Forecasting Mortality Rate Using a Neural Network with Fuzzy Inference System [PDF]
Various methods have been developed to improve mortality forecasts. The authors proposed a neuro-fuzzy model to forecast the mortality. The forecasting of mortality is curried out by an ANFIS model which uses a first order Sugeno-type FIS.
Camelia Ioana Ucenic +4 more
core
Study of Discrete Choice Models and Adaptive Neuro-Fuzzy Inference System in the Prediction of Economic Crisis Periods in USA [PDF]
In this study two approaches are applied for the prediction of the economic recession or expansion periods in USA. The first approach includes Logit and Probit models and the second is an Adaptive Neuro-Fuzzy Inference System (ANFIS) with Gaussian and ...
Eleftherios Giovanis
core
Design automation based on fluid dynamics [PDF]
, 2017 This article was accepted and presented at the 9th International Workshop on Bio-Design Automation, Pittsburgh, Pennsylvania (2017).Microfluidic devices provide researchers with numerous advantages such as high throughput, increased sensitivity and ...
Densmore, Douglas +3 more
core
ANFIS based hybrid approach identifying correlation between decision making and online social networks [PDF]
, 2018 Areeba Rahman +6 more
openalex +1 more source
Forecasting Unemployment Rate Using a Neural Network with Fuzzy Inference System [PDF]
Greece is a low-productivity economy with an ineffective welfare state, relying almost exclusively on low wages and social transfers. Failure to come to terms with this reality hampers both the appropriateness of EU recommendations and the Greek ...
Camelia Ioana Ucenic +2 more
core
Neuro-Fuzzy approach for the predictions of economic crisis [PDF]
In this paper we present the neuro-fuzzy technology for the prediction of economic crisis of USA economy. Our findings support ANFIS models to traditional discrete choice models of Probit and Logit, indicating that the last models are not very useful for
Giovanis, Eleftherios
core +1 more source
ANFIS Controller for Non-holonomic Robots
Majlesi Journal of Electrical Engineering, 2010 In this paper, a control strategy for a non-holonomic robot based on an Adaptive Neural Fuzzy Inference System is proposed. The neuro-controller makes it possible for the robot to track a given reference trajectory. After a short introduction about Adaptive Neural Fuzzy Inference System, the control strategy which is used on our virtual non-holonomic ...
Wang, T., Sabourin, C., Madani, K.
openaire +2 more sources
Investigation of the performance of Superheated Drop Detectors for unfolding fast neutron spectra produced by cosmic rays using an Adaptive Network-based Fuzzy Inference System (ANFIS) [PDF]
, 2023 Sh. Badiei, P. Rezaeian
openalex +1 more source
Estimation water vapor content using the mixing ratio method and validated with the ANFIS PWV model [PDF]
, 2017 Wayan Suparta +2 more
openalex +1 more source