斂足不前 的英文怎麼說
中文拼音 [liǎnzúbùqián]
斂足不前
英文
hold one's steps and refuse to go further-
The method proposed in this thesis do well in solving the problems of multi - damping - ratio - spectra simulation. it is convenient to obtain the pareto optimal solution set of the multi - object question by using implicit parallel genetic algorithms and the method can meet the practical needs for simulating ground motions coinciding with multi - damping - ratio - spectra in seismic design. the crossing rate and variance rate are important parameters of genetic algorithms which affect the rate of convergence, the adapting rate of cross and variation in this paper can auto - adapt and according to stand or fall of current sample, it assures the sample approach to the pareto optimal solution set in fast convergent speed
較好地解決多阻尼比反應譜擬合問題；本文方法通過一次運行就能獲得一組具有集系特性的地震動，在擬合多阻尼比反應譜的人造地震波集系的模擬方面有傳統方法所不能比擬的優勢，產生的人造波或人造波集系可滿足工程抗震設計需要；在遺傳演算法中，交叉概率和變異概率是影響收斂速度的重要參數，本文採用的改進自適應交叉概率和變異概率，可以根據當前樣本的好壞程度來自動地選擇適當的交叉概率和變異概率，以保證演算法始終以較好的速度向pareto最優解集逼近。Secondly, after analyzing the strategic relations between the manufacturer and the supplier, the dissertation brings forward that the manufacturer must category the materials and select different supplier to built relations, explains the features and the advantages and disadvantages of strategic partnerships, and bring forward that the manufacturer must give some special request for the supplier strategic partner. thirdly, the dissertation analyses and summarize the existing methods of supplier selection, and point out their disadvantages. then, the dissertation apply the extenics to the dynamic selection model of the strategic supplier, building the evaluation indexes with implication systems, selecting strategic supplier with rhombus thinking method, looking for the suppliers with the extension of the matter - element, selecting the right supplier with the extension evaluating methods, replacing the dissatisfying features with the transformation matter - element method and making it more better
本文首先對供應鏈管理和戰略合作夥伴關系的國內外研究現狀和發展趨勢進行了研究；其次，對製造商和供應商的戰略合作夥伴關系進行分析，指出了製造商需要對采購物料分類，針對戰略型物料選擇戰略合作夥伴建立戰略合作夥伴關系，闡明了建立戰略合作夥伴關系的特徵及優缺點，並提出了製造商對供應商戰略合作夥伴的具體要求；再次，對目前存在的供應商選擇方法進行了深入的分析和總結，指出了不足之處，並提出了應用可拓理論進行供應商戰略合作夥伴選擇的思路；然後，應用可拓理論建立供應商戰略合作夥伴選擇動態模型，其中，用蘊含系方法建立評價指標體系，用菱形思維建立選擇模型，利用物元的可擴性來尋找待評供應商，用可拓評價進行收斂，並用物元變換對已經選中供應商的不滿意特徵進行變換，使其完善；最後對r企業的供應商戰略合作夥伴選擇進行了本文模型的實證部分，使模型不僅具有理論意義，更具有實踐意義。Based on the single genetic algorithms and the features of the distribution network reconfiguration, this dissertation makes a further study on such aspects as selection operator, crossover operator, mutation operator, termination conditions and etc, thus, puts forward improved genetic algorithms. the dissertation makes certain study on the optimization reconfiguration model of distribution network. it puts forward a multi - objective model and according to the theory of variable weight coefficients transforms the multi - objective problem into a single - objective one
針對目前遺傳演算法在配電網路重構應用中的不足，論文著重從選擇運算元、交叉運算元、變異運算元和收斂準則等方面進行了改進，把最優保存策略和兩兩競爭相結合的方法作為新的選擇運算元，採用隨最優個體相對保留代數自適應變化的交叉和變異運算元，把最優個體最少保留代數作為演算法的終止條件。Their learning and training rules have been analyzed profoundly and their abilities to approximate arbitrary nonlinear function have been testified and compared by the simulation. a new rbf neural network has been presented which uses a raised - cosine function as activation transfer function. it provides a wider generalization in comparison with gaussian rbf neural networks by simulation as well as strong approximation ability, fast convergence, a rule to select the parameters of the networks
本文詳細研究了兩種典型的前向神經網路（ bp網路和rbf網路）的學習和訓練演算法，提出了一種新穎的基於緊支集餘弦函數的徑向基神經網路，其克服了常用的高斯型rbf神經網路雖具有緊支集但各基函數非正交的不足，其收斂速度快、網路參數選取有理論依據且相比于高斯型rbf神經網路具有更強的泛化能力，模擬驗證了其有效性。Fan and yuan [ 6 ] uses another method that has proved under the local error bound condition, if we choice the parameter as the norm of the function, the sequence produced by the levenberg - marquardt method converges quadraticlly to a solution of the system of the equations
如此選取參數有一些不足之處。范、袁在[ 6 ]中用另一種方法證明了當迭代參數為當前迭代點處函數值的模時， levenberg - marquardt方法具有二階收斂性。Pso is simple and efficient, so many researchers have been attracted by this algorithm, and furthermore, it converges fast by moving each particle aimed at guides when it deals with single - objective optimization, and these features are important in multi - objective optimization also. from some current research works, we describe a multi - objective particle swarm optimization algorithm ( mopso ) that incorporates the concept of the enhanced - dominance, we present this new concept to update the archive, the archiving technique can help us to maintain a sequence of well - spread solutions. a new particle update strategy and the mutation operator are shown to speed up convergence
目前，國內外已有部分相關研究成果，但是它們在解集分佈性、收斂性方面仍存在不足，在吸取已有成果的基礎上，本文提出了一種改進的多目標粒子群演算法（ mopso ） ，使用我們提出的強支配概念構造外部種群，使解集保持良好的分佈性，同時，通過採用新的全局極值和個體極值的選取方式及採用新的種群更新策略加快解集的收斂，提出基於快速排序的非支配集構造方法加快演算法運行效率。With the development of morden aero - propulsion system, the simulation technology has became one of the most important means in aeroengine design. aeroengine nonlinear mathematical models, as the basis of engine performance simulation, are not convergence favorably in entire flight scope, because of the solution limitations of nonlinear equation and the engine balance equations
作為數值模擬的基礎與核心，目前廣泛應用的發動機非線性數學模型，由於平衡方程各種迭代解法與模型中非線性方程解法的不足，因而從根本上沒有解決模型在整個包線范圍內的收斂問題，極大地制約了發動機數值模擬技術的發展。Later on, after elaborating the disadvantages of the old methods in detecting and recognizing moving objects, a series of corresponding approaches are proposed, such as grid scan, local tracking bug and dynamic window in object tracing to reduce the huge data needed to be processed, maximum and minimum for selecting a proper segmentation threshold and improved conversion from rgb model to hsv and so on to decrease the influence of inhomogeneous lighting and the color noise, a bilinear interpolation in each quadrant to eliminate the bad effect on the recognition precise because of the distortions of the camera. after that, much emphasis is given on application study in pattern recognition with a feed - forward neural network. both the basic bp algorithm and improved bp algorithm in the study process are described in detail, and the later is used to quicken convergence speed and improve validity of the network
然後，分析和闡明了傳統的運動目標檢測方法的不足，並在此基礎上結合研究中的實際實驗環境，提出了一系列解決方法，包括針對降低龐大數據量而提出的網格掃描、局部「跟蟲」追蹤和動態窗口掃描等目標檢測方法，針對實驗環境中光照不均和顏色干擾提出基於人機交互的最大最小值閾值選取方法和引入改進的rgb模型到hsv模型的轉換方法，為消除圖像畸變對識別精度的惡劣影響而採用的通過控制點進行雙線性插值進行畸變校正的方法；緊接著，概述了神經網路的發展歷史和幾種常用神經網路模型的特點，重點研究了前饋型神經網路在模式識別中的應用問題，詳細闡述了基本的bp演算法和學習過程中bp演算法的改進，從而使網路收斂速度更快，解決問題更有效，並在此基礎上，設計了一個基於bp神經網路的運動目標識別系統，給出了實驗結果。The several ones that have more lager sensitivity to embankment settlement are found out. then, aimed at the traditional three - layer bp network ' s shortages : easily getting into local minimum value and slow convergence, the modification combined momentum method with self - adaptation study velocity is made, and one improved bp network is put forward. finally, according to the results from above sensitivity analyses, the nonlinear model main parameters of each natural layer in roadbed are approximately rectified using the improved bp network technology founded on its stronger nonlinear mapping capacity and the settlement measurements
採用非線性有限元程序，對鄧肯-張模型中8個參數與路堤沉降的關系進行了詳細分析，找到了影響沉降的主要參數；接著，針對傳統的三層bp網路具有收斂速度慢、易陷入局部極小點等不足，對其進行了修正，提出了改進的bp神經網路模型；最後，根據上述靈敏度分析結果，基於改進的bp網路模型較強的非線性映射能力和前期沉降實測資料，對路基中各天然土層的非線性模型主要參數進行了反分析修正； （ 4 ）路堤沉降計算一維法中考慮應力歷史、側向變形的研究。In order to solve the problem of pheromone shortage and slow convergent speed of existing ant system algorithm ( as ) in its application to complex optimal searching, this paper presents a new hybrid adaptive ant system algorithm with pheromone weight multiplier and pheromone balance operator, which can adaptively adjust select probabilities and pheromone strength
摘要針對已有蟻群演算法在復雜問題應用中尋優前期信息素匱乏、收斂速度慢的不足，通過引入信息權重因子和信息量均衡運算元對蟻群的選擇概率和信息素濃度進行自適應調節，提出了混合自適應蟻群演算法。Currently most works on pc employ the sensitivities of the stability energy margin to the generator power injections, which exist some disadvantages and the cause of potential divergence in computation are analyzed. the amount of pre - assigned harmful contingencies in large power systems is a real chanllenge for pc. in this thesis, it is settled soundly through grouping these contingencies into some subsets according to each unstable mode ( um ) provided by eeac, and identifying the worst contingency among each subset by stability energy margin provided also by eeac
預防控制研究大多基於控制參數相對于系統暫態穩定裕度的靈敏度系數，本文分析了此類方法存在的不足和可能迭代不收斂的原因；依據eeac的暫穩裕度量化指標和失穩模式概念，解決了起關鍵作用的暫穩約束的識別問題，克服了當前該領域中僅能研究小規模系統和或少量預想事故約束的局限。分享友人