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• Design of Neural Predictor for Performance Analysis of Mountain Bicycles

  1-6.

  Şahin Yildirim

  Menderes Kalkat

  Views:

  185

  In recent years, bicycle races, along with the crest of the high technology continues to increase. Because of this increased races, performance of bicycles, in both biological and mechanical terms, is extraordinarily important and efficient. In terms of the ratio of cargo weight a bicycle can carry to total weight, it is also a most efficient means of cargo transportation. In spite of advanced technology, there are still some problems on bicycles during working conditions and road roughness such as on the mountain from tire and mechanical parts. In this investigation, a extraordinary designed with fiber-carbon body and light bicycle is tested on mountain road conditionswith prescribed trajectory on the mountain for different elevation, speed, hearth rate, bike cadence and average temperature. The real time measured parameters are predicted with proposed two types of neural networks for approaching real time neural network predictors. The results of the proposed neural network have shown that neural predictor has superior performance to adopt the real time bicycle performance.

• Noise and Performances Analysis of Commerical Aircrafts using Artificial Neural Networks

  1-6.

  Şahin Yildirim

  Views:

  92

  Commerical aircrafts are very important part for airway travelling. In spite of high technology on aircrafts, there is still fatality accidents in the world. Because of this reason, it is very important criteria to analyse noises of main elements of the air-craft systems. In tis study, an aircraft’s main disturbances are analysed with proposed neural networks. Firstly, the noises of the jet, turbine and fan were measured from the aircraft. Secondly, the measured parameter values were predicted the proposed neural networks. The results of the proposed neuarl approaches were shown that this type of neural predictors will be employed to predict aircrafts unpredicted disturbances in real time applications.

• Vibration Analysis and Optimal Design of Pneumatic Circuits Using Artificial Neural Networks

  1-9.

  Şahin Yildirim

  Asli Durmuşoğlu

  Views:

  150

  Pneumatic systems are commonly used in industry processes and applications of automotion. These systems are make attractive power transmission with the compressed air, because of they are economic, clear, safe and simple structured.So in this systems, as noise and vibration effects, it’ s undesirable situations both human health and system performances yield and working life. In this study, vibration and noise datas are obtained from two type of pneumatic systems prototype which are classify metal and non-metal materials and performed an analysis with help of this datas and used neural network which has adaptive and quick contruction.