神經量熱計 的英文怎麼說
中文拼音 [shénjīngliángrèjì]
神經量熱計
英文
neurocalorimeter-
This paper researches the basic statistical rule of oil - gas dynamic system from the systematic theory, combining with the common characteristic and structure characteristic of oil - gas dynamic system, taking the design requirement of oil field development programming into consideration, by using of functional simulation principle ( including nn method, differential simulation method ) and historical data of oil field, establishes the in - out conjunctional relationship of dynamic index of oil field development, and researches the two level index prediction of development dynamic with both oil field and oil production plant on the basis of the in - out conjunctional relationship. furthermore, this paper analyzes the " decision - making variable ", " object " and " restriction terms " by the optimization theory and set up several optimal models which compose the oil field development programming, it is following : optimization model of the production composing ( solving the optimal composing of each subentry production and cor responding cost, workload, including the onshore thin oil production, the heavy oil thermal process production, tertiary oil recovery production, and the offshore production ) ; optimization model of measure production structure ( determining the optimal composing of each measure production and measure workload, which is composed of fracture, acidulation, capital repair and so on ) ; optimization model of the production distraction ( optimal distribution of the whole oil field production to each oil production plant ) and the integrated development programming model of oil field
本文從系統理論出發研究油氣動態系統基本統計規律,結合油氣動態系統的一般特點,結構特點,兼顧油田開發規劃設計的要求,利用功能模擬原理(含神經網路方法、微分模擬方法) ,依據油田歷史數據,建立了油田開發動態指標間的輸入輸出關聯關系,並在此輸入輸出關聯關系的基礎上研究了油田及採油廠兩級的開發動態指標預測,同時利用最優化原理,在分析「決策變量」 、 「目標」及「約束條件」的基礎上建立了多個構成油田開發規劃的「優化模型」 ,這些優化模型包括:產量構成優化模型(解決陸上稀油產量、稠油熱采產量、三次採油產量、海上產量及對應的成本、工作量的最優構成問題) ;措施產量結構優化模型(解決壓裂、酸化、大修等各項措施產量及措施工作量的最優構成問題) ;產量分配優化模型(將油田的產量最優地分配到各採油廠)以及油田綜合開發規劃模型。The goal of this paper is establish the model of calorific value of coal and the count values to forecast the value quickly and exactly
本文的目的在於利用人工神經網路建立發熱量與各計數值之間的模型,快速準確地計算發熱量。It possesses not only the self - learning ability and adaptability, but also the function of self - adjusting factors. based on fuzzy set, neural network theory, the fuzzy control model and fuzzy neural network control model of multi variable system are presented. based on the automatic core - welding line of shop floor control system in yangzhou radiator plant computer integrated manufacturing system ( ys - cims / sfcs ), the fuzzy logic theory was applied to the controlling device and established the main heating room fuzzy temperature controller and finally was put into practical use
本文採用了基於神經網路技術的智能pid控制策略,設計了一類具有自學習和自調整比例因子功能的神經元網路自適應pid控制器的結構及演算法;為解決結構不確定性的復雜多變量系統的控制,基於模糊集及模糊系統、神經網路理論,建立了多變量系統的模糊控制模型及模糊神經網路控制模型;針對揚州水箱廠計算機集成製造系統車間管理與控制系統( ys - cims sfcs )中的實際工程問題,設計和開發了散熱器芯子烘焊自動線主烘腔溫度模糊控制器,解決了生產中長期存在的老大難問題,提高了產品質量,降低了單產能耗。Taking ningxia - inner mongolia reach of yellow river as a study case, a ice regime forecast data warehouse is established for the datamining concerned on the basis of the analysis on the ice regime changing law and its influencing factor of the reach, and then the conceptual mathematic model and artificial neural network model for the parameter calibration of ice regime forecast are built up with gis in combination of the relevant empirical forecast models based on the principles of the hydrological flow muting, thermodynamics and ice hydraulics etc., with which the design and development of the decision support system for the ice regime forecast with the integrated functions of information inquiry, model parameter calibration, temperature forecast and ice regime forecast are preliminarily discussed
摘要以黃河寧蒙河段為例,在對河段歷史冰情變化規律及其影響因素分析的基礎上,建立冰情預報數據庫,進行數據挖掘,並以地理信息系統( gis )為平臺,以水文學流量演算、熱力學、冰水力學等原理為基礎,結合相關經驗預報模型,建立用實測資料進行參數率定的冰情預報概念性數學模型和人工神經網路模型,初步探討了集信息查詢、模型參數率定、氣溫預報、冰情預報等功能為一體的冰情預報決策支持系統的設計與開發。In order to improve measurement precision and display fidelity of the instrument, three new methods of nonlinear calibration of thermal instruments, which are based on intelligent control theory, are presented in this paper, such as nonlinear compensation of zr02 oxygen measurement instrument using bp nn, nonlinear calibration of temperature measurement sensors using cmac nn and nonlinear identification of throttle flow meter using ga. these methods prove to be not only simple but also effective
火電廠熱工儀表普遍存在非線性特性,為了提高參數測量的準確度和儀表顯示的精確度,基於智能控制理論,文中提出了熱工儀表非線性校正的新方法: bp神經網路補償氧化鋯氧量計非線性特性的方法、 cmac神經網路校正測溫傳感器非線性特性的方法、遺傳演算法辯識節流式流量儀表非線性特性的方法。And it would be applied to other blast furnaces after some modifications. to improve the quality of the model, some methods should be used in future : l. impoving the database and making it have more information. 2. considering the mass and thermal accumulation and calculating the effect of the data of every period
2 、模型在作動態計算時,使用日平均數據來調整參數,而用即時的數據來計算預測值,這種方法盡管有一定的科學性,但要提高模型的準確性,必須考慮到高爐內物料和熱量的積累,考慮各個時段入爐物料對化學平衡和熱平衡的影響,根據專家系統和神經元網路的方法,得到更為完善的模型。The neural network methology for heat transfer system of underground heat exchanger was also introduced, which lay emphasis on systematics, entirety and fuzzy systematics, and established predication modeling using neural network. from the computer simulation results, it was concluded that with nn modeling the precision was very high. it is worth to developed and applied for engeering practice and different situation
本文還介紹了主要從系統性、整體性和非線性上來描述地下埋管傳熱系統的神經網路,並針對不同輸入和輸出變量建立了神經網路預測模型,對埋管換熱進行模擬計算和預測,從計算結果可以看出神經網路的模擬值與實驗值相當一致,計算精度高。The important research is about the theory and methods of the cluster analysis in view of statistical theory, the theory and methods of fuzzy cluster analysis, the fkn " s structure and the fkn ' s study algorithm ( fkn, fuzzy kohonen network ) - the organic fusion of the fuzzy c - means algorithm and self - organized feature map neural network. the paper proposes the ifkn ( improved fkn ) on the basis of the hard classification idea and the soft classification idea, then carries on the cluster analysis of the artificial synthetic control chart time series through matlab program and tt ? cluster result matches the cluster result of the famous dataengine " s software of the intellectual data analysis and data mining from german mit company. finally, the paper discusses the applying of the cluster analysis to the control process, which can be widely applied to the pattern recognition of the parameter " s changing trend during the control process and the image partition processing, and utilizes the ifkn to recognize the thermotechnical parameter " s changing trend based on the engineering of clinker sintering rotary kiln automatic control system of guizhou " s aluminium factory, through which good effect is obtained
數據挖掘技術在商業領域中已廣泛使用,然而在工業過程式控制制中的應用卻極少,本文正是在這種背景下,對數據挖掘中的聚類分析方法及其在工業過程式控制制中的應用研究作了償試,重點研究了基於統計理論的聚類分析理論和方法,模糊聚類分析理論和方法及模糊kohonen網路( fkn )的結構與學習演算法,即模糊c ? ?均值演算法與自組織特徵映射神經網路( kohonen網路)的有機融合,並根據硬分類思想及軟分類思想提出了改進的模糊kohonen網路( ifkn ) ,通過matlab編程對人工合成控制時序圖數據集進行聚類分析,其聚類效果與當今廣泛使用的數掘挖掘軟體平臺,德國mit公司著名的dataengine智能數據分析和數掘挖掘軟體的聚類效果相當,最後,論述了聚類分析在控制中的應用,它可以用於過程式控制制中的參數變化趨勢的模式識別及圖象分割處理等具體應用中,並以貴州鋁廠熟料燒結回轉窯自動控制系統為工程背景,利用ifkn識別其熱工參量變化趨勢,取得了較理想的效果。The third chapter employed a new method of taking pressure as step to simulate refrigerant flow characteristics in adiabatic capillary tubes, based on adiabatic capillary tube mathematic models. refrigerant critical flux in capillary tubes is predicted by means of back - propagated method. it indicates that this method can save computational time, so it can be used in engineering
在建立絕熱毛細管數學模型基礎上,採用以壓力為步長的新方法對絕熱毛細管進行了模擬計算,採用bp神經網路對製冷劑在毛細管中臨界流量進行了預測,結果表明該方法能夠較大幅度地節省計算時間,因而具有工程應用價值。Adopting bp model calculative method, that is trainbpx, could shorten the time of model exercitation and study and realize the amalgamation between neural networks and thermodynamic models of crycooler. the learned neural networks model could be used in the thermodynamic calculation of crycooler
採用改進的bp模型演算法,即動量?自適應學習速率演算法,使模型訓練和學習的時間大大減少,從而實現了神經網路與製冷機熱力模型之間的融合,學習后的神經網路模型可直接用於製冷機的熱力計算。分享友人