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| 【懸賞金幣】回答本帖問題，作者jacket114111將贈送您 6 個金幣 | |||
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jacket114111金蟲 (小有名氣)
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[求助]
請求大神，中文翻譯英文，謝謝幫助 已有1人參與
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| 針對架空線路荷載風險預測問題，基于結(jié)構(gòu)可靠性原理和線路荷載-強度的隨機特性與干涉理論，建立了基于概率神經(jīng)網(wǎng)絡（PNN）的風險預測模型，提取極端天氣下的氣象信息典型特征值風速、覆冰厚度、降雨量、氣溫作為模型輸入量，以線路失效概率劃分的時間尺度上線路的荷載風險狀態(tài)作為預測輸出量。 |
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jacket114111
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According to the principle of structure reliability and the random character of load-strength and load-strength interference theory, the risk forecasting model based on the PNN(probabilistic neural network) is built for overhead lines load risk forecasting problem, using the meteorological typical characteristic value of extreme weather, wind speed, ice thickness, rain fall and temperature as input, using overhead lines load risk on the time scale of lines failures probability. 望您指正，謝謝��！ |
3樓2016-04-24 09:41:17
2樓2016-04-23 01:15:11
【答案】應助回帖
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jacket114111: 金幣+4, ★★★很有幫助 2016-04-25 11:40:44
jacket114111: 金幣+4, ★★★很有幫助 2016-04-25 11:40:44
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本人非英語及你的研究方向的專業(yè)人士，僅理順了一下你的內(nèi)容，僅供參考，若偏差，請諒解。 Based on the principle of structure reliability and the random character and the interference theory of load-strength, the risk forecast model of the overhead lines load is built up using the probabilistic neural network (PNN). In this model, the values including wind speed, ice thickness, rain fall and temperature at the extreme weather are employed to forecast the overhead lines load risks on the time scale which are divided by the lines failures probability method. |
4樓2016-04-25 08:15:26
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