Accuracy preserving interpretability by a hierarchical fuzzy multiagent design for mobile robot controller

Fast Training Algorithms for Deep Convolutional Fuzzy Systems with Application to Stock Index Prediction

“…For a given input point, say the point Fig. 3 (left), the action of the fuzzy system FS(x * 1 , x * 2 ) can be represented by the fuzzy IF-THEN rule: IF x 1 is A 2 and x 2 is A 3 , THEN y is B 23 , which covers the cell over (…”

“…During this period, the structural and approximation properties of hierarchical fuzzy systems were studied in depth [9]- [12] and many new methods for designing hierarchical fuzzy systems were proposed [13]- [16]. Since then, the hierarchical fuzzy models have been applied to a wide variety of practical problems, such as environmental monitoring [17], educational assessment [18], video deinterlacing [19], price negotiation [20], mobile robots automation [21]- [23], self-nominating in peer-to-peer networks [24], linguistic hierarchy [25], hotel location selection [26], smart structures [27], weapon target assignment [28], image description [29], nutrition evaluation [30], spacecraft control [31], photovoltaic management [32], and wastewater treatment [33]. More recently, the research on the hierarchical fuzzy systems has been advanced along many directions, such as fast implementation [34], adaptive control [35], multiobjective optimization [36], interpretability [37], classification [38], [39] and so on.…”

“…, n 1 . (24) Specifically, for each of the n 1 input-output data pairs of (24), update the c j * 1 ,...,j * m (k) using (21) and (22); for the rest c j 1 ,...,j m (k), keep them the same using (23). Then, copy this…”