Neural Network Approaches to Simulation of Spring Flood in Sites of the Lena River| Chapter 1 | New Frontiers in Physical Science Research Vol. 6

 The Republic of Sakha (Yakutia), accompanying an extent of 3103.2 thousand km2, is one of the best constituent bodies of the Russian Federation accompanying a piercingly continental environment and a large group of abundant and narrow rivers and streams. The Lena River is individual of the most protracted waterways of Russia, flows through all republic from cold to northward through the region accompanying different of or in the atmosphere zones, this leads to a a lot of compressing experiences during the spring floods accompanying a big relating to space and material range.Spring-summer floods cause mammoth damage to the domain, inducing inundation of vast domains and objects of the civil saving, that determines the pertinence and need to cultivate and correct flood guessing methods to implement convenient measures for fear that and humble the risk of inundation, especially in laboriously inhabited extents and districts with complex foundation, in the way that strategically main conveniences, underwater crossings of main pipelines, bridges and capacity lines. The projected forms manage possible to estimate water levels all the while spring floods two together on the action of calling a time succession from prior principles and reversion dependences on miscellaneous determinants (iceberg girth, temperature, etc.) and accompanying enough veracity, that is shown for one results of guessing maximum water levels e.g. of two portions of the Lena River, based on classical dossier.