Determining the weathering classification of stone cultural heritage via the analytic hierarchy process and fuzzy inference system

2020 ◽  
Vol 44 ◽  
pp. 120-134 ◽  
Author(s):  
Mehmet Ergün Hatır
Keyword(s):  
Cultural Heritage ◽  
Analytic Hierarchy Process ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Analytic Hierarchy ◽  
Inference System ◽  
The Analytic Hierarchy Process ◽  
Weathering Classification ◽  
Hierarchy Process

scholarly journals Risk Assessment and Mitigation Model for Overseas Steel-Plant Project Investment with Analytic Hierarchy Process—Fuzzy Inference System

2018 ◽  
Vol 10 (12) ◽  
pp. 4780 ◽  
Author(s):  
Min-Sung Kim ◽  
Eul-Bum Lee ◽  
In-Hye Jung ◽  
Douglas Alleman
Keyword(s):  
Risk Assessment ◽  
Analytic Hierarchy Process ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Raw Materials ◽  
Decision Makers ◽  
Analytic Hierarchy ◽  
Project Risk ◽  
Inference System ◽  
Hierarchy Process

This paper presents an analytic hierarchy process (AHP)-fuzzy inference system (FIS) model to aid decision-makers in the risk assessment and mitigation of overseas steel-plant projects. Through a thorough literature review, the authors identified 57 risks associated with international steel construction, operation, and transference of new technologies. Pairwise comparisons of all 57 risks by 14 subject-matter experts resulted in a relative weighting. Furthermore, to mitigate human subjectivity, vagueness, and uncertainty, a fuzzy analysis based on the findings of two case studies was performed. From these combined analyses, weighted individual risk soring resulted in the following top five most impactful international steel project risks: procurement of raw materials; design errors and omissions; conditions of raw materials; technology spill prevention plan; investment cost and poor plant availability and performance. Risk mitigation measures are also presented, and risk scores are re-assessed through the AHP-FIS analysis model depicting an overall project risk score reduction. The model presented is a useful tool for industry performing steel project risk assessments. It also provides decision-makers with a better understanding of the criticality of risks that are likely to occur on international steel projects.

scholarly journals Estimation of fines amount in syariah criminal offences using adaptive neuro-fuzzy inference system (ANFIS) enhanced with analytic hierarchy process (AHP)

2019 ◽  
Vol 9 (6) ◽  
pp. 5537
Author(s):  
Ahmad Fitri Mazlam ◽  
Wan Nural Jawahir Hj Wan Yussof ◽  
Rabiei Mamat
Keyword(s):  
Analytic Hierarchy Process ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Individual Decision ◽  
Criminal Cases ◽  
Analytic Hierarchy ◽  
Inference System ◽  
Neuro Fuzzy ◽  
The Individual ◽  
Hierarchy Process

<span lang="EN-US">All syariah criminal cases, especially in khalwat offence have their case-fact, and the judges typically look forward to all the facts which were tabulated by the prosecutors. A variety of criteria is considered by the judge to determine the fines amount that should be imposed on an accused who pleads guilty. In Terengganu, there were ten (10) judges, and the judgments were made by the individual decision upon the trial to decide the case. Each judge has a stake, principles and distinctive criteria in determining fines amount on an accused who pleads guilty and convicted. This research paper presents an Adaptive Neuro-fuzzy Inference System (ANFIS) technique combining with Analytic Hierarchy Process (AHP) for estimating fines amount in Syariah (khalwat) criminal. Datasets were collected under the supervision of registrar and syarie judge in the Department of Syariah Judiciary State Of Terengganu, Malaysia. The results showed that ANFIS+AHP could estimate fines efficiently than the traditional method with a very minimal error.</span>

Index of suicide risk in Mexico using Twitter

2019 ◽  
pp. 1-13
Author(s):  
Luz Judith Rodríguez-Esparza ◽  
Diana Barraza-Barraza ◽  
Jesús Salazar-Ibarra ◽  
Rafael Gerardo Vargas-Pasaye
Keyword(s):  
Social Networks ◽  
Analytic Hierarchy Process ◽  
Suicide Risk ◽  
Opinion Mining ◽  
Real Data ◽  
Analytic Hierarchy ◽  
Specialized Care ◽  
The Analytic Hierarchy Process ◽  
Hierarchy Process

Objectives: To identify early suicide risk signs on depressive subjects, so that specialized care can be provided. Various studies have focused on studying expressions on social networks, where users pour their emotions, to determine if they show signs of depression or not. However, they have neglected the quantification of the risk of committing suicide. Therefore, this article proposes a new index for identifying suicide risk in Mexico. Methodology: The proposal index is constructed through opinion mining using Twitter and the Analytic Hierarchy Process. Contribution: Using R statistical package, a study is presented considering real data, making a classification of people according to the obtained index and using information from psychologists. The proposed methodology represents an innovative prevention alternative for suicide.

scholarly journals Application of Fuzzy Analytic Hierarchy Process to Building Research Teams

2016 ◽  
Vol 21 (1) ◽  
pp. 7-11 ◽  
Author(s):  
Karol Dąbrowski ◽  
Katarzyna Skrzypek
Keyword(s):  
Analytic Hierarchy Process ◽  
Fuzzy Inference ◽  
Fuzzy Ahp ◽  
Project Teams ◽  
Analytic Hierarchy ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Working Groups ◽  
Research Facilities ◽  
Hierarchy Process

Abstract Building teams has a fundamental impact for execution of research and development projects. The teams appointed for the needs of given projects are based on individuals from both inside and outside of the organization. Knowledge is not only a product available on the market but also an intangible resource affecting their internal and external processes. Thus it is vitally important for businesses and scientific research facilities to effectively manage knowledge within project teams. The article presents a proposal to use Fuzzy AHP (Analytic Hierarchy Process ) and ANFIS (Adaptive Neuro Fuzzy Inference System) methods in working groups building for R&D projects on the basis of employees skills.

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