Original/Review Paper
A Bi-objective Virtual-force Local Search PSO Algorithm for Improving Sensing Deployment in Wireless Sensor Network

Vahid Kiani; Mahdi Imanparast

Volume 11, Issue 1 , January 2023, Pages 1-12


  In this paper, we present a bi-objective virtual-force local search particle swarm optimization (BVFPSO) algorithm to improve the placement of sensors in wireless sensor networks while it simultaneously increases the coverage rate and preserves the battery energy of the sensors. Mostly, sensor nodes ...  Read More

Original/Review Paper
An Efficient XCS-based Algorithm for Learning Classifier Systems in Real Environments

Ali Yousefi; Kambiz Badie; Mohammad Mehdi Ebadzadeh; Arash Sharifi

Volume 11, Issue 1 , January 2023, Pages 13-27


  Recently, learning classifier systems are used to control physical robots, sensory robots, and intelligent rescue systems. The most important challenge in these systems, which are models of real environments, is its non-markov quality. Therefore, it is necessary to use memory to store system states in ...  Read More

Original/Review Paper
Efficient Feature Selection Method using Binary Teaching-learning-based Optimization Algorithm

S. Hosseini; M. Khorashadizade

Volume 11, Issue 1 , January 2023, Pages 29-37


  High dimensionality is the biggest problem when working with large datasets. Feature selection is a procedure for reducing the dimensionality of datasets by removing additional and irrelevant features; the most effective features in the dataset will remain, increasing the algorithms’ performance. ...  Read More

Original/Review Paper
FEEM: A Flexible Model based on Artificial Intelligence for Software Effort Estimation

Amin Moradbeiky

Volume 11, Issue 1 , January 2023, Pages 39-51


  Managing software projects due to its intangible nature is full of challenges when predicting the effort needed for development. Accordingly, there exist many studies with the attempt to devise models to estimate efforts necessary in developing software. According to the literature, the accuracy of estimator ...  Read More

Technical Paper
Adaptive Pruning of Convolutional Neural Network

S. Ahmadluei; K. Faez; B. Masoumi

Volume 11, Issue 1 , January 2023, Pages 53-67


  Deep convolutional neural networks (CNNs) have attained remarkable success in numerous visual recognition tasks. There are two challenges when adopting CNNs in real-world applications: a) Existing CNNs are computationally expensive and memory intensive, impeding their use in edge computing; b) there ...  Read More

Original/Review Paper
Efficient Stance Ordering to Improve Rumor Veracity Detection

Z. MohammadHosseini; A. Jalaly Bidgoly

Volume 11, Issue 1 , January 2023, Pages 69-76


  Social media is an inseparable part of human life, although published information through social media is not always true. Rumors may spread easily and quickly in the social media, hence, it is vital to have a tool for rumor veracity detection. Papers already proved that users’ stance is an important ...  Read More

Original/Review Paper
Learning a Nonlinear Combination of Generalized Heterogeneous Classifiers

M. Rahimi; A. A. Taheri; H. Mashayekhi

Volume 11, Issue 1 , January 2023, Pages 77-93


  Finding an effective way to combine the base learners is an essential part of constructing a heterogeneous ensemble of classifiers. In this paper, we propose a framework for heterogeneous ensembles, which investigates using an artificial neural network to learn a nonlinear combination of the base classifiers. ...  Read More

Original/Review Paper
Automatic Post-editing of Hierarchical Attention Networks for Improved Context-aware Neural Machine Translation

M. M. Jaziriyan; F. Ghaderi

Volume 11, Issue 1 , January 2023, Pages 95-102


  Most of the existing neural machine translation (NMT) methods translate sentences without considering the context. It is shown that exploiting inter and intra-sentential context can improve the NMT models and yield to better overall translation quality. However, providing document-level data is costly, ...  Read More

Original/Review Paper H.3. Artificial Intelligence
A Reinforcement Learning-based Encoder-Decoder Framework for Learning Stock Trading Rules

M. Taghian; A. Asadi; R. Safabakhsh

Volume 11, Issue 1 , January 2023, Pages 103-118


  The quality of the extracted features from a long-term sequence of raw prices of the instruments greatly affects the performance of the trading rules learned by machine learning models. Employing a neural encoder-decoder structure to extract informative features from complex input time-series has proved ...  Read More

Original/Review Paper
A Comparison of CQT Spectrogram with STFT-based Acoustic Features in Deep Learning-based Synthetic Speech Detection

P. Abdzadeh; H. Veisi

Volume 11, Issue 1 , January 2023, Pages 119-129


  Automatic Speaker Verification (ASV) systems have proven to bevulnerable to various types of presentation attacks, among whichLogical Access attacks are manufactured using voiceconversion and text-to-speech methods. In recent years, there has beenloads of work concentrating on synthetic speech detection, ...  Read More

Original/Review Paper
Investigating Revenue Smoothing Thresholds That Affect Bank Credit Scoring Models: An Iranian Bank Case Study

Seyed Mahdi Sadatrasoul; Omid Mahdi Ebadati; Amir Amirzadeh Irani

Volume 11, Issue 1 , January 2023, Pages 131-148


  Companies have different considerations for using smoothing in their financial statements, including annual general meeting, auditing, Regulatory and Supervisory institutions and shareholders requirements. Smoothing is done based on the various possible and feasible choices in identifying company’s ...  Read More

Original/Review Paper
A New Adaptive Approach for Efficient Energy Consumption in Edge Computing

H. Morshedlou; A.R. Tajari

Volume 11, Issue 1 , January 2023, Pages 149-159


  Edge computing is an evolving approach for the growing computing and networking demands from end devices and smart things. Edge computing lets the computation to be offloaded from the cloud data centers to the network edge for lower latency, security, and privacy preservation. Although energy efficiency ...  Read More