).

1. Chaotic-based Particle Swarm Optimization with Inertia Weight for Optimization Tasks

N. Mobaraki; R. Boostani; M. Sabeti

Volume 8, Issue 3 , Summer 2020, Pages 303-312

http://dx.doi.org/10.22044/jadm.2020.8594.1993

Abstract
  Among variety of meta-heuristic population-based search algorithms, particle swarm optimization (PSO) with adaptive inertia weight (AIW) has been considered as a versatile optimization tool, which incorporates the experience of the whole swarm into the movement of particles. Although the exploitation ...  Read More

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

A. Salehi; B. Masoumi

Volume 8, Issue 3 , Summer 2020, Pages 313-329

http://dx.doi.org/10.22044/jadm.2020.7835.1922

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

3. Shuffled Frog-Leaping Programming for Solving Regression Problems

M. Abdollahi; M. Aliyari Shoorehdeli

Volume 8, Issue 3 , Summer 2020, Pages 331-341

http://dx.doi.org/10.22044/jadm.2020.7847.1924

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

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

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

Volume 8, Issue 3 , Summer 2020, Pages 343-356

http://dx.doi.org/10.22044/jadm.2020.7858.1923

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

5. VHR Semantic Labeling by Random Forest Classification and Fusion of Spectral and Spatial Features on Google Earth Engine

M. Kakooei; Y. Baleghi

Volume 8, Issue 3 , Summer 2020, Pages 357-370

http://dx.doi.org/10.22044/jadm.2020.8252.1964

Abstract
  Semantic labeling is an active field in remote sensing applications. Although handling high detailed objects in Very High Resolution (VHR) optical image and VHR Digital Surface Model (DSM) is a challenging task, it can improve the accuracy of semantic labeling methods. In this paper, a semantic labeling ...  Read More

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

M. Salehi; J. Razmara; Sh. Lotfi

Volume 8, Issue 3 , Summer 2020, Pages 371-378

http://dx.doi.org/10.22044/jadm.2020.8406.1978

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

7. Improving Accuracy of Recommender Systems using Social Network Information and Longitudinal Data

B. Hassanpour; N. Abdolvand; S. Rajaee Harandi

Volume 8, Issue 3 , Summer 2020, Pages 379-389

http://dx.doi.org/10.22044/jadm.2020.7326.1871

Abstract
  The rapid development of technology, the Internet, and the development of electronic commerce have led to the emergence of recommender systems. These systems will assist the users in finding and selecting their desired items. The accuracy of the advice in recommender systems is one of the main challenges ...  Read More

8. High-Dimensional Unsupervised Active Learning Method

V. Ghasemi; M. Javadian; S. Bagheri Shouraki

Volume 8, Issue 3 , Summer 2020, Pages 391-407

http://dx.doi.org/10.22044/jadm.2020.7826.1941

Abstract
  In this work, a hierarchical ensemble of projected clustering algorithm for high-dimensional data is proposed. The basic concept of the algorithm is based on the active learning method (ALM) which is a fuzzy learning scheme, inspired by some behavioral features of human brain functionality. High-dimensional ...  Read More

9. A Routing-Aware Simulated Annealing-based Placement Method in Wireless Network on Chips

A.R. Tajary; E. Tahanian

Volume 8, Issue 3 , Summer 2020, Pages 409-415

http://dx.doi.org/10.22044/jadm.2020.8964.2034

Abstract
  Wireless network on chip (WiNoC) is one of the promising on-chip interconnection networks for on-chip system architectures. In addition to wired links, these architectures also use wireless links. Using these wireless links makes packets reach destination nodes faster and with less power consumption. ...  Read More

10. Identification of Multiple Input-multiple Output Non-linear System Cement Rotary Kiln using Stochastic Gradient-based Rough-neural Network

Gh. Ahmadi; M. Teshnelab

Volume 8, Issue 3 , Summer 2020, Pages 417-425

http://dx.doi.org/10.22044/jadm.2020.8865.2021

Abstract
  Because of the existing interactions among the variables of a multiple input-multiple output (MIMO) nonlinear system, its identification is a difficult task, particularly in the presence of uncertainties. Cement rotary kiln (CRK) is a MIMO nonlinear system in the cement factory with a complicated mechanism ...  Read More

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

R. Asgarian Dehkordi; H. Khosravi

Volume 8, Issue 3 , Summer 2020, Pages 427-438

http://dx.doi.org/10.22044/jadm.2020.8375.1975

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

H.4.7. Methodology and Techniques
12. Coordinate Exhaustive Search Hybridization Enhancing Evolutionary Optimization Algorithms

Osman K. Erol; I. Eksin; A. Akdemir; A. Aydınoglu

Volume 8, Issue 3 , Summer 2020, Pages 439-449

http://dx.doi.org/10.22044/jadm.2019.7351.1875

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

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

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

F. Sabahi

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

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

2. 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

3. Modeling Length of Hydraulic Jump on Sloping Rough Bed using Gene Expression Programming

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

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

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

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

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

Articles in Press, Accepted Manuscript, Available Online from 23 June 2020

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

5. Optimizing Membership Functions using Learning Automata for Fuzzy Association Rule Mining

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

Articles in Press, Accepted Manuscript, Available Online from 27 June 2020

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

6. A Monte Carlo-Based Search Strategy for Dimensionality Reduction in Performance Tuning Parameters

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

Articles in Press, Accepted Manuscript, Available Online from 05 July 2020

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

7. A Fuzzy C-means Algorithm for Clustering Fuzzy Data and Its Application in Clustering Incomplete Data

J. Tayyebi; E. Hosseinzadeh

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

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

8. 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

Articles in Press, Accepted Manuscript, Available Online from 21 July 2020

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

9. A Combinatorial Algorithm for Fuzzy Parameter Estimation with Application to Uncertain Measurements

M. Danesh; S. Danesh

Articles in Press, Accepted Manuscript, Available Online from 21 July 2020

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

10. A Deep Model for Super-resolution Enhancement from a Single Image

N. Majidi; K. Kiani; R. Rastgoo

Articles in Press, Accepted Manuscript, Available Online from 06 September 2020

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

11. 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

12. 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

13. 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

14. A Recommendation System for Finding Experts in Online Scientific Communities

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

Articles in Press, Accepted Manuscript, Available Online from 19 September 2020

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

15. Joint Burst Denoising and Demosaicking via Regularization and an Efficient Alignment

R. Azizi; A. M. Latif

Articles in Press, Accepted Manuscript, Available Online from 21 September 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

16. Multi-View Face Detection in Open Environments using Gabor Features and Neural Networks

R. Mohammadian; M. Mahlouji; A. Shahidinejad

Articles in Press, Accepted Manuscript, Available Online from 01 July 2020

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

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