This research was conducted to optimize the distribution system using Adaptive Neuro Fuzzy Inference System (ANFIS) method. Objective functions used are to minimize active power loss, node voltage deviation, number of switches, and maintain balance of the feeder. This function is modeled in a fuzzy set to build basic characteristics. The Method has been applied to the 32 bus IEEE standard distr...

For a fast and accurate evaluation of the values damaged fragrant pears, prediction method damage degree Korla pears was proposed. To study variation laws damages under different volumes squeezing deformation, partial least squares regression (PLSR), generalised neural network (GRNN) adaptive fuzzy inference system (ANFIS) were chosen to predict establish optimal model. The results demonstrated...

Thermal errors can have significant effects on CNC machine tool accuracy. The errors come from thermal deformations of the machine elements caused by heat sources within the machine structure or from ambient temperature change. The effect of temperature can be reduced by error avoidance or numerical compensation. The performance of a thermal error compensation system essentially depends upon th...

This paper assesses the operator functional state (OFS) based on a collection of psychophysiological (i.e., cardiovascular and EEG) and performance measures. Two types of adaptive fuzzy model, namely ANFIS (adaptivenetwork-based fuzzy inference system) and GA (genetic algorithm) based Mamdani fuzzy model, are employed to estimate the OFSs under a set of simulated process control tasks involved ...

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 ...

infiltration plays an important role in surface and subsurface hydrology and it is a key factor in the rainfall and runoff equations. the use of new approaches that have no limitations of common theoretical and empirical methods to determine infiltration relationships, will minimize the necessity of time consuming and costly experiments to determine permeability values and will make it possible...

The aim of this research is to analyze ANFIS performance for prediction of financial time series data. Financial time series data is usually characterized by volatility clustering, persistence, and leptokurtic data behavior. The financial time series data are usually non-stationary and non-linear. ARIMA has a good performance to predict linear time series data, but its performance is decreasing...

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 proximate analysis is the most common form of coal evaluation and it reveals the quality of a coal sample. It examines four factors including the moisture, ash, volatile matter (VM), and fixed carbon (FC) within the coal sample. Every factor is determined through a distinct experimental procedure under ASTM specified conditions. These determinations are time consuming and require a signific...

This paper introduces the application of the hybrid approach Adaptive Neuro-Fuzzy Inference System (ANFIS) for fault classification and diagnosis in industrial actuator. The ANFIS can be viewed either as a fuzzy inference system, a neural network or fuzzy neural network (FNN). This paper integrates the learning capabilities of neural network to the robustness of fuzzy systems in the sense that ...