Fuzzy Logic Method Design for Landslide Vulnerability

Wardhana, Made Dandy; Sofwan, Aghus; Setiawan, Iwan

doi:10.1051/e3sconf/201912503004

Cited by 4 publications

(3 citation statements)

References 10 publications

(10 reference statements)

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“…A study on the landslide vulnerability level decision support system was carried out in 2019 under the title "Fuzzy Logic Method Design for Landslide Vulnerability" [15]. As a decision support tool, we employed the Mamdani fuzzy logic method in this work.…”

Section: Literature Reviewmentioning

confidence: 99%

Adaptive Neuro-Fuzzy Inference System (ANFIS) Method for Developing a Decision Support System for Determining Landslide Susceptibility

et al. 2023

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Landslide catastrophes are one of the disasters that frequently occur in Indonesia owing to the weather and climatic features, regional terrain, and geological formations that make this nation prone to landslides. The primary goal of this research is to compare the application of the fuzzy logic technique and the adaptive neuro-fuzzy inference system (ANFIS) approach to landslide detection sensors based on prior research in order to identify landslide-prone locations more easily. The Adaptive Neuro-Fuzzy Inference System (ANFIS) technique analyzes the landslide area using three factors. Rainfall, land slope, and soil moisture are examples of these factors. This variable is used to assess the area's level of vulnerability to landslides: very safe, relatively safe, relatively potential, potential, and very potential. In the study, each piece of data is subjected to a training and testing procedure to identify landslide vulnerability, with the factors and weighting methods aligned with current government standards. This study compares the rules outcomes to those of past studies as well as the system results. Based on the studies findings, it can be stated that the decision support system for the degree of landslide vulnerability utilizing the ANFIS approach is superior to the fuzzy logic method, with an accuracy rate of 86.21%.

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Section: Literature Reviewmentioning

confidence: 99%

Adaptive Neuro-Fuzzy Inference System (ANFIS) Method for Developing a Decision Support System for Determining Landslide Susceptibility

et al. 2023

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“…The originator of the idea of fuzzy logic is Prof. Dr. Lotfi Zadeh from the University of California, Berkeley in 1965. In principle, the fuzzy set is the expansion of the crisp set, which is a set that divides a group of individuals into two categories, namely members and non-members [4], [8], [23], [26], [28].…”

Section: Introductionmentioning

confidence: 99%

Implementation of fuzzy logic method for automation of decision making of Boeing aircraft landing

Pratiwi

Sofwan

Setiawan

2021

IJ-AI

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In the landing process, airplanes have many safety factors that must be protected. Weather advice and information is very important as a consideration in determining the feasibility of landing an aircraft. The main objective of this research is the implementation of Mamdani fuzzy simulation in determining the feasibility of landing aircraft at Ahmad Yani Airport in Semarang using ATC police and pilot coordination on runway number 31. Wind direction, wind velocity, visibility, and pilot experience are used to determine eligibility aircraft landing. An intelligent system based on fuzzy logic produces three decisions that are feasible, careful, and not feasible in landing an aircraft on a runway. The results of the study concluded from an intelligent system based on fuzzy logic can be used to determine aircraft landing decisions on the runway of Ahmad Yani Airport Semarang on runway number 31.

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“…Answering the needs of particular applications: the modification of methods and models to fit particular geographic areas and study needs (e.g., by introducing new parameters and models for their evaluation) [1,[10][11][12][13][18][19][20][21]; • Improving existing methods: the development of more complex and sophisticated methods using Fuzzy Logic, Analytical Hierarchy Processes, and similar models [14][15][16][17][22][23][24][25][26][27][28][29][30][31][32][33][34]; • Supporting coastal management: including more socio-economic issues, decision making processes, or public awareness [33,35,36].…”

Section: Introductionmentioning

confidence: 99%

Household Level Vulnerability Analysis—Index and Fuzzy Based Methods

Baučić

2020

IJGI

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Coastal vulnerability assessment due to climate change impacts, particularly for sea level rise, has become an essential part of coastal management all over the world. For the planning and implementation of adaptation measures at the household level, large-scale analysis is necessary. The main aim of this research is to investigate and propose a simple and viable assessment method that includes three key geospatial parameters: elevation, distance to coastline, and building footprint area. Two methods are proposed—one based on the Index method and another on fuzzy logic. While the former method standardizes the quantitative parameters to unit-less vulnerability sub-indices using functions (avoiding crisp classification) and summarizes them, the latter method turns quantitative parameters into linguistic variables and further implements fuzzy logic. For comparison purposes, a third method is considered: the existing Index method using crisp values for vulnerability sub-indices. All three methods were implemented, and the results show significant differences in their vulnerability assessments. A discussion on the advantages and disadvantages led to the following conclusion: although the fuzzy logic method satisfies almost all the requirements, a less complex method based on functions can be applied and still yields significant improvement.

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Fuzzy Logic Method Design for Landslide Vulnerability

Cited by 4 publications

References 10 publications

Adaptive Neuro-Fuzzy Inference System (ANFIS) Method for Developing a Decision Support System for Determining Landslide Susceptibility

Adaptive Neuro-Fuzzy Inference System (ANFIS) Method for Developing a Decision Support System for Determining Landslide Susceptibility

Implementation of fuzzy logic method for automation of decision making of Boeing aircraft landing

Household Level Vulnerability Analysis—Index and Fuzzy Based Methods

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