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Applied Sciences
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Fuzzy Logic and Fuzzy Hybrid Techniques for Construction Engineering
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Fuzzy Logic and Fuzzy Hybrid Techniques for Construction Engineering

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: closed (10 February 2023) | Viewed by 7677

Special Issue Editor

Prof. Dr. Edyta Plebankiewicz

E-Mail Website
Guest Editor
Department of Construction Management, Cracow University of Technology, Warszawska 24 Street, 31-155 Cracow, Poland
Interests: costs in construction; construction investment process; fuzzy sets in civil engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

It is my pleasure to announce the opening of a new Special Issue in the Applied Science Journal.

The main topics of this Special Issue will be those associated with approaches for fuzzy logic and fuzzy hybrid techniques to aid in solving construction engineering problems.

The field of construction is very dynamic, with many interacting factors that influence construction processes and decisions. With an increase in the complexity of construction, the expression of various kinds of information is associated with significant risk, uncertainty, and a lack of precision. There are numerous uncontrollable factors involved in decision-making processes, such as human factors and approaches to making judgements. As a result of this, the development of deterministic mathematical models for solving various problems within the area of civil engineering represents a difficult task. The use of fuzzy logic provides advantages over classic techniques. Fuzzy logic is commonly used, for instance, in construction management, for the following tasks: construction contractor’s prequalification, supplier/subcontractor selection, construction project risk assessment, and many others. Fuzzy systems have many applications in decision making, in design, control, and management. Dam control and water quality control are typical examples of fuzzy system applications in hydrology and water resource engineering. The successful use of fuzzy logic has been showcased  in geotechnical engineering, transportation engineering, and many other sectors. Fuzzy sets are usually accompanied by other computational intelligence technologies, especially neurocomputing. Neural networks and fuzzy sets are highly complementary. Combining fuzzy mathematics with other techniques, such as heuristic algorithms or meta-heuristic algorithms, the Monte Carlo simulation, the analytic hierarchy process (AHP), and computer applications, can better simplify complex ideas, reduce human subjectivity, increase calculation speed, and achieve a combination of qualitative and quantitative research.

Some of the topics proposed for this Special Issue are as follows (but not limited to):

  • Fuzzy Logic-based Decision Making in Construction Engineering;
  • Fuzzy Data Mining Approaches in Construction Engineering;
  • Fuzzy Simulation Techniques in Construction Engineering;
  • Fuzzy Analytic Hierarchy Process in Construction Engineering;
  • Type-2 fuzzy sets in Construction Engineering;
  • Adaptive Neuro-fuzzy Inference System in Construction Engineering;
  • Fuzzy Cognitive Maps in Construction Engineering;
  • Fuzzy Systems with Big Data and Cloud Computing, Fuzzy Analytics and Visualization.

We hope that you will contribute your high-quality research to this Special Issue, and we look forward to reading your valuable results.

Prof. Dr. Edyta Plebankiewicz
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • construction engineering
  • fuzzy logic
  • fuzzy systems
  • fuzzy simulation techniques

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Published Papers (3 papers)

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Research

23 pages, 1614 KiB  
Article
Construction Material Selection by Using Multi-Attribute Decision Making Based on q-Rung Orthopair Fuzzy Aczel–Alsina Aggregation Operators
by Muhammad Rizwan Khan, Haolun Wang, Kifayat Ullah and Hanen Karamti
Appl. Sci. 2022, 12(17), 8537; https://doi.org/10.3390/app12178537 - 26 Aug 2022
Cited by 25 | Viewed by 1873
Abstract
A contribution of this article is to introduce new q-rung Orthopair fuzzy (q-ROF) aggregation operators (AOs) as the consequence of Aczel–Alsina (AA) t-norm (TN) (AATN) and t-conorm (TCN) (AATCN) and their specific advantages in handling real-world problems. In the beginning, we introduce a [...] Read more.
A contribution of this article is to introduce new q-rung Orthopair fuzzy (q-ROF) aggregation operators (AOs) as the consequence of Aczel–Alsina (AA) t-norm (TN) (AATN) and t-conorm (TCN) (AATCN) and their specific advantages in handling real-world problems. In the beginning, we introduce a few new q-ROF numbers (q-ROFNs) operations, including sum, product, scalar product, and power operations based on AATN and AATCN. At that point, we construct a few q-ROF AOs such as q-ROF Aczel–Alsina weighted averaging (q-ROFAAWA) and q-ROF Aczel–Alsina weighted geometric (q-ROFAAWG) operators. It is illustrated that suggested AOs have the features of monotonicity, boundedness, idempotency, and commutativity. Then, to address multi-attribute decision-making (MADM) challenges, we develop new strategies based on these operators. To demonstrate the compatibility and performance of our suggested approach, we offer an example of construction material selection. The outcome demonstrates the new technique’s applicability and viability. Finally, we comprehensively compare current procedures with the proposed approach. Full article
(This article belongs to the Special Issue Fuzzy Logic and Fuzzy Hybrid Techniques for Construction Engineering)
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20 pages, 2033 KiB  
Article
Analyzing and Controlling Construction Engineering Project Gray Rhino Risks with Innovative MCDM Methods: Interference Fuzzy Analytical Network Process and Decision-Making Trial and Evaluation Laboratory
by Jeen Guo, Pengcheng Xiang and Yuanli Lee
Appl. Sci. 2022, 12(11), 5693; https://doi.org/10.3390/app12115693 - 3 Jun 2022
Cited by 9 | Viewed by 2266
Abstract
Construction engineering projects are costly and require large amounts of labor, physical, and financial resources. The failure of a construction engineering project typically brings huge losses. Previous studies have focused on the identification of risks, but insufficient attention has been given to strategic [...] Read more.
Construction engineering projects are costly and require large amounts of labor, physical, and financial resources. The failure of a construction engineering project typically brings huge losses. Previous studies have focused on the identification of risks, but insufficient attention has been given to strategic resource allocation for risk management after risk identification. Statistics show that most construction engineering project failures are caused by common risks. Common risks are called gray rhino risks. This metaphor illustrates that many risks are obvious but dangerous. This study was motivated by the challenge of efficiently managing gray rhino risks with limited inputs. The literature suggests that gray rhino risks are abundant in construction engineering projects and that there are mutual eliciting relationships between them, which make it difficult for the manager to devote enough resources to the prevention of key risks. Considerable resources are wasted on unimportant risks, resulting in key risk occurrence and failure of construction engineering projects. Therefore, this study describes an innovative multi-criteria decision making (MCDM) technique for ranking risks based on the strength of the eliciting relationships between them. This study used the fuzzy technique and created an interference fuzzy analytical network process (IF-ANP) method. By employing the IF-ANP alongside a decision-making trial and evaluation laboratory (DEMATEL) approach, the subjectivity can be effectively reduced and the accuracy improved during expert risk evaluation for construction engineering projects. IF-ANP was used to quantify eliciting relationships between risks and DEMATEL was used to rank risks based on the IF-ANP result. An empirical study was done to meticulously rank five risks that were selected from the gray rhino risks in the Chengdu–Chongqing Middle Line High-speed Railway construction engineering project. They are capital chain rupture, decision failure, policy and legal risk, economic downturn, and stakeholder conflict. The results showed that the policy and legal risk was the source of other risks, and that these other risks were symptoms rather than the disease. Full article
(This article belongs to the Special Issue Fuzzy Logic and Fuzzy Hybrid Techniques for Construction Engineering)
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13 pages, 1693 KiB  
Article
Improvement of Working Conditions of Mining Workers by Reducing Nitrogen Oxide Emissions during Blasting Operations
by Marat Rudakov, Ruslan Babkin and Ekaterina Medova
Appl. Sci. 2021, 11(21), 9969; https://doi.org/10.3390/app11219969 - 25 Oct 2021
Cited by 7 | Viewed by 2508
Abstract
The article presents comparison of the values of maximum permissible concentrations, revealed during the analysis of the national standards of Russia and Australia in the field of regulation of nitrogen oxides. The impact of poisoning of the workers of the quarry with nitrogen [...] Read more.
The article presents comparison of the values of maximum permissible concentrations, revealed during the analysis of the national standards of Russia and Australia in the field of regulation of nitrogen oxides. The impact of poisoning of the workers of the quarry with nitrogen oxides after blasting operations are presented. A detailed review of studies of methods for reducing nitrogen oxide emissions is given. The way of decreasing emission of nitrogen oxides using highly active catalysts as a part of the profiled tamping is offered. Laboratory studies were carried out using a model explosive and pentaerythritol tetranitrate. The results obtained showed that zinc carbonate (ZnCO3) is the most effective. The reduction in the amount of nitrogen oxide emissions was 40% of that released during experiments without the addition of catalysts. Full article
(This article belongs to the Special Issue Fuzzy Logic and Fuzzy Hybrid Techniques for Construction Engineering)
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