allocation and removing of excess water from the irrigation and drainage network is one of the most important activities in the management of these networks. side weir is one of the most common structures for this purpose. study on the flow hydraulic characteristics of this structure included two parts, defining the water surface profiles and estimating the discharge coefficient. to estimate th...

This paper illustrates a Comparative study of highly non-linear, complex and multivariable Inverted Pendulum (IP) system on Cart using different soft computing techniques. Firstly, a Fuzzy logic controller was designed using triangular and trapezoidal shape Membership functions (MF's). The trapezoidal fuzzy controller shows better results in comparison to triangular fuzzy controller. Secondly, ...

Electrical load forecasting is well-known as one of the most important challenges in the management of electrical supply and demand and has been studied extensively. Electrical load forecasting is conducted at different time scales from short-term, medium-term and long-term load forecasting. Adaptive neuro-fuzzy inference system is a model that combines fuzzy logic and adaptive neuro system and...

In this study, artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS) were used to estimate shear stress distribution in streams. The methods were applied to the 145 field data gauged from four different sites on the Sarimsakli and Sosun streams in Turkey. The accuracy of the applied models was compared with the multiple-linear regression (MLR). The results showed t...

In this paper, ‎the multi-sensor fault diagnosis in the exhaust temperature sensors of a V94.2 heavy duty gas turbine is presented‎. ‎A Laguerre network-based fuzzy modeling approach is presented to predict the output temperature of the gas turbine for sensor fault diagnosis‎. Due to the nonlinear dynamics of the gas turbine, in these models the Laguerre filter parts are related to the linear d...

in this study, a new adaptive controller is proposed for position control of pneumatic systems. difficulties associated with the mathematical model of the system in addition to the instability caused by pulse width modulation (pwm) in the learning-based controllers using gradient descent, motivate the development of a new approach for pwm pneumatics. in this study, two modified feedback error l...

Today, DC motors is still being used globally due to their easy speed controllability. In this article, an Adaptive Neuro-Fuzzy Inference System (ANFIS) controller is designed for DC motors. The main purpose of performing such task is to reduce the DC motor starting current and deleting the ripple current during starting time in considering control parameters such as: rise time, settling time, ...

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...

In this paper, an innovated method is used for cooling Milling zone of Stainless Steel via Adaptive Neuro-Fuzzy Inference System (ANFIS) using non-touch laser thermometer for non-touch measuring of the temperature. This method is economically appropriate because of its optimization in using coolant. In comparison to the ways which were designed to optimize the ratio of coolant, this method is t...

The purpose of this study is to model and optimize the detection of tar in cigarettes during the manufacturing process and show that low yield cigarettes contain similar levels of nicotine as compared to high yield cigarettes while B (Benzene), T(toluene) and X (xylene) (BTX) levels increase with increasing tar yields. A neuro-fuzzy system which comprises a fuzzy inference structure is used to ...