The application of a fuzzy inference system and analytical hierarchy process based online evaluation framework to the Donghai Bridge Health Monitoring System

2014 ◽  
Vol 14 (2) ◽  
pp. 129-144 ◽  
Author(s):  
Danhui Dan ◽  
Limin Sun ◽  
Zhifang Yang ◽  
Daqi Xie
Keyword(s):  
Health Monitoring ◽  
Analytical Hierarchy Process ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Evaluation Framework ◽  
Inference System ◽  
Health Monitoring System ◽  
Bridge Health Monitoring ◽  
Online Evaluation ◽  
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.

An integrated fuzzy inference system and AHP approach for criticality analysis of assets: A case study of a gas refinery

2021 ◽  
pp. 1-19
Author(s):  
Majid Mardani Shahri ◽  
Abdolhamid Eshraghniaye Jahromi ◽  
Mahmoud Houshmand
Keyword(s):  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Integrated Approach ◽  
Human Mind ◽  
Maximum Efficiency ◽  
Risk Matrix ◽  
Inference System ◽  
Criticality Analysis ◽  
Hierarchy Process ◽  
Gas Refinery

The purpose of maintenance is to ensure the maximum efficiency and availability of production assets at optimal cost considering quality, safety, and environmental aspects. Assets criticality analysis is one of the main steps in many maintenance methodologies, including Reliability Centered Maintenance. The present study seeks to provide a solution for determining critical assets for more efficient maintenance management. In this regard, an integrated approach of the analytical hierarchy process and fuzzy inference system was proposed based on the concept of the risk matrix. According to the concept of the risk matrix, two main criteria of failure consequences and probability were employed to determine assets criticality. Analytic Hierarchy Process (AHP) was used to consider all sub-criteria of failure consequences and probability. Finally, using two main criteria as inputs, a fuzzy inference system was developed to determine the criticality of the assets. The proposed approach was implemented in a gas refinery; the results showed its effectiveness and applicability in the process of prioritizing assets based on criticality criteria. The proposed approach has the advantages of multi-criteria decision-making techniques, modeling ambiguity and uncertainty in real issues, modeling the process of inference in the human mind, and storing the knowledge of the organization’s expert.

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>

scholarly journals PREDICTION OF FLASH FLOOD SUSCEPTIBILITY USING FUZZY ANALYTICAL HIERARCHY PROCESS (FAHP) ALGORITHMS AND GIS: A STUDY CASE OF GUELMIM REGION IN SOUTHWESTERN OF MOROCCO

2019 ◽  
Vol XLII-4/W19 ◽  
pp. 407-414 ◽  
Author(s):  
S. Talha ◽  
M. Maanan ◽  
H. Atika ◽  
H. Rhinane
Keyword(s):  
Analytical Hierarchy Process ◽  
Fuzzy Inference ◽  
Flash Flood ◽  
Flash Floods ◽  
Drainage Density ◽  
Fuzzy Analytical Hierarchy Process ◽  
Moisture Index ◽  
Inference System ◽  
Flood Susceptibility ◽  
Hierarchy Process

Abstract. In recent decades, many of the countries around the world as well as the south-western Morocco (Guelmim region, Assaka watershed), was subject to flood-storm causing huge human and material damages. The current study focuses on the Prediction of flash flood susceptibility using Fuzzy Analytical Hierarchy Process (FAHP) algorithms and Geographic Information System (GIS) technical. Flash floods areas were identified based on seven flash flood conditioning factors (Soil Moisture Index (SMI), Drainage Density, Rainfall, LULC, Altitude, Slope and Soil). Using AHP the weight derived for the factors were SMI 37% Rainfall 24.30%, Drainage Density 15.57%, LULC 9.98% Altitude 6.39% Slope of the river basin 4.06% and Soil type 2.70%. Then, applying a fuzzy inference system to create flash flood vulnerability maps. The resulting maps were classified into three categories: low, moderate and high flash flood susceptibility; indicated that the areas at the outlet of the watershed and which are close of the main affluent wadis (Seyyad and Oum Al-Achar) were very susceptible to flooding. This study will be helping these zones to be prioritized for the conservation and managing of flash floods.

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