<p class="MsoNormal" style="text-align: left; margin: 0cm 0cm 0pt; layout-grid-mode: char;" align="left"><span class="text"><span style="font-family: ";Arial";,";sans-serif";; font-size: 9pt;">This paper presents a new modeling of elevator group intelligent scheduling system with destination floor guidance. The traditional input mode of separate hall call registration and the destination selection is improved to a single-input mode. On this basis, dynamic partition method in up-peak traffic is studied. This method means dynamically adjust division of floor region based on flow rate and distribution of passenger. Dynamic programming algorithm is used to solve this problem. Through regroupment and classification for ensemble of hall call communication, prediction of multi-objective evaluation items is proposed. Fuzzy Neural Network is constructed and applied further to realize the optimal scheduling policy. Simulated results show that the presented elevator model is effective and the optimized scheduling algorithm has advantaged improvement for overall performance of elevator system.</span></span><span style="font-family: ";Arial";,";sans-serif";; font-size: 9pt;"></span></p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.