Purpose. To develop an automated classifier based on adaptive neuro-fuzzy inference system (ANFIS) to differentiate between normal and glaucomatous eyes from the quantitative assessment of summary data reports of the Stratus optical coherence tomography (OCT) in Taiwan Chinese population. Methods. This observational non-interventional, cross-sectional, case–control study included one randomly s...

Oil production estimation plays a critical role in economic plans for local governments and organizations. Therefore, many studies applied different Artificial Intelligence (AI) based methods to estimate oil countries. The Adaptive Neuro-Fuzzy Inference System (ANFIS) is well-known model that has been successfully employed various applications, including time-series forecasting. However, the AN...

Predicting groundwater levels is critical for ensuring sustainable use of an aquifer’s limited reserves and developing a useful abstraction management strategy. The purpose this study was to assess the predictive accuracy estimation capability various models based on Adaptive Neuro Fuzzy Inference System (ANFIS). These included Differential Evolution-ANFIS (DE-ANFIS), Particle Swarm Optimizatio...

Fetal Electrocardiogram Extraction (FECG) identifies the congenital heart problems at the earlier stage. The major problem in the non invasive procedure is the extraction of FECG from Maternal ECG (MECG) and many interferences. The proposed methods (i) Combination of Adaptive Neuro Fuzzy Inference (ANFIS) and Fractional spline wavelet (ii) Combination of Fractional spline wavelet and ANFIS (iii...

There is an increasing interest in modeling groundwater contamination, particularly geogenic contaminant, on a large scale both from the researcher’s as well as policy maker’s point of view. However, modeling large scale groundwater contamination is very challenging due to the incomplete understanding of geochemical and hydrological processes in the aquifer. Despite the incomplete understanding...

In a great diversity of knowledge areas, the variables that are involved in the behavior of a complex system, perform normally, a non-linear system. The search of a function that express those behavior, requires techniques as mathematics optimization techniques or others. The new paradigms introduced in the soft computing, as fuzzy logic, neuronal networks, genetics algorithms and the fusion of...

This article proposes an adaptive neuro-fuzzy inference system (ANFIS) for solving navigation problems of an autonomous ground vehicle (AGV). The system consists of four ANFIS controllers; two of which are used for regulating both the left and right angular velocities of the AGV in order to reach the target position; and other two ANFIS controllers are used for optimal heading adjustment in ord...

Decision making pertaining to injection profiles during oilfield development is one of the most important factors that affect the oilfields’ performance. Since injection profiles are affected by multiple geological and development factors, it is difficult to model their complicated, non-linear relationships using conventional approaches. In this paper, two adaptivenetwork-based fuzzy inference ...

Purpose Respiratory motion prediction is a chaotic time series prediction problem. In this study, respiratory motion predictability from 12 traces from breast cancer patients is examined by using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Interval Type-2 Non Singleton Fuzzy System (IT2NSFLS). Methods Free breathing data curves were obtained from Real Time Position Management system (RPM ...