Accurate predictions of sea level with different forecast horizons are important for coastal and ocean engineering applications, as well as in land drainage and reclamation studies. The methodology of tidal harmonic analysis, which is generally used for obtaining a mathematical description of the tides, is data demanding requiring processing of tidal observation collected over several years. In...

The main purpose of the current research is comparing the results of Artificial Neural Network (ANN) with Adaptive Neuro-Fuzzy Inference System (ANFIS) with regard to determination of the importance of soil properties affecting clay dispersibility. After taking samples from two depths of 0-40 and 40-80 cm, the spontaneous and mechanical dispersions of clay were recorded using both weighing and ...

This chapter discusses the foundation of neuro-fuzzy systems. First, we introduce Takagi, Sugeno, and Kang (TSK) fuzzy model [l,2] and its difference from the Mamdani model. Under the idea of TSK fuzzy model, we discuss a neuro-fuzzy system architecture: Adaptive Network-based Fuzzy Inference System (ANFIS) that is developed by Jang [3]. This model allows the fuzzy systems to learn the paramete...

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...

Monitoring and predicting machine components' faults play an important role in maintenance actions. Developing an intelligent system is a good way to overcome the problems of maintenance management. In fact, several methods of fault diagnostics have been developed and applied effectively to identify the machine faults at an early stage using different quantities (Measures or Readings) such as c...

The water level in boiler drum is the critical control parameter to be addressed for providing the efficient and safe operation of steam generators in power plants. The regulation is achieved by using the Artificial Intelligence (AI) technique, namely, Adaptive Neuro-Fuzzy Inference System (ANFIS). It has the capability of self-learning as ANN with the linguistic expression function of fuzzy in...

This article deals with utilization of the combination of the fuzzy system and artificial intelligence techniques, called the Adaptive Neuro Fuzzy Inference System ANFIS, with the aim to refine the diagnostic quality of the abdominal fetal electrocardiogram FECG. Within the scope of the experiments carried out and based on the ANFIS structure the authors created a complex system for removing th...

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...

Accurate prediction of the water level in a reservoir is crucial to optimizing the management of water resources. A neuro-fuzzy hybrid approach was used to construct a water level forecasting system during flood periods. In particular, we used the adaptive network-based fuzzy inference system (ANFIS) to build a prediction model for reservoir management. To illustrate the applicability and capab...

This paper develops an autonomous flight controller for fixed-wing UAV based on ANFIS. Three ANFIS modules are designed for controlling the altitude, the heading angle, and the speed of the UAV. In this way, the UAV position is controlled in threedimensional space: altitude, longitude, and latitude position. The simulation results show the capability of the designed approach and its very satisf...