Feed Point Optimization using Neural Network
نویسندگان
چکیده
Microstrip antenna is gathering a lot of interest in communication systems. In this paper neural network approach has been used for calculation of feed position of microstrip antenna for maximum power transfer. This paper demonstrates the validity of neural network for the estimation of feed point of patch antenna varying with input impedance. Accuracy of the results encourages the use of Neural network.. Further simulations are done using CST software.
منابع مشابه
Predicting Force in Single Point Incremental Forming by Using Artificial Neural Network
In this study, an artificial neural network was used to predict the minimum force required to single point incremental forming (SPIF) of thin sheets of Aluminium AA3003-O and calamine brass Cu67Zn33 alloy. Accordingly, the parameters for processing, i.e., step depth, the feed rate of the tool, spindle speed, wall angle, thickness of metal sheets and type of material were selected as input and t...
متن کاملSTRUCTURAL DAMAGE DETECTION BY MODEL UPDATING METHOD BASED ON CASCADE FEED-FORWARD NEURAL NETWORK AS AN EFFICIENT APPROXIMATION MECHANISM
Vibration based techniques of structural damage detection using model updating method, are computationally expensive for large-scale structures. In this study, after locating precisely the eventual damage of a structure using modal strain energy based index (MSEBI), To efficiently reduce the computational cost of model updating during the optimization process of damage severity detection, the M...
متن کاملOptimization of Oleuropein Extraction from Olive Leaves using Artificial Neural Network
In this work, the artificial neural networks (ANN) technology was applied to the simulation of oleuropein extraction process. For this technology, a 3-layer network structure is applied, and the operation factors such as amount of flow intensity ratio, temperature, residence time, and pH are used as input variables of the network, whereas the extraction yield is considere...
متن کاملRejection of the Feed-Flow Disturbances in a Multi-Component Distillation Column Using a Multiple Neural Network Model-Predictive Controller
This article deals with the issues associated with developing a new design methodology for the nonlinear model-predictive control (MPC) of a chemical plant. A combination of multiple neural networks is selected and used to model a nonlinear multi-input multi-output (MIMO) process with time delays. An optimization procedure for a neural MPC algorithm based on this model is then developed. T...
متن کاملA Neural Network Method Based on Mittag-Leffler Function for Solving a Class of Fractional Optimal Control Problems
In this paper, a computational intelligence method is used for the solution of fractional optimal control problems (FOCP)'s with equality and inequality constraints. According to the Ponteryagin minimum principle (PMP) for FOCP with fractional derivative in the Riemann- Liouville sense and by constructing a suitable error function, we define an unconstrained minimization problem. In the optimiz...
متن کامل