Quarterly Publication

Big Data and Computing Visions (BDCV) is an international scholarly open access, interdisciplinary, fully refereed, and quarterly free of charge journal as a non-commercial publication. The publication start year of BDCV is 2021. All submitted manuscripts are checked for similarity through a trustworthy software named iThenticate to be assured about its originality and rigorously peer-reviewed by the international reviewers (The similarity rate must be below 20%).

BDCV is a peer-reviewed journal publishes original research papers, reviews, case studies, short communication and innovative research studies, covering all aspects on theoretical and applied papers of Big Data  and Computing Visions concepts such as “data analysis”, “data mining”, “information systems”, “pattern recognition”, “soft computing”, ”computer vision”, ”image and video processing”, “distributed systems”, “Intelligent Systems”, “Bioinformatics”,” performance evaluation”,” data envelopment analysis”, “mathematical modeling”,” financial analysis”, etc. This journal respects the ethical rules in publishing and is subject to the rules of the Ethics Committee" for Publication (COPE) and committed to follow the executive regulations of the Law on Prevention and Combating Fraud in Scientific  Works. This journal publishes fully open access journals, which means that all articles are available on the internet to all users immediately upon publication.

Access to articles from this journal is free.

 

Original Article
Advancing risk assessment in renewable power plant construction: an integrated DEA-SVM approach

Reza Rasinojehdehi; Seyyed Esmaeil Najafi

Volume 4, Issue 1 , March 2024, Pages 1-11

https://doi.org/10.22105/bdcv.2024.447876.1178

Abstract
  An indispensable aspect of human life is energy. The escalating global population and the subsequent rise in the human need for energy, coupled with the constraints of fossil fuels, have compelled researchers to explore innovative techniques for energy production and the adoption of renewable energy ...  Read More

Environmental risk assessment using FMEA and entropy based on TOPSIS method: a case study oil wells drilling

Negar Afzali Behbahani; Mazdak Khodadadi-Karimvand; Afarin Ahmadi

Volume 2, Issue 1 , March 2022, , Pages 31-39

https://doi.org/10.22105/bdcv.2022.331778.1054

Abstract
  Drilling is among the major processes of exploration, description, and development of oil and gas reservoirs with a strategic significance in the oil industry. It has also always been a major challenge in the oil industry. Because of the importance of drilling in major upstream oil and gas industries, ...  Read More

Using machine learning-based models for personality recognition

Fatemeh Mohades Deilami; Hossein Sadr; Mozhdeh Nazari

Volume 1, Issue 3 , September 2021, , Pages 128-139

https://doi.org/10.22105/bdcv.2021.142588

Abstract
  Personality can be defined as the combination of behavior, emotion, motivation, and thoughts that aim at describing various aspects of human behavior based on a few stable and measurable characteristics. Considering the fact that our personality has a remarkable influence in our daily life, automatic ...  Read More

Toward prediction of entrepreneurial exit in Iran; a study based on GEM 2008-2019 data and approach of machine learning algorithms

Masoumeh Moterased; Seyed Mojtaba Sajadi; Ali Davari; Mohammad Reza Zali

Volume 1, Issue 3 , September 2021, , Pages 111-127

https://doi.org/10.22105/bdcv.2021.142089

Abstract
  This study discusses the prediction model of Entrepreneurial Exit from Entrepreneurial Perceptions, acquired the data from the Global Entrepreneurship Monitor's (GEM) database in 2008-2019. Some essential indicators include Opportunity Perception, Fear of Failure, Capability Perception, Role Model, and ...  Read More

Smart bus ticketing system through IoT enabled technology

Agyan Kumar; Antônio Clécio Fontelles Thomaz

Volume 2, Issue 1 , March 2022, , Pages 1-8

https://doi.org/10.22105/bdcv.2022.326976.1046

Abstract
  This project is concerned with using a digital rather than a manual approach to providing bus passes. The major goal of this technology is to digitally manufacture bus passes and eliminate the need for handwritten paperwork. Commuters will be able to acquire their passes in a fraction of a second, eliminating ...  Read More

Estimating cash in bank branches by time series and neural network approaches

Pejman Peykani; Farzad Eshghi; Alireza Jandaghian; Hamed Farrokhi-Asl; Farid Tondnevis

Volume 1, Issue 4 , December 2021, , Pages 170-178

https://doi.org/10.22105/bdcv.2021.142232

Abstract
  Providing efficient and powerful approach for liquidity management of bank branches has always been one of the most important and challenging issues for researchers and scholars in the banking field. In other words, estimating the amount of required cash in different branches of the bank is one of the ...  Read More