Volume 12 (2024)
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)

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 , April 2020, , Pages 279-287

https://doi.org/10.22044/jadm.2020.8248.1963

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.3.7. Learning
Distributed Incremental Least Mean-Square for Parameter Estimation using Heterogeneous Adaptive Networks in Unreliable Measurements

M. Farhid; M. Shamsi; M. H. Sedaaghi

Volume 5, Issue 2 , July 2017, , Pages 285-291

https://doi.org/10.22044/jadm.2017.888

Abstract
  Adaptive networks include a set of nodes with adaptation and learning abilities for modeling various types of self-organized and complex activities encountered in the real world. This paper presents the effect of heterogeneously distributed incremental LMS algorithm with ideal links on the quality of ...  Read More

B.3. Communication/Networking and Information Technology
Analyzing Customers of South Khorasan Telecommunication Company with Expansion of RFM to LRFM Model

V. Babaiyan; Seyyede A. Sarfarazi

Volume 7, Issue 2 , April 2019, , Pages 331-340

https://doi.org/10.22044/jadm.2018.6035.1715

Abstract
  Telecommunication Companies use data mining techniques to maintain good relationships with their existing customers and attract new customers and identifying profitable/unprofitable customers. Clustering leads to better understanding of customer and its results can be used to definition and decision-making ...  Read More

A.7. Logic Design
A Fast and Self-Repairing Genetic Programming Designer for Logic Circuits

A. M. Mousavi; M. Khodadadi

Volume 6, Issue 2 , July 2018, , Pages 355-363

https://doi.org/10.22044/jadm.2017.1059

Abstract
  Usually, important parameters in the design and implementation of combinational logic circuits are the number of gates, transistors, and the levels used in the design of the circuit. In this regard, various evolutionary paradigms with different competency have recently been introduced. However, while ...  Read More

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

R. Asgarian Dehkordi; H. Khosravi

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

https://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

Expert Discovery: A web mining approach

Muhammad Naeem; Muhammad Bilal Khan; Muhammad Tanvir Afzal

Volume 1, Issue 1 , March 2013, , Pages 35-47

https://doi.org/10.22044/jadm.2013.116

Abstract
  Expert discovery is a quest in search of finding an answer to a question: “Who is the best expert of a specific subject in a particular domain within peculiar array of parameters?” Expert with domain knowledge in any field is crucial for consulting in industry, academia and scientific community. ...  Read More

D.1. General
Dynamic characterization and predictability analysis of wind speed and wind power time series in Spain wind farm

N. Bigdeli; H. Sadegh Lafmejani

Volume 4, Issue 1 , March 2016, , Pages 103-116

https://doi.org/10.5829/idosi.JAIDM.2016.04.01.12

Abstract
  The renewable energy resources such as wind power have recently attracted more researchers’ attention. It is mainly due to the aggressive energy consumption, high pollution and cost of fossil fuels. In this era, the future fluctuations of these time series should be predicted to increase the reliability ...  Read More

A.2. Control Structures and Microprogramming
Discrete time robust control of robot manipulators in the task space using adaptive fuzzy estimator

M. M. Fateh; S. Azargoshasb

Volume 3, Issue 1 , March 2015, , Pages 113-120

https://doi.org/10.5829/idosi.JAIDM.2015.03.01.12

Abstract
  This paper presents a discrete-time robust control for electrically driven robot manipulators in the task space. A novel discrete-time model-free control law is proposed by employing an adaptive fuzzy estimator for the compensation of the uncertainty including model uncertainty, external disturbances ...  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

I.3.7. Engineering
Prediction of maximum surface settlement caused by earth pressure balance shield tunneling using random forest

V. R. Kohestani; M. R. Bazarganlari; J. Asgari marnani

Volume 5, Issue 1 , March 2017, , Pages 127-135

https://doi.org/10.22044/jadm.2016.748

Abstract
  Due to urbanization and population increase, need for metro tunnels, has been considerably increased in urban areas. Estimating the surface settlement caused by tunnel excavation is an important task especially where the tunnels are excavated in urban areas or beneath important structures. Many models ...  Read More

H.3. Artificial Intelligence
Using an Evaluator Fixed Structure Learning Automata in Sampling of Social Networks

S. Roohollahi; A. Khatibi Bardsiri; F. Keynia

Volume 8, Issue 1 , January 2020, , Pages 127-148

https://doi.org/10.22044/jadm.2019.7145.1842

Abstract
  Social networks are streaming, diverse and include a wide range of edges so that continuously evolves over time and formed by the activities among users (such as tweets, emails, etc.), where each activity among its users, adds an edge to the network graph. Despite their popularities, the dynamicity and ...  Read More

H.6.5.13. Signal processing
Improving Phoneme Sequence Recognition using Phoneme Duration Information in DNN-HSMM

M. Asadolahzade Kermanshahi; M. M. Homayounpour

Volume 7, Issue 1 , January 2019, , Pages 137-147

https://doi.org/10.22044/jadm.2018.6136.1725

Abstract
  Improving phoneme recognition has attracted the attention of many researchers due to its applications in various fields of speech processing. Recent research achievements show that using deep neural network (DNN) in speech recognition systems significantly improves the performance of these systems. There ...  Read More

H.3.11. Vision and Scene Understanding
Graph-based Visual Saliency Model using Background Color

Sh. Foolad; A. Maleki

Volume 6, Issue 1 , March 2018, , Pages 145-156

https://doi.org/10.22044/jadm.2017.911

Abstract
  Visual saliency is a cognitive psychology concept that makes some stimuli of a scene stand out relative to their neighbors and attract our attention. Computing visual saliency is a topic of recent interest. Here, we propose a graph-based method for saliency detection, which contains three stages: pre-processing, ...  Read More

F.2.7. Optimization
Estimation of parameters of metal-oxide surge arrester models using Big Bang-Big Crunch and Hybrid Big Bang-Big Crunch algorithms

M.M Abravesh; A Sheikholeslami; H. Abravesh; M. Yazdani asrami

Volume 4, Issue 2 , July 2016, , Pages 235-241

https://doi.org/10.5829/idosi.JAIDM.2016.04.02.12

Abstract
  Metal oxide surge arrester accurate modeling and its parameter identification are very important for insulation coordination studies, arrester allocation and system reliability. Since quality and reliability of lightning performance studies can be improved with the more efficient representation of the ...  Read More

H.6.4. Clustering
Improved COA with Chaotic Initialization and Intelligent Migration for Data Clustering

M. Lashkari; M. Moattar

Volume 5, Issue 2 , July 2017, , Pages 293-305

https://doi.org/10.22044/jadm.2016.783

Abstract
  A well-known clustering algorithm is K-means. This algorithm, besides advantages such as high speed and ease of employment, suffers from the problem of local optima. In order to overcome this problem, a lot of studies have been done in clustering. This paper presents a hybrid Extended Cuckoo Optimization ...  Read More

F.2.7. Optimization
Non-linear Fractional-Order Chaotic Systems Identification with Approximated Fractional-Order Derivative based on a Hybrid Particle Swarm Optimization-Genetic Algorithm Method

M. Kosari; M. Teshnehlab

Volume 6, Issue 2 , July 2018, , Pages 365-373

https://doi.org/10.22044/jadm.2017.4670.1553

Abstract
  Although many mathematicians have searched on the fractional calculus since many years ago, but its application in engineering, especially in modeling and control, does not have many antecedents. Since there are much freedom in choosing the order of differentiator and integrator in fractional calculus, ...  Read More

Data mining for decision making in engineering optimal design

Amir Mosavi

Volume 2, Issue 1 , March 2014, , Pages 7-14

https://doi.org/10.22044/jadm.2014.125

Abstract
  Often in modeling the engineering optimization design problems, the value of objective function(s) is not clearly defined in terms of design variables. Instead it is obtained by some numerical analysis such as FE structural analysis, fluid mechanic analysis, and thermodynamic analysis, etc. Yet, the ...  Read More

Protection Scheme of Power Transformer Based on Time–Frequency Analysis and KSIR-SSVM

mehdi hajian; Asghar Akbari Foroud

Volume 1, Issue 1 , March 2013, , Pages 49-61

https://doi.org/10.22044/jadm.2013.122

Abstract
  The aim of this paper is to extend a hybrid protection plan for Power Transformer (PT) based on MRA-KSIR-SSVM. This paper offers a new scheme for protection of power transformers to distinguish internal faults from inrush currents. Some significant characteristics of differential currents in the real ...  Read More

H.6.2.2. Fuzzy set
Direct adaptive fuzzy control of flexible-joint robots including actuator dynamics using particle swarm optimization

M. Moradizirkohi; S. Izadpanah

Volume 5, Issue 1 , March 2017, , Pages 137-147

https://doi.org/10.22044/jadm.2016.739

Abstract
  In this paper a novel direct adaptive fuzzy system is proposed to control flexible-joints robot including actuator dynamics. The design includes two interior loops: the inner loop controls the motor position using proposed approach while the outer loop controls the joint angle of the robot using a PID ...  Read More

H.3.2.6. Games and infotainment
Robust Opponent Modeling in Real-Time Strategy Games using Bayesian Networks

A. Torkaman; R. Safabakhsh

Volume 7, Issue 1 , January 2019, , Pages 149-159

https://doi.org/10.22044/jadm.2018.6932.1815

Abstract
  Opponent modeling is a key challenge in Real-Time Strategy (RTS) games as the environment is adversarial in these games, and the player cannot predict the future actions of her opponent. Additionally, the environment is partially observable due to the fog of war. In this paper, we propose an opponent ...  Read More

C.1. General
Intrusion Detection based on a Novel Hybrid Learning Approach

L. khalvati; M. Keshtgary; N. Rikhtegar

Volume 6, Issue 1 , March 2018, , Pages 157-162

https://doi.org/10.22044/jadm.2017.979

Abstract
  Information security and Intrusion Detection System (IDS) plays a critical role in the Internet. IDS is an essential tool for detecting different kinds of attacks in a network and maintaining data integrity, confidentiality and system availability against possible threats. In this paper, a hybrid approach ...  Read More

H.6.4. Clustering
A Multi-Objective Approach to Fuzzy Clustering using ITLBO Algorithm

P. Shahsamandi Esfahani; A. Saghaei

Volume 5, Issue 2 , July 2017, , Pages 307-317

https://doi.org/10.22044/jadm.2016.784

Abstract
  Data clustering is one of the most important areas of research in data mining and knowledge discovery. Recent research in this area has shown that the best clustering results can be achieved using multi-objective methods. In other words, assuming more than one criterion as objective functions for clustering ...  Read More

C.3. Software Engineering
Optimizing Cost Function in Imperialist Competitive Algorithm for Path Coverage Problem in Software Testing

M. A. Saadtjoo; S. M. Babamir

Volume 6, Issue 2 , July 2018, , Pages 375-385

https://doi.org/10.22044/jadm.2017.5015.1603

Abstract
  Search-based optimization methods have been used for software engineering activities such as software testing. In the field of software testing, search-based test data generation refers to application of meta-heuristic optimization methods to generate test data that cover the code space of a program. ...  Read More

Applying mean shift and motion detection approaches to hand tracking in sign language

Mohammad Mehdi Hosseini; Jalal Hassanian

Volume 2, Issue 1 , March 2014, , Pages 15-24

https://doi.org/10.22044/jadm.2014.145

Abstract
  Hand gesture recognition is very important to communicate in sign language. In this paper, an effective object tracking and hand gesture recognition method is proposed. This method is combination of two well-known approaches, the mean shift and the motion detection algorithm. The mean shift algorithm ...  Read More

H.6.2.4. Neural nets
Intelligent identification of vehicle’s dynamics based on local model network

M. Abtahi

Volume 7, Issue 1 , January 2019, , Pages 161-168

https://doi.org/10.22044/jadm.2018.5334.1642

Abstract
  This paper proposes an intelligent approach for dynamic identification of the vehicles. The proposed approach is based on the data-driven identification and uses a high-performance local model network (LMN) for estimation of the vehicle’s longitudinal velocity, lateral acceleration and yaw rate. ...  Read More