日負荷預測 的英文怎麼說

中文拼音 [rìfùhéyùcè]
日負荷預測 英文
daily load prediction
  • 日 : Ⅰ名詞1 （太陽） sun 2 （白天） daytime; day 3 （一晝夜; 天） day 4 （泛指某一段時間） time 5 （日...
  • 負 : Ⅰ名詞1 （負擔） burden; load 2 （虧損） loss 3 （失敗） defeat Ⅱ動詞1 [書面語] （背） carry on th...
  • 荷 : 荷名詞（蓮） lotus
  • 預 : Ⅰ副詞（預先; 事先） in advance; beforehand Ⅱ動詞（參與） take part in
  • 測 : 動詞1. （測量） survey; fathom; measure 2. （測度; 推測） conjecture; infer
  • 負荷 : [電學] load; charge; weight
  • 預測 : calculate; forecast; prognosis; divine; forecasting; foreshadowing; predetermination
  1. Then, mre reaches 3. 21 % for workday and 5. 96 % for holiday. a unique next 24 hours hourly cooling load prediction ann model is established

    對工作日負荷預測，其平均預測誤差是3 . 21 ；對假日負荷，其平均預測誤差是5 . 96 。
  2. Mean relative error ( mre ) is reduced to 1. 36 % from 2. 02 %. based on a unique day cooling load predicting ann model, day cooling load predicting ann model for workday and holiday is established respectively

    在研究一個統一的日冷負荷預測模型來預測周一到周日所有日子的日冷負荷的基礎上，針對工作日和假日分別建立了日總冷負荷的神經網路預測模型。
  3. Chapter iii tries to establish the mathematic model of daily gas consumption forecasting, focusing on the introduction of index smooth forecasting theory and determining the reasonable flatness constant

    第三章，建立了日用氣負荷預測的數學模型，重點介紹了指數平滑預測理論，確定了合理的平滑常數，進行日用氣負荷預測，用歷史統計數據與預測結果進行對比分析。
  4. To make the prediction values with independence of the general trend, which is changed from year to year, the load data are transformed by profiles, mean value, and variance. sofm is used for the prediction of profiles and mlp networks for prediction of daily mean and daily variance. at a result, load forecasting for 24 hours in a day can be gotten

    為使預測值不受負荷逐年變化這一趨勢的影響，把負荷數據變換為特徵、均值和方差的形式，利用白組織競爭網路預測負荷的特徵，然後利用多層感知器網路預測負荷的日均值和方差，最終實現對一大24小時負荷的預測。
  5. Combining it with the standard daily load curve can make the mean daily forecasting error with in 2 %

    將其與標準日負荷曲線取平均作為預測結果，示例表明日平均誤差小於2 % 。
  6. The paper completes daily load forecasting based on clustering analysis and ann. this offers credible basis for scheming generating electricity

    本文利用聚類分析、神經網路方法實現了電力系統日負荷預測，為發電計劃的制定提供了可靠依據。
  7. This article aims at the research and exploitation of day loading forecast system of electrical net of hebei province, and expatiates emphatically the process and meaning of the realization of loading forecast system of electrical net that based on intellectualized

    本文針對河北電網日負荷預測系統的研究與開發，著重闡述了基於智能化的電力負荷預測系統的實現過程及其意義。
  8. This paper analyzes the character of the transformer load and presents the control means to reduce the comprehensive power loss to minimum by controlling the transformer operation status, which forecasts the daily load of transformer by periodical auto - regression model ( par ) and divides the daily flow line automatically into two typical phases. then, this paper simulates the par by matlab. at last, a real intelligent control device based on the ti ’ s tms320lf2407 dsp has been completed

    論文分析了配電變壓器的負載特點；提出採用周期自回歸模型預測配電站用電日負荷，根據負荷預測結果和用電時段，以綜合功率損耗最小為目的變壓器經濟運行控制方法；以ti公司的tms320lf2407dsp為基礎，完成了配電站變壓器經濟運行智能監控裝置的研製。
  9. In summer, load is affectd by meteorological elements greatly. based on multidimension time series approach, the car model is constructed, which could take account into the accumalated influence from temperature and inertia action from historic load, meanwhile, the advantage of the model is that its expreaasion is in the form of apparent function, which could provide us some quaqutive imformation existed between input variable and output variable

    本文以多維時間序列分析方法為基礎，成功地解決了未來日負荷與前些日負荷慣性變化的影響，以及氣象累計效應的影響顯性函數關系問題，從而為負荷預測人員掌握未來負荷與歷史負荷，歷史氣象要素與當日氣象條件之間的規律，提供了量化的分析基礎。
  10. Applying forecasting and controls theory, the author analyzes the statistics data of civil use of urban gas in the wisco, establishes forecasting models for the daily and hourly gas consumption, and compares the model result with the real load. on this basis, the author maintains that it is necessary to adopt control measures and reasonably organize production. moreover, the author puts forward a feasible plan to improve the current production technology, in order to meet users " needs and meanwhile reduce cost of production and increase enterprise profit

    運用預測與控制理論對武鋼民用煤氣歷史統計數據進行分析，建立了日用氣負荷和小時用氣負荷預測模型，將預測結果與實際負荷進行對比，採取控制措施進行生產調度，合理組織生產，提出了改變現行生產工藝的可行性方案，以達到既保證用戶需要，又降低生產成本，增加企業利潤的目的。
  11. To improve accuracy of forecasting, all the facts, such as influence of basic load, temperature, weather related sensitive factors and festive national holidays are considered systematically and simultaneously

    為提高負荷預測的精度，本文同時考慮基本負荷、溫度、天氣敏感因素、節假日等多種影響負荷預測的因素。
  12. As to the selection of neural network input node, not only is related historical load was introduced as ? the drilling sample, but also influence of temperature and weather sensitive factors to the load variance is considered. 4

    在神經網路輸入節摘要點的選擇方面，除了引入相關歷史負荷作訓練樣本外，還考慮了溫度、氣候敏感因素和特徵日對負荷變化的影響，提高了負荷預測的精度。
  13. After a short - term load forecasting method based analogous and linear extrapolation is proposed, the load forecast and the priority of equipment action are led into static reactive power optimization. the aim function is constructed for the practical situation of power system. on the basis of traditional genetic algorithm the fitness function and the holding of population diversity are improved

    在提出基於相似日和線性外推的短期負荷預測新方法的基礎上，將負荷預測和設備動作優先級引入靜態無功優化中，並結合電網實際情況，構造了實用的目標函數，對遺傳演算法的適應度函數和群體多樣性的保持進行了改進，採用鄰域搜索運算元增加遺傳演算法的局部尋優能力。
  14. Secondly, based on the characteristic datum extracted from the datum of daily peak load, the probability model of the nature random part of power load is established ; the grey gm ( 1, 1 ) model is improved to forecast the basis part of power load ; after the relation model is established on the basis of the researching the relationship between the climate part of power load and climate factors, the probability model of the climate part of power load is established combined with the tentative probability model of temperature

    然後，在日最大負荷數據中提取自然隨機分量的特徵數據，建立其概率模型並實現參數估計；改進灰色gm （ 1 ， 1 ）模型，完成年最大負荷中基礎負荷分量預測；研究氣候負荷與各氣候因素的關系，建立合理的氣候負荷與溫度關系模型，結合假設溫度概率模型，完成年最大負荷中氣候負荷分量的概率模型建立。
  15. According to the research results from som model, 8 sub neural network is adopted in inner and mae of hourly cooling load prediction is reduced 80. 64kwh. expected error percentage ( eep ) is reduced to 3. 27 %. next 24 hours hourly cooling load prediction multi - output dynamic model is established and prediction accuracy is improved again

    建立了一個統一的空調逐時負荷的24小時提前人工神經網路預測模型，並根據對日冷負荷類型的som分類結果，通過在內部一共採用8個子神經網路模型使得逐時負荷預測平均絕對誤差降低到了80 . 64kwh ，期望相對誤差降低到了3 . 27 。
  16. At last, based on the analysis of electric load, we build 24 - hour forecasting models according the type of the date and the weather. with all above the discussions, we build the software

    在對負荷變化規律分析的基礎上提出了按日期類型分開建模的24小時預測模型，並對天氣因素進行了有效處理。
  17. This present thesis analyzes the characteristics of the load in - depth. and studies the factors which effect the precision of the load forecasting, such as the type of day, special holidays, all kind of weather factors and so on

    通過對電力系統負荷特性的認真深入分析，總結了影響短期負荷預測的各種因素如日類型、特殊節假日、各種天氣因素等。
  18. A model for short term and super short term forecasting integrating neural network, expert system and dynamic clustering is introduced here, which involves weather, festival and other load forecasting affecting factors

    介紹了一種整合神經網路、專家系統和動態聚類多種智能方法為一體的短期/超短期預測模型，綜合考慮了氣象、節假日等負荷影響因素。
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