neural gas networks

基本解釋

In order to predict coal bed gas content quantitatively, a BP neural networks model was established using a BP neural networks prediction method.
爲(wèi)了對(duì)煤層含氣量進(jìn)行定量預(yù)測(cè)，採(cǎi)用BP神經(jīng)網(wǎng)絡(luò)預(yù)測(cè)方法，建立了煤層含氣量預(yù)測(cè)的BP神經(jīng)網(wǎng)絡(luò)模型。
A new hybrid method for prediction of solids holdup in gas-solid circulating fluidized bed is proposed based on chaos phase reconstruction and wavelet package as well as neural networks.
提出了一種將混沌的相空間重?fù)k、小波包分析和神經(jīng)網(wǎng)絡(luò)相結(jié)郃的新方法用於預(yù)測(cè)氣-固循環(huán)流化牀的顆粒濃度。
In this paper, a new measurement method of flow velocity in gas-solid two phase flow is presented by using linear neural networks.
本文提出了一種以線性神經(jīng)網(wǎng)絡(luò)爲(wèi)基礎(chǔ)測(cè)量氣、固兩相流速度的新方法。