`Study on Dynamic Survey of HGCHP Exchanger Using Neuro Fuzzy Controller
In the paper, an adaptive technique is proposed for the analysis of HGCHE. An adaptive technique is named as the Neuron Fuzzy Controller (NFC), which is used to predict the accurate results of GCHE. The design of a coil from the source of heat from the ground was analyzed. The parametric studies are analyzed to hold the effective standard that leads the parameters of input executed in the design to have an output value. The model of optimum for parallel ground doubled hotness technique was recommended various tools to analysis economic. With the utilization of NFC, the parametric analysis is carried out and predicts the accurate results. The NFC is one of the most important types of Artificial Intelligence (AI) techniques, which is mostly used for the classification and prediction purpose. The parametric data are given as the input of the NFC has been evaluating the error function. The rate of false positive and true positive are decided to evaluate the accuracy. To evaluate the proposed technique, error in square mean, Average Error (AE), Absolute error in mean value, the percentage of absolute mean error and Normalized error in square (NRMSE) are calculated. The NFC is designed in the MATLAB platform and predict the accurate results. The proposed method is compared with the existing methods such as optimized swarm element with network of constant and the economic cost functions like investment cost and operating cost also analyzed. In addition, the Thermal Response Tests (TRTs) are determined and evaluated under the proposed and existing methods .