{"title":"RBF modeling of Incipient Motion of Plane Sand Bed Channels","authors":"Gopu Sreenivasulu, Bimlesh Kumar, Achanta Ramakrishna Rao","country":null,"institution":"","volume":20,"journal":"International Journal of Computer and Information Engineering","pagesStart":2688,"pagesEnd":2694,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/11421","abstract":"To define or predict incipient motion in an alluvial\r\nchannel, most of the investigators use a standard or modified form of\r\nShields- diagram. Shields- diagram does give a process to determine\r\nthe incipient motion parameters but an iterative one. To design\r\nproperly (without iteration), one should have another equation for\r\nresistance. Absence of a universal resistance equation also magnifies\r\nthe difficulties in defining the model. Neural network technique,\r\nwhich is particularly useful in modeling a complex processes, is\r\npresented as a tool complimentary to modeling incipient motion.\r\nPresent work develops a neural network model employing the RBF\r\nnetwork to predict the average velocity u and water depth y based on\r\nthe experimental data on incipient condition. Based on the model,\r\ndesign curves have been presented for the field application.","references":null,"publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 20, 2008"}