Dealing with uncertainty is one of the most critical problems in complicated pattern recognition subjects. In this paper, we modify the structure of a useful Unsupervised Fuzzy Neural Network (UFNN) of Kwan and Cai, and compose a new FNN with 6 types of fuzzy neurons and its associated self organizing supervised learning algorithm. This improved five-layer feed forward Supervised Fuzzy Neural N...

In this paper we present a fault detection strategy for wireless sensor networks. The strategy is based on modeling a sensor node by Takagi–Sugeno–Kang (TSK) fuzzy inference system (FIS), where a sensor measurement of a node is approximated by a function of the sensor measurements of the neighboring nodes. We also model a node by recurrent TSK-FIS (RFIS), where the sensor measurement of the nod...

Most existing multi-attribute optimization researches for the modern CNC (computer numerical control) turning industry were either accomplished within certain manufacturing circumstances, or achieved through numerous equipment operations. Therefore, a general deduction optimization scheme proposed is deemed to be necessary for the industry. In this paper, four parameters (cutting depth, feed ra...

The paper describes the application of a combined neuro-fuzzy model for indoor temperature dynamic and automatic regulation. The neural module of the model, an auto-regressive neural network with external inputs (NNARX), produces indoor temperature forecasts that are used to feed a fuzzy logic control unit that simulates switching the heating, ventilation and air conditioning (HVAC) system on a...

In this paper we propose a new scheduling policy namely IRD (Intelligence Request Dispatcher) for web switches operating at layer-7 of OSI protocol stack in a web server farm .we classify dynamic and static requests. A hybrid Neuro-Fuzzy and LARD like approach is used to make route decision of dynamic and static requests separately. IRD select server with lower response time in an adaptive disp...

The efficiency of a wind turbine highly depends on the value of tip speed ratio during its operation. The power coefficient of a wind turbine varies with tip speed ratio. For maximum power extraction, it is very important to hold the tip speed ratio at optimum value and operate the variable-speed wind turbine at its maximum power coefficient. In this paper, an intelligent learning based adaptiv...

Nowadays, the demand for high product quality focuses extensive attention to the quality of machined surface. The (CNC) milling machine facilities provides a wide variety of parameters set-up, making the machining process on the glass excellent in manufacturing complicated special products compared to other machining processes. However, the application of grinding process on the CNC milling mac...

Surface roughness is often considered the main purpose in contemporary computer numerical controlled CNC machining industry. Most existing optimization researches for CNC finish turning were either accomplished within certain manufacturing circumstances or achieved through numerous equipment operations. Therefore, a general deduction optimization scheme is deemed to be necessary for the industr...

Based on the developed neural-fuzzy control system for anaerobic hybrid reactor (AHR) in wastewater treatment and biogas production, the neural network with backpropagation algorithm for prediction of the variables pH, alkalinity (Alk) and total volatile acids (TVA) at present day time t was used as input data for the fuzzy logic to calculate the influent feed flow rate that was applied to cont...

Weather operations play an important and integral part of planning, execution and sustainment of mission operations. In this paper, a neuro-fuzzy hybridization technique is applied to model the weather operations and predict its impact on the effectiveness of air tasking operations and missions. Spatiotemporal weather data from various meteorological sources are collected and used as the input ...