Over the last years, a number of methods have been proposed to automatically learn and optimize fuzzy rule bases from data. The obtained rule bases are usually robust and allow an interpretation even for data sets that contains imprecise or uncertain information. However, most of the proposed methods are still restricted to learn and/or optimize single layer feed-forward rule bases. The main di...

In this paper we investigated a fuzzy logic-based video rate control technique which aims to regulate the data rate of compressed video at a constant transmission rate without objectionable quality degradation. It is considered that conventional fuzzy rule-based control (FRC) does not eeectively control the two variables (video data rate and video quality) which are mutually contradictory. The ...

The existing conventional motion controller does not perform well in the presence of nonlinear properties, uncertain factors, and servo lag phenomena of industrial actuators. Hence, a feasible and effective fuzzy self-tuning proportional integral derivative (PID) and feed-forward control scheme is introduced to overcome these problems. In this design, a fuzzy tuner is used to tune the PID param...

The product safety of food-waste feed is the key factor limiting the development of its industrial chain. In this paper, we construct a method based on data from the testing of food-waste feed with comprehensive evaluation of its product safety by integrating fuzzy mathematics effectively, i.e., the entropy method (EM), and the model of the analytic hierarchy (AHP) process. Furthermore, a hiera...

The selection of proper machining-parameters viz. feed, speed and depth of cut is an important task for obtaining the desired performance in the turning process. This work proposes a neuro-fuzzy control scheme for the selection of feed and speed in a single pass turning. The scheme provides the manufacturer a flexibility of specifying the objectives in linguistic terms. The scheme is dependent ...

By using the single VGA camera installed on mobile robot, a vision-based intelligent obstacle avoidance algorithm is developed in this paper. The image data are processed by edge detection method. By using the adaptive network based fuzzy inference system (ANFIS), the horizontal edge numbers (HEN) and vertical edge numbers (VEN) are feed into ANFIS to train the fuzzy rules such as to control th...

Ibis paper investigates the application of fuzzy algorithm for the speed control of switched reluctance motor (SRM) drives. For the purpose of performance simulation of closed loop SRM drive, its components are modelled in a systematic manner. Hysteresis current controlled midpoint converter is employed to feed four phase 8/6 SRM. Non-linearity caused by magnetic saturation in the motor is also...

The present work deals with developing a fuzzy back propagation neural network scheme for prediction of drill wear. Drill wear is an important issue in the manufacturing industries, which not only affects the surface roughness of the hole but also influences the drill life. Therefore, replacement of drill at an appropriate time is of significant importance. Flank wear in a drill which depends u...

Neural Network is and used to be a principal component of mathematics education. Many models have been developed in the literature for the description of the neural network. In this paper, we use fuzzy number choose the best machine for a job by Feed-Forward Neural Network.

This paper intends to offer a new iterative method based on articial neural networks for finding solution of a fuzzy equations system. Our proposed fuzzied neural network is a ve-layer feedback neural network that corresponding connection weights to output layer are fuzzy numbers. This architecture of articial neural networks, can get a real input vector and calculates its corresponding fuzzy o...