English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Radial Basis Function Network Based Design of Incipient Motion Condition of Alluvial Channels with Seepage Incipient motion is the critical condition at which bed particles begin to move. Existing relationships for incipient motion prediction do not consider the effect of seepage. Incipient motion design of an alluvial channel affected from seepage requires the information about five basic parameters, i.e., particle size d, water depth y, energy slope Sf, seepage velocity vs and average velocity u. As the process is extremely complex, getting deterministic or analytical form of process phenomena is too difficult. Data mining technique, which is particularly useful in modeling processes about which adequate knowledge of the physics is limited, is presented here as a tool complimentary to model the incipient motion condition of alluvial channel at seepage. This article describes the radial basis function (RBF) network to predict the seepage velocity vs and average velocity u based on experimental data of incipient condition. The prediction capability of model has been found satisfactory and methodology to use the model is also presented. It has been found that model predicts the phenomena very well. With the help of the RBF network, design curves have been presented for designing the alluvial channel when it is affected by seepage. Návrh aluviálneho kanála s použitím siete "Radial Basis Function Network" (RBF) v podmienkach pohybu dna koryta, ovplyvneného priesakom z kanála Návrh aluviálneho kanála s ohľadom na iniciáciu pohybu dna koryta, ovplyvneného priesakom vyžaduje informáciu o piatich základných parametroch: veľkosti častice d, hĺbke vody y, sklone čiary energie Sf, rýchlosti priesaku vs a priemernej rýchlosti prúdenia u. Pretože proces je extrémne zložitý, získať deterministickú alebo analytickú formu riešenia je ťažké. Príspevok opisuje získavanie údajov (data mining technique), bežne používané pri modelovaní. Opisuje aj sieť tzv. "radial basis function (RBF)" na prognózu rýchlosti priesaku vs a priemernej rýchlosti u; výpočet je založený na experimentálnych hodnotách v štádiu začínajúceho sa pohybu častíc v koryte. Bola konštatovaná dobrá schopnosť modelu prognózovať začínajúci pohyb; je uvedená tiež metodológia používania modelu. Bolo zistené, že model predpovedá uvedené javy veľmi dobre. Je tu opísaný návrh aluviálneho kanála ovplyvneného priesakom pomocou návrhových kriviek vytvorených pomocou siete RBF.