Model design of Forecast and Determining the organization's resource innovation capacity With the approach of neural-adaptive fuzzy inference system (ANFIS).

In today's competitive world where innovation is a condition for the survival of any organization, it is important to know the level of innovation capacity of the organization's resources, which is related to organizational policy, technology transfer, life and competition of the organization. The main purpose of this research is to design a model to determine and predict the level of innovation of organizational resources. After reviewing the available sources and interviewing experts, using confirmatory factor analysis, 12 main indicators in the form of 3 dimensions were determined as input to the fuzzy inference system. Among the new modeling methods, fuzzy systems have a special place in various sciences. Neuro-adaptive fuzzy inference system (ANFIS) is a good way to solve nonlinear problems. This method is a combination of fuzzy inference and artificial neural network that uses the ability of both to model. Using three types of model design methods in the fuzzy system and comparing the results, the best result for presentation was determined. To evaluate the performance of the model, the parameters of squared mean square error (RMSE), relative error percentage (ε), mean absolute error (MAE) and coefficient of determination (R2) were used, which were 0.047, 1.02%, 0.046 and 989 / Is achieved and indicates the accuracy and reliability of the model. This research is applied in terms of purpose and survey type according to the data collection method. The output of this study is ANFIS.