توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱EVOLUTIONARY BASED OPTIMAL DESIGN OF SR MOTORS VIA NEUROFUZZY MODELING OF NATURAL FREQUENCIES OF CYLINDRICAL SHELLS
نویسنده(ها): ، ، ،
اطلاعات انتشار: نوزدهمین کنفرانس بین المللی برق، سال
تعداد صفحات: ۱۰
Analysis of dynamic behavior of cylindrical shells is essential in design wherever it is used. Equations of shell vibrations are partial differential equations of order eight which their exact solution is possible only in special cases with a few known boundary conditions and with a lot of simplified assumptions. On the other hand finite element method does not yield a lumped model or a general solution for natural frequencies of cylindrical shells. In this paper natural frequencies of cylindrical shells in a wide range of dimensions are obtained with either exact solution or finite element method and they are applied to training of a Locally Linear Neurofuzzy Network. Finally a general model for calculation of natural frequencies of cylindrical shells has been proposed. Then the model has been applied for optimal design of a Switched Reluctance motor with the evolutionary algorithms as optimization method.<\div>

۲The New Mixed Stochastic Power–Supply Noise–Aware Floorplanning Technique
نویسنده(ها): ، ،
اطلاعات انتشار: سیزدهیمن کنفرانس مهندسی برق ایران، سال
تعداد صفحات: ۵
Nowadays, with the high demand of Very Large Scale Integration (VLSI) design and also high work frequency for circuits, the related issues such as noise cancellation, reduction, and modelling have become more important. In order to solve power supply noise problem, in the floorplanning level, this paper develops a new mixed algorithm based on priority–based max–flow algorithm, and decoupling capacitance insertion technique. We considered the new algorithm, as a part of a floorplanner and select the floorplan with the optimized area, wire length, and power supply noise reduction and power supply network design objectives.<\div>

۳Evolving Artificial Neural Networks for Prediction in Robocup Soccer
نویسنده(ها): ،
اطلاعات انتشار: نهمین کنفرانس دانشجویی مهندسی برق، سال
تعداد صفحات: ۵
The prediction of the future states in Multi Agent Systems such as Robocup Soccer has been a challenging problem since the beginning of the MAS. Robocup 3D Soccer is selected because of its global view of the agents. An Artificial Neural Network is used for prediction. The goal is to concentrate on the design of an optimal ANN. In order to handle it, a genetic algorithm is used for optimization of the design, which shows a great improvement over the manual methods<\div>
نمایش نتایج ۱ تا ۳ از میان ۳ نتیجه