Stock market prediction is important and of great interest because successful prediction of stock prices may promise attractive benefits. These tasks are highly complicated and very difficult. In this paper, we investigate the predictability of stock market return with Adaptive Network-Based Fuzzy Inference System (ANFIS). The objective of this study is to determine whether an ANFIS algorithm i...

In the present study, the energetic and economic modeling of lentil and chickpea production in Esfahan province of Iran was conducted using adaptive neuro-fuzzy inference system (ANFIS) and linear regression. Data were taken by interviewing and visiting of 140 lentil farms and 110 chickpea farms during 2014-2015 production period. The results showed that the yield and total energy consumpti...

The utilization of a microgrid with photovoltaic (PV) and wind generation system presents challenge due to their voltage power output variations. This problem is majorly addressed within the converter section using maximum point tracking (MPPT) algorithms regulation strategies. paper an interleaved boost (IBC) modeling control hybrid adaptive neuro-fuzzy inference system-proportional plus integ...

This paper presents an optimum network structure based on a BBO tuned adaptive neuro-fuzzy inference system (ANFIS) to control active suspension (ASS). The unsupervised learning via Biogeography-Based Optimization (BBO) algorithm is used train the ANFIS network. optimal proportional-integral-derivative controller LQR method generate training data set. base Fuzzy c-means (FCM) clustering applied...

nowadays, it has demonstrated that viruses can be transmitted by water and foods. therefore, it causes the research to develop for detecting different viruses in water and foods. among foods, milk can transfer potentially pathogenic viruses. on the other hand, to achieve every method for recovery and extraction of viruses in raw milk it needs to know about impact of milk components on viruses. ...

Accurate solar radiation (SR) prediction is one of the essential prerequisites harvesting energy. The current study proposed a novel intelligence model through hybridization Adaptive Neuro-Fuzzy Inference System (ANFIS) with two metaheuristic optimization algorithms, Salp Swarm Algorithm (SSA) and Grasshopper Optimization (GOA) (ANFIS-muSG) for global SR at different locations North Dakota, USA...

For double inverted pendulum multivariable, strong coupling and nonlinear proposed adaptive fuzzy neural inference system (ANFIS) is applied inverted pendulum stabilization control process. Adaptive control algorithm, fully able to meet the requirements of double inverted pendulum control, ANFIS system after training, will be applied to the inverted pendulum system controller has better control...

In this paper, an attempt has been made to design an computational intelligence technique based expert system using Adaptive Neuro-Fuzzy Inference System (ANFIS) for predicting surface roughness in end milling of Inconel 718. Two different types of membership functions are adopted for analysis in ANFIS training and compared their differences regarding the accuracy rate of the surface roughness ...

Nonlinear system identification is becoming an important tool which can be used to improve control performance. This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for controlling a car. The vehicle must follow a predefined path by supervised learning. Back-propagation gradient descent method was performed to train the ANFIS system. The performance of the...

In this paper, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural networks (ANNs) techniques are developed and applied to identify damage in a model steel girder bridge using dynamic parameters. The required data in the form of natural frequencies are obtained from experimental modal analysis. A comparative study is made using the ANNs and ANFIS techniques and results showed th...