radial multiple 中文意思是什麼
radial multiple
解釋
徑列復管孔-
A non - contact drive and control method on capsule type micro robot was proposed, in which exterior permanent magnet driver was composed of multiple tegular magnetic poles magnetized in radial direction, while interior permanent magnet driver built in robot was in the same structure as exterior one
摘要提出一種以徑向磁化的瓦狀多磁極組成的圓筒式永磁體為外驅動器，以嵌入機器人本體內與外驅動器同磁極結構的永磁體為內驅動器的非接觸式驅動控制方案。 -
Taking load uncertainties, infeasibility problem and multiple objection of the reactive power optimization in the radial distribution system into consideration, loads are modeled as fuzzy interval numbers. fuzzy power flow is proposed based on fuzzy interval load for the more practical membership function of line losses rate and maximal voltages offset. this thesis presents multiple objection model of the reactive power optimization considering uncertainties using the fuzzy set theory
對配電網電壓無功優化問題中負荷的非概率性的不確定性問題、多目標問題、約束不可行性問題進行了研究，用模糊區間來描述實際的負荷情況，並用負荷的模糊區間值計算配電網的潮流，得到有功功率損耗和電壓的模糊區間值，使網損率和節點電壓最大偏移量的隸屬函數更接近實際情況；將改進遺傳演算法與模糊集理論相結合，通過求解多目標函數和約束條件的模糊集合的交集，得出網損率和節點電壓最大偏移量最小的最優運行狀態。 -
The conclusion is that sheering and radial stress are dominant in viscosity shearing force, and that reynolds stress is larger than viscosity stress in turbulent flow, and the multiple is the reynolds number
由分析可知在粘性應力中，切向和徑向剪切應力佔主導地位；而在湍流條件下，雷諾應力是粘性應力的若干倍數，此倍數在量級上即為雷諾數。 -
Through study of correlative contents of advanced computer cybernetics, artificial intelligence, the domain knowledge and special crop growth mechanism in greenhouse, we present the system of multi - sensor data fusion ( msdf ) based on radial basis function network ( rbf ) to implement on line detection for nutrient - liquid, which may realize multiple components detection on - line, for example no3 -, cl -, ca2 +, ph, ec, nh4 +, k + and so on. the soft sensor ' s mechanism is introduced to overcome the limitations of sensor ' s manufacturing process. to improve the believe - degree of soft sensor ' s result, we analyze soft sensor ' s result by uncertain inferential capacity and combination rule of evidential theory
本論文通過對計算機技術、控制理論、人工智慧技術和設施農業領域知識等相關理論的研究，結合對特定溫室蔬菜生長的研究與機理分析，提出了一種基於rbf神經網路的營養液多傳感器數據融合（ msdf ）系統，實現對營養液組分： no _ 3 ~ - 、 cl ~ - 、 ca ~ （ 2 + ） 、 ph 、 ec 、 nh _ 4 ~ +和k ~ +的在線檢測；對于由於目前傳感器製造工藝的限制而不能在線檢測的離子成分如磷酸根和硫酸根，提出了一種基於徑向基函數網路的軟測量機制，可以有效地實現對營養液中磷酸根和硫酸根成分的實時檢測；為了提高軟測量結果的可信度，利用d - s證據理論的不確定推理能力和合成公式，結合領域知識對軟測量結果進行可信度分析。 -
Making use of the idea of the parallel genetic algorithms, presenting the adaptive multiple subpopulation evolutive strategy. presenting extinction and immigration strategy in order to avoid the similar or even same individuals appear. in order to enhance convergence velocity of reactive power optimization of the radial distribution system, combining the characteristic of the radial distribution system, a sensitivity analysis approach was build up for optimal selection of capacitors and mutation of transformer tap changer
為了提高配電網無功優化的收斂速度，結合配電網的特點，提出採用簡單可行的靈敏度公式選擇無功電容補償器的安裝地點，並用靈敏度分析變異變壓器分接頭，使變異運算元的選取更符合配電網無功優化問題中關于調節變壓器分接頭的實際情況，減少了一些不必要的變異運算，使適應性和魯棒性加強；根據實際情況採用無功補償電容器的啟發式變異，使變異運算元的選取更符合無功優化問題中關于補償電容器的實際。 -
A multiple objects optimization design for whole performance of a radial - axial flow cryogenic turboexpander
軸流低溫透平膨脹機整體性能多目標優化設計 -
In the multiple - layered test for injection wells, a lot of pressure falloff curves in the single layers are hard to show a radial flow straight line due to the perturbative phenomena of multilayer reservoir, low permeability or short test time
摘要在注水井分層測試中，由於油藏的低滲透性或者測試時間相對較短等原因，各層的壓力恢復曲線難以出現徑向流直線段。 -
However, there have still some unresolved problems : first, how to determine the number and size of the clusters automatically during the clustering process. second, how to utilize the " local " ridge regression method which including multiple regularization parameters in learning rbf network. third, those clusters in irregular form ca n ' t represented by radial basis function, thus we must find some other basis functions that can describe the irregular form
但是仍然存在幾個問題尚待解決：首先，聚類時怎樣自動確定簇的個數和半徑；其次，如何利用含有多個正規化參數的局部嶺回歸方法進行rbf網路學習；第三，如果簇的形狀是不規則的，則它很難用徑向基函數來描述，因此需要研究其它能代表不規則形狀的簇的基函數。
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