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

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

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

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

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

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

M. Kakooei; Y. Baleghi

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

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

10. 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

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

11. 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

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

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

Gh. Ahmadi; M. Teshnelab

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

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

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

N. Mobaraki; R. Boostani; M. Sabeti

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

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

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

A.R. Tajary; E. Tahanian

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

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

15. 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

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

16. High-Dimensional Unsupervised Active Learning Method

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

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

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

17. 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

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

18. 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

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