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• Design of Neural Predictor for Performance Analysis of Mountain Bicycles

  1-6.

  Şahin Yildirim

  Menderes Kalkat

  Views:

  187

  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.

• A Review Regarding Deep Learning Technology in Mobile Robots

  1-5.

  Vlad Ovidiu Mihalca

  Flaviu Birouaș

  Florin Avram

  Arnold Nilgesz

  Views:

  113

  Deep Learning usage is spread across many fields of application. This paper presents details from a selected variety of works published in recent years to illustrate the versatility of the Deep Learning techniques, their potential in current and future research and industry applications as well as their state-of-the-art status in vision tasks, where their efficiency is experimentally proven to near 100% accuracy. The presented applications range from navigation to localization, object recognition and more advanced interactions such as grasping.

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

  1-9.

  Şahin Yildirim

  Asli Durmuşoğlu

  Views:

  153

  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.