Neural networks and fuzzy systems have been the subject of much interest in recent years for the control of nonlinear processes. Much research has been directed at indirect control schemes where, basically, the neural network or fuzzy system has been used to identify the process, and a controller has been synthesised from this model. An alternative approach is that of direct control where the n...

With the rapid development of natural gas pipeline, the safety of natural gas pipeline is paid more and more attention to. This paper presents a new safety assessment model based on fault tree and fuzzy neural network. Firstly, in the light of fault tree theory, fault tree analytical figure is established for buried natural gas pipeline system and the index system is established about buried na...

Nowadays, due to the competitive conditions of global market, corporations try to outsource their extraneous processes to third-party suppliers. So, selecting a proper supplier play a significant role in organization success. The supplier selection problem can be viewed as a group decision-making problem with multiple criteria. Since in previous researches the inter relationship between cri...

With regard to limits in annual budget for maintenance, inevitably, one must choose prioritized projects to optimize the allocated budget in the network. This paper looks into prioritization based upon models including all effects of important factors such as pavement condition index, road type, traffic volume as well as rehabilitation and maintenance cost. Analytical hierarchy process and fuzz...

Caixia Li , Sreenatha Gopalarao Anavatti, Tapabrata Ray University of New South Wales @ Australian Defence Force Academy [email protected] Abstract-This paper focuses on the design and implementation of the analytical hierarchy process (AHP) using Fuzzy inference techniques. This AHP-FUZZY approach is a multi-criteria combination system. The nature of the AHP-FUZZY approach is pair-...

in this paper, we introduce a takagi-sugeno (ts) fuzzy model which is derived from a typical multi-layer perceptron neural network (mlp nn). at first, it is shown that the considered mlp nn can be interpreted as a variety of ts fuzzy model. it is discussed that the utilized membership function (mf) in such ts fuzzy model, despite its flexible structure, has some major restrictions. after modify...