project, it will be designed and realized OBDH-based on FPGA (Field Programmable Gate Array). Because FPGA has many advantages … over commonly used conventional microcontroller. In the development of space technology implementation for FPGA resistant … computational capability, low power consumption, small hardware size, and many others. FPGA-based OBDH in this thesis are designed …

to develop fuzzy inference, adaptive neuro fuzzy (ANFIS) and regression tree models for the debutanizer column. The … the ANFIS model has better estimation accuracy than other models developed in this work and many data-driven models …

-linear autoregressive exogenous) and ANFIS (adaptive neuro-fuzzy inference system) models are separately applied to strengthen this … investigation. NARX and ANFIS, as artificial neural networks (ANN) models, were used for the first time in this study to test the …

adaptive neuro-fuzzy inference system (ANFIS). The validation of the numerical results obtained by Runge-Kutta approach is also … facilitated by computational results generated by ANFIS. …

(ANFISs) and weather conditions. ANFIS combines the interpretability of fuzzy inference systems and the learning ability of …

This work presents an adaptive neuro-fuzzy inference system (ANFIS) artificial intelligence methodology of predicting … purpose, substractive clustering and grid partition approaches were utilized to train the ANFIS models required in estimating … the 2nd law efficiency and total irreversibility using some experimental data. Furthermore, predictions of ANFIS models …

(ANFIS), artificial neural network (ANN) and response surface methodology (RSM) methods were employed. The average energy … ratio was obtained 1.205, and the R2 of the best ANFIS, ANN and RSM models were 0.989, 0.966, and 0.990, respectively, and … MSE was calculated at 0.0005, 0.0015 and 0.00003. The results revealed that the RSM and ANFIS models were preferred to the …

forecast. Methodology/methods: The methods of analysis, synthesis and techniques of mathematical neuro-fuzzy modelling were … relatively low error. Findings: The developed ANFIS model is a suitable tool for predicting stock indexes. The importance of the …

major steps; 1) Data preparation 2) Modelling/Generation of IGNRN, and; 3) Measuring three classes of centrality, namely …