Seyed Farhad Saberhoseini; Seyyed Ahmad Edalatpanah; Ali Sorourkhah
Abstract
Public-Private Partnership (PPP) refers to a partnership between a government and a private sector to provide public infrastructure projects, services, etc. These projects have been associated with numerous problems, many of which failed. A critical issue in PPP projects is choosing the right private-sector ...
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Public-Private Partnership (PPP) refers to a partnership between a government and a private sector to provide public infrastructure projects, services, etc. These projects have been associated with numerous problems, many of which failed. A critical issue in PPP projects is choosing the right private-sector partner. Considering various criteria, the public sector has to select the best alternative concerning uncertainty. There needs to be a focus on well-structured, feasible decision approaches necessary to improve the performance of PPPs. In the MCDM context, the ratings of the alternatives provided by decision-makers can be expressed with the Fuzzy Set theory. Single-valued neutrosophic sets SVNSs are well suited for handling ambiguous, incomplete, and imprecise information. Moreover, some information measures for the SVNS model have been proposed, such as similarity measures. As selecting the suitable private-sector partner problem is an MCDM one, including various risk factors and uncertainty, this article has addressed choosing that by considering the risk factors as the problem criteria in a neutrosophic environment. We proposed a simple, practical approach to solve the problem of selecting the best private-sector partner. This approach considers the most critical risk factors affecting the infrastructure PPP project and copes with uncertainty using SVNSs.
Agyan Panda; Seyed Ahmad Edalatpanah; Ramin Godarzi Karim
Abstract
The goal is to build and create an agricultural monitoring system that uses a wireless sensor network to boost farming production and quality without having to manually monitor it all of the time. In agriculture, temperature, humidity, and carbon dioxide levels are the most critical elements affecting ...
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The goal is to build and create an agricultural monitoring system that uses a wireless sensor network to boost farming production and quality without having to manually monitor it all of the time. In agriculture, temperature, humidity, and carbon dioxide levels are the most critical elements affecting plant productivity, growth, and quality. As a result, this system measures these characteristics in the fields on a regular basis, allowing farmers or agriculture specialists to view the readings on the web at the same time. Furthermore, if a crucial change in one of the metrics occurs, an agriculture specialist will notify the farmer through mobile text message and e-mail. The farmer can study the best environmental conditions for maximum crop productivity, greater productivity, and significant energy savings by continuously monitoring several environmental data.
