توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱Dynamic Neural Network by using Feedback Error Learning Approaches for LFC in Interconnected Power System
نویسنده(ها): ، ، ،
اطلاعات انتشار: شانزدهیمن کنفرانس مهندسی برق ایران، سال
تعداد صفحات: ۷
In This paper, a new adaptive controller based on modified feedback error learning (FEL) approaches is proposed for load frequency control (LFC) problem. The FEL controller consists of neural network feedforward controller (NNFC) and conventional feedback controller (CFC), where the CFC is essential to guarantee global asymptotic stability of the overall system. Also, for improved the performance of system the dynamic neural network (DNN) is adopted in NNFC instead of conventional neural network. This neural network has dynamic in itsstructure and consists of two units: inhibitory and excitatory unit. The proposed FEL controller has been compared with the conventional FEL (CFEL) controller and the PID controller through some performance indices.<\div>

۲Creative Algorithm For optimization Circular Antenna Arrays
نویسنده(ها):
اطلاعات انتشار: همایش ملی رویکرد عملی به پیاده سازی مفاهیم علمی،مباحث تئوری و پژوهش های های کاربردی علوم فنی، سال
تعداد صفحات: ۶
Nature–inspired algorithms such as Particle SwarmOptimization and Genetic Algorithm are among the most powerfulalgorithms for optimization. The newly proposed globalevolutionary optimization method; namely, the firefly algorithm(FA) is used to determine an optimum set of weights and positionsfor circular antenna arrays (CAAs) and concentric circular antennaarrays (CCAAs) of isotropic radiators with optimum side lobe level(SLL) reduction is studied. The FA represents a new algorithm foroptimization problems in electromagnetics. It is shown that the FAresults provide a SLL reduction that is better than that obtainedusing well–known algorithms, like the particle swarm optimization,genetic algorithm (GA), and evolutionary programming.<\div>
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