Time series prediction has been widely used in a variety of applications in science, engineering, finance, etc. There are two different modeling options for constructing forecasting models in time series prediction. Global modeling constructs a model which is independent from user queries. On the contrary, local modeling constructs a local model for each different query from the user. In this p...

Due to scarcity of fossil fuel and increasing demand of power supply, we are forced to utilize the renewable energy resources. Considering easy availability and vast potential, world has turned to solar photovoltaic energy to meet out its ever increasing energy demand. The mathematical modeling and simulation of the photovoltaic system is implemented in the MATLAB/Simulink environment and the s...

The output power delivered by solar photovoltaic (PV) module depends on weather conditions and to obtain maximum they are required to operate at maximum available power point for different weather conditions. Maximum power point tracking (MPPT) controllers are usually employed in PV power systems to extract maximum power. Since the solar PV module characteristics are highly nonlinear, conventio...

The use of Artificial Intelligence methods is becoming increasingly common in the modeling and forecasting of hydrological and water resource processes. In this study, applicability of Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) methods, Generalized Regression Neural Networks (GRNN) and Feed 5 Forward Neural Networks (FFNN), for forecasting of daily river f...

This paper presents novel GA-ANFIS expert system prototype for dermatological disease detection by using dermatological features and diagnoses collected in real conditions. Nine dermatological features are used as inputs to classifiers that are based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for the first level of fuzzy model optimization. After that, they are used as inputs in Genetic ...

Carbon nanostructures are famous structures which are used in several industries such as separation, treatment, energy storage (i.e. methane and hydrogen storage), etc. A successful modeling of activated carbon preparation is very important in saving time and money. There are some attempts to achieve the appropriate theoretical modeling of activated carbon preparation but most of them were almo...

Ziqiang Bi 1,2, Jieming Ma 1,2,*, Xinyu Pan 1, Jian Wang 1 and Yu Shi 1 1 School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215011, China; [email protected] (Z.B.); [email protected] (X.P.); [email protected] (J.W.); [email protected] (Y.S.) 2 Department of Computer Science and Software Engineering, Xi’an Jiaotong-Liverpool Unive...

This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for classification of electroencephalogram (EEG) signals. Decision making was performed in two stages: feature extraction using the wavelet transform (WT) and the ANFIS trained with the backpropagation gradient descent method in combination with the least squares method. Five types of EEG signals were us...

In recent years, soft computing and artificial intelligence techniques such as artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) have been effectively used in various civil engineering applications. This study aims to examine the potential of ANN and ANFIS for modeling the compressive strength of concrete containing expanded perlite powder (EPP). For doing this, ...

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...