The occurrence of catastrophic floods will increase the uncertainty hydrological forecasting at downstream stations. In order to solve problems unclear propagation law in middle and lower reaches Yangtze River inadaptability traditional methods, this paper uses M-K trend test method analyze annual average flow water level Yichang Hankou For conventional floods, Random Forest (RF), Convolutional...

Conference (FLAIRS-19) was held 11–13 May 2006 at the Crowne Plaza Melbourne Oceanfront Hotel in Melbourne Beach, FL. The general cochairs were Philip Chan and Debasis Mitra, from the Florida Institute of Technology. The program cochairs were Geoff Sutcliffe, from the University of Miami, and Randy Goebel, from the University of Alberta. The special tracks chair was Barry O’Sullivan, from Unive...

We present a hybrid and stand-level forest ecosystem model, DRAINMOD-FOREST, for simulating the hydrology, carbon (C) and nitrogen (N) dynamics, and tree growth for drained forest lands under common silvicultural practices. The model was developed by linking DRAINMOD, the hydrological model, and DRAINMOD-N II, the soil C and N dynamics model, to a forest growth model, which was adapted mainly f...

Present study investigates the capabilities of six distinct machine learning techniques such as ANFIS network with fuzzy c-means (ANFIS-FCM), grid partition (ANFIS-GP), subtractive clustering (ANFIS-SC), feed-forward neural (FNN), Elman (ENN), and long short-term memory (LSTM) in one-day ahead soil temperature (ST) forecasting. For this aim, daily ST data gathered at three different depths 5 cm...

Biogas is a significant renewable fuel derived by sources of biological origin. One today’s research issues the effect biofuels on engine efficiency. The experiments are complicated, time consuming and expensive. Furthermore, evaluation cannot be carried out beyond permissible limit. purpose this to build an artificial neural network successfully for dual diesel with view overcoming experimenta...