H.3. Artificial Intelligence
1. 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

http://dx.doi.org/10.22044/jadm.2019.7903.1929

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

H.3. Artificial Intelligence
2. QoS-based Web Service Recommendation using Popular-dependent Collaborative Filtering

S. Adeli; P. Moradi

Volume 8, Issue 1 , Winter 2020, , Pages 83-93

http://dx.doi.org/10.22044/jadm.2019.7461.1888

Abstract
  Since, most of the organizations present their services electronically, the number of functionally-equivalent web services is increasing as well as the number of users that employ those web services. Consequently, plenty of information is generated by the users and the web services that lead to the users ...  Read More

H.3. Artificial Intelligence
3. Controller Placement in Software Defined Network using Iterated Local Search

A. Moradi; A. Abdi Seyedkolaei; Seyed A. Hosseini

Volume 8, Issue 1 , Winter 2020, , Pages 55-65

http://dx.doi.org/10.22044/jadm.2019.7934.1931

Abstract
  Software defined network is a new computer network architecture who separates controller and data layer in network devices such as switches and routers. By the emerge of software defined networks, a class of location problems, called controller placement problem, has attracted much more research attention. ...  Read More

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

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

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

http://dx.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.3. Artificial Intelligence
5. Forecasting Gold Price using Data Mining Techniques by Considering New Factors

A.R. Hatamlou; M. Deljavan

Volume 7, Issue 3 , Summer 2019, , Pages 411-420

http://dx.doi.org/10.22044/jadm.2018.6114.1727

Abstract
  Gold price forecast is of great importance. Many models were presented by researchers to forecast gold price. It seems that although different models could forecast gold price under different conditions, the new factors affecting gold price forecast have a significant importance and effect on the increase ...  Read More

H.3. Artificial Intelligence
6. MEFUASN: A Helpful Method to Extract Features using Analyzing Social Network for Fraud Detection

Z. Karimi Zandian; M. R. Keyvanpour

Volume 7, Issue 2 , Spring 2019, , Pages 213-224

http://dx.doi.org/10.22044/jadm.2018.6311.1746

Abstract
  Fraud detection is one of the ways to cope with damages associated with fraudulent activities that have become common due to the rapid development of the Internet and electronic business. There is a need to propose methods to detect fraud accurately and fast. To achieve to accuracy, fraud detection methods ...  Read More

H.3. Artificial Intelligence
7. An Efficient Optimal Fractional Emotional Intelligent Controller for an AVR System in Power Systems

M. Moradi Zirkohi

Volume 7, Issue 1 , Winter 2019, , Pages 193-202

http://dx.doi.org/10.22044/jadm.2018.6797.1798

Abstract
  In this paper, a high-performance optimal fractional emotional intelligent controller for an Automatic Voltage Regulator (AVR) in power system using Cuckoo optimization algorithm (COA) is proposed. AVR is the main controller within the excitation system that preserves the terminal voltage of a synchronous ...  Read More

H.3. Artificial Intelligence
8. A New Routing Algorithm for Vehicular Ad-hoc Networks based on Glowworm Swarm Optimization Algorithm

R. Yarinezhad; A. Sarabi

Volume 7, Issue 1 , Winter 2019, , Pages 69-76

http://dx.doi.org/10.22044/jadm.2018.6516.1765

Abstract
  Vehicular ad hoc networks (VANETs) are a particular type of Mobile ad hoc networks (MANET) in which the vehicles are considered as nodes. Due to rapid topology changing and frequent disconnection makes it difficult to design an efficient routing protocol for routing data among vehicles. In this paper, ...  Read More

H.3. Artificial Intelligence
9. A New Knowledge-Based System for Diagnosis of Breast Cancer by a combination of the Affinity Propagation and Firefly Algorithms

N. Emami; A. Pakzad

Volume 7, Issue 1 , Winter 2019, , Pages 59-68

http://dx.doi.org/10.22044/jadm.2018.6489.1763

Abstract
  Breast cancer has become a widespread disease around the world in young women. Expert systems, developed by data mining techniques, are valuable tools in diagnosis of breast cancer and can help physicians for decision making process. This paper presents a new hybrid data mining approach to classify two ...  Read More

H.3. Artificial Intelligence
10. Extracting Prior Knowledge from Data Distribution to Migrate from Blind to Semi-Supervised Clustering

Z. Sedighi; R. Boostani

Volume 6, Issue 2 , Summer 2018, , Pages 287-295

http://dx.doi.org/10.22044/jadm.2017.5064.1611

Abstract
  Although many studies have been conducted to improve the clustering efficiency, most of the state-of-art schemes suffer from the lack of robustness and stability. This paper is aimed at proposing an efficient approach to elicit prior knowledge in terms of must-link and cannot-link from the estimated ...  Read More

H.3. Artificial Intelligence
11. BQIABC: A new Quantum-Inspired Artificial Bee Colony Algorithm for Binary Optimization Problems

F. Barani; H. Nezamabadi-pour

Volume 6, Issue 1 , Winter 2018, , Pages 133-143

http://dx.doi.org/10.22044/jadm.2017.899

Abstract
  Artificial bee colony (ABC) algorithm is a swarm intelligence optimization algorithm inspired by the intelligent behavior of honey bees when searching for food sources. The various versions of the ABC algorithm have been widely used to solve continuous and discrete optimization problems in different ...  Read More

H.3. Artificial Intelligence
12. FDiBC: A Novel Fraud Detection Method in Bank Club based on Sliding Time and Scores Window

Seyed M. H. Hasheminejad; Z. Salimi

Volume 6, Issue 1 , Winter 2018, , Pages 219-231

http://dx.doi.org/10.22044/jadm.2017.964

Abstract
  One of the recent strategies for increasing the customer’s loyalty in banking industry is the use of customers’ club system. In this system, customers receive scores on the basis of financial and club activities they are performing, and due to the achieved points, they get credits from the ...  Read More

H.3. Artificial Intelligence
13. Composite Kernel Optimization in Semi-Supervised Metric

T. Zare; M. T. Sadeghi; H. R. Abutalebi; J. Kittler

Volume 5, Issue 2 , Summer 2017, , Pages 259-273

http://dx.doi.org/10.22044/jadm.2017.906

Abstract
  Machine-learning solutions to classification, clustering and matching problems critically depend on the adopted metric, which in the past was selected heuristically. In the last decade, it has been demonstrated that an appropriate metric can be learnt from data, resulting in superior performance as compared ...  Read More

H.3. Artificial Intelligence
14. A Sensor-Based Scheme for Activity Recognition in Smart Homes using Dempster-Shafer Theory of Evidence

V. Ghasemi; A. Pouyan; M. Sharifi

Volume 5, Issue 2 , Summer 2017, , Pages 245-258

http://dx.doi.org/10.22044/jadm.2017.845

Abstract
  This paper proposes a scheme for activity recognition in sensor based smart homes using Dempster-Shafer theory of evidence. In this work, opinion owners and their belief masses are constructed from sensors and employed in a single-layered inference architecture. The belief masses are calculated using ...  Read More

H.3. Artificial Intelligence
15. Ensemble Classification and Extended Feature Selection for Credit Card Fraud Detection

F. Fadaei Noghani; M. Moattar

Volume 5, Issue 2 , Summer 2017, , Pages 235-243

http://dx.doi.org/10.22044/jadm.2016.788

Abstract
  Due to the rise of technology, the possibility of fraud in different areas such as banking has been increased. Credit card fraud is a crucial problem in banking and its danger is over increasing. This paper proposes an advanced data mining method, considering both feature selection and decision cost ...  Read More

H.3. Artificial Intelligence
16. Prediction of rock strength parameters for an Iranian oil field using neuro-fuzzy method

M. Heidarian; H. Jalalifar; F. Rafati

Volume 4, Issue 2 , Summer 2016, , Pages 229-234

http://dx.doi.org/10.5829/idosi.JAIDM.2016.04.02.11

Abstract
  Uniaxial compressive strength (UCS) and internal friction coefficient (µ) are the most important strength parameters of rock. They could be determined either by laboratory tests or from empirical correlations. The laboratory analysis sometimes is not possible for many reasons. On the other hand, ...  Read More

H.3. Artificial Intelligence
17. An indirect adaptive neuro-fuzzy speed control of induction motors

M. Vahedi; M. Hadad Zarif; A. Akbarzadeh Kalat

Volume 4, Issue 2 , Summer 2016, , Pages 243-251

http://dx.doi.org/10.5829/idosi.JAIDM.2016.04.02.13

Abstract
  This paper presents an indirect adaptive system based on neuro-fuzzy approximators for the speed control of induction motors. The uncertainty including parametric variations, the external load disturbance and unmodeled dynamics is estimated and compensated by designing neuro-fuzzy systems. The contribution ...  Read More

H.3. Artificial Intelligence
18. Trajectory tracking of under-actuated nonlinear dynamic robots: Adaptive fuzzy hierarchical terminal sliding-mode control

Y. Vaghei; A. Farshidianfar

Volume 4, Issue 1 , Winter 2016, , Pages 93-102

http://dx.doi.org/10.5829/idosi.JAIDM.2016.04.01.11

Abstract
  In recent years, underactuated nonlinear dynamic systems trajectory tracking, such as space robots and manipulators with structural flexibility, has become a major field of interest due to the complexity and high computational load of these systems. Hierarchical sliding mode control has been investigated ...  Read More

H.3. Artificial Intelligence
19. PSO for multi-objective problems: Criteria for leader selection and uniformity distribution

H. Motameni

Volume 4, Issue 1 , Winter 2016, , Pages 67-76

http://dx.doi.org/10.5829/idosi.JAIDM.2016.04.01.08

Abstract
  This paper proposes a method to solve multi-objective problems using improved Particle Swarm Optimization. We propose leader particles which guide other particles inside the problem domain. Two techniques are suggested for selection and deletion of such particles to improve the optimal solutions. The ...  Read More