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

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

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

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

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

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

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

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

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

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

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

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

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