By Lazaros Iliadis, Chrisina Jayne
This publication constitutes the refereed lawsuits of the sixteenth foreign convention on Engineering functions of Neural Networks, EANN 2015, held in Rhodes, Greece, in September 2015.
The 36 revised complete papers awarded including the abstracts of 3 invited talks and tutorials have been rigorously reviewed and chosen from eighty four submissions. The papers are equipped in topical sections on industrial-engineering functions of ANN; bioinformatics; clever scientific modeling; life-earth sciences clever modeling; learning-algorithms; clever telecommunications modeling; fuzzy modeling; robotics and keep watch over; clever cameras; trend recognition-facial mapping; category; monetary clever modeling; echo country networks.
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Extra info for Engineering Applications of Neural Networks: 16th International Conference, EANN 2015, Rhodes, Greece, September 25-28 2015.Proceedings
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The variable c0 is assumed to be a random variable. We do not attempt to estimate it. It is the task of controller to suppress disturbances. Solution of (25) is not known. One can learn however that because of the derivative of Ωm on the left hand side of the equation, the variable Ωm cannot be expressed as a function of the transformed variables {v1 , v2 , v3 , v4 , v5 }. The system is not static, but the dynamic one. m However if additionally dΩ dt = const = c, equation (25) become algebraic one and Ωm could be expressed as an entangled function of v1 , v2 , v3 , v4 , v5 : c0 = − 2 2 ) = c0 (h0 + h1 Ωm ) + c1 v1 c(h0 + h1 Ωm +c2 Ωm v2 + c3 Ωm v3 + c4 v4 + c5 Ωm v5 .
Simplified FWCS with constant PI gains 16 G. Martins et al. The level controller corrects the level error and the flow controller is an anticipatory signal that detects the difference between mass flows. Regarding the use of the same values of proportional and integral gains in all power levels, and taking advantage of the stability produced by feedback system, it is possible to simulate the closed loop responses and verify that they are dynamically different in each power level. Real Advanced FWCS are PID adaptive.
Eus 2 Department of Mechanical Engineering, University of the Basque Country, C/Alameda Urquijo s/n, 48013 Bilbao, Spain Abstract. Grinding is a key process in high-added value sectors due to its capacity for producing high surface quality and high precision parts. One of the most important parameters that indicate the grinding quality is the surface roughness (Ra). Analytical models developed to predict surface finish are not easy to apply in the industry. Therefore, many researchers have made use of Artificial Neural Networks.