a new approach for pole placement of nonlinear systems using state feedback and fuzzy system is proposed. we use a new online fuzzy training method to identify and to obtain a fuzzy model for the unknown nonlinear system using only the system input and output. then, we linearized this identified model at each sampling time to have an approximate linear time varying system. in order to stabilize...

In recent years, many studies have been done on forecasting fuzzy time series. First-order fuzzy time series forecasting methods with first-order lagged variables and high-order fuzzy time series forecasting methods with consecutive lagged variables constitute the considerable part of these studies. However, these methods are not effective in forecasting fuzzy time series which contain seasonal...

This paper introduces a time efficient deep learning-based solution to the traveling salesman problem with window (TSPTW). Our goal is reduce total tour length traveled by -*the agent without violating any limitations. will aid in decreasing required supply type of service, as well lowering emissions produced automobiles, allowing our planet recover from air pollution emissions. The proposed mo...