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Some applications of Adaptive Neuro-Fuzzy Inference System (ANFIS) in geotechnical engineering
Computers and Geotechnics, 2012Abstract This paper presents a review of the Adaptive Neuro-Fuzzy Inference System (ANFIS) in current use for geotechnical engineering-based studies, as well as some applications employed in resonant column testing, triaxial testing, and liquefaction triggering. Over the last few years, ANFIS has been used in many geotechnical engineering problems. A
Ali Firat Cabalar +2 more
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Science of the Total Environment, 2020
Landslides are natural and sometimes quasi-natural hazards that are destructive to natural resources and cause loss of human life every year. Hence, preparing susceptibility maps for landslide monitoring is essential to minimizing their negative effects.
M. Panahi +4 more
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Landslides are natural and sometimes quasi-natural hazards that are destructive to natural resources and cause loss of human life every year. Hence, preparing susceptibility maps for landslide monitoring is essential to minimizing their negative effects.
M. Panahi +4 more
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An Implementation of the Adaptive Neuro-Fuzzy Inference System (ANFIS) for Odor Source Localization
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020In this paper, we investigate the viability of implementing machine learning (ML) algorithms to solve the odor source localization (OSL) problem. The primary objective is to obtain an ML model that guides and navigates a mobile robot to find an odor source without explicating searching algorithms.
Lingxiao Wang 0005, Shuo Pang 0001
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MI-ANFIS: A multiple instance Adaptive Neuro-Fuzzy Inference System
2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2015We introduce a novel adaptive neuro-fuzzy architecture based on the framework of Multiple Instance Fuzzy Inference. The new architecture called Multiple Instance-ANFIS (MI-ANFIS), is an extension of the standard Adaptive Neuro Fuzzy Inference System (ANFIS) [1] that is designed to handle reasoning with multiple instances (bags of instances) as input ...
Amine Ben Khalifa, Hichem Frigui
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Adaptive Neuro Fuzzy Inference System (ANFIS) based wildfire risk assessment
Journal of Experimental & Theoretical Artificial Intelligence, 2019ABSTRACTWildfires are extremely destructive disasters that cause significant loss of lives, forest cover and wildlife. This is due to their uncontrolled, erratic, rapid spread and behaviour. The incidence of wildfires is expected to increase worldwide because of Global Warming.
Harkiran Kaur, Sandeep K. Sood
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Adaptive neuro-fuzzy inference system (ANFIS) in modelling breast cancer survival
International Conference on Fuzzy Systems, 2010Medical prognosis is the prediction of the future course and outcome of a disease and an indication of the likelihood of recovery from that disease. Soft-computing approaches including artificial neural networks and fuzzy inference have been used widely to model expert behaviour.
Hazlina Hamdan, Jonathan M. Garibaldi
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Control of Trms using Adaptive Neuro Fuzzy Inference System (ANFIS)
2020 International Conference on System, Computation, Automation and Networking (ICSCAN), 2020This paper gives approach about the designing of ANFIS controller to control a TRMS to track the desired trajectory and make the system stable. The stages of development of a two input ANFIS model were presented. It shows the designing of controller is easy and it reduces the time and memory.
K. Kalyani, S. Kanagalakshmi
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Improved Performance of a PV Solar Panel with Adaptive Neuro Fuzzy Inference System ANFIS based MPPT
IEEE International Conference on Renewable Energy Research and Applications, 2018This article presents the development of an intelligent technique of Adaptive-Neuro-Fuzzy Inference System (ANFIS) based on Maximum Power Point Tracking (ANFIS-MPPT) algorithm with PI controller in order to increase the performances of the photovoltaic ...
Karima Amara +6 more
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Landslide susceptibility mapping by using an adaptive neuro-fuzzy inference system (ANFIS)
2011 IEEE International Geoscience and Remote Sensing Symposium, 2011This paper applied an adaptive neuro-fuzzy inference system (ANFIS) based on a geographic information system (GIS) environment using landslide-related factors and location for landslide susceptibility mapping. Landslide-related factors such as slope, soil texture, wood type, lithology and density of lineament were extracted from topographic, soil ...
Jaewon Choi +9 more
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