逼近速率 的英文怎麼說

中文拼音 [bījìnsùlǜ]
逼近速率 英文
rate of closure
  • 逼 : Ⅰ動詞1 （逼迫; 給人以威脅） compel; force; drive; threaten 2 （強迫索取） extort; exert pressure ...
  • 近 : Ⅰ形容詞1 （空間或時間距離短） near; close 2 （接近） approaching; approximately; close to 3 （親...
  • 速 : Ⅰ形容詞（迅速; 快） fast; rapid; quick; speedy Ⅱ名詞1 （速度） speed; velocity 2 （姓氏） a surna...
  • 率 : 率名詞（比值） rate; ratio; proportion
  • 逼近 : 1 （靠近 接近） press on towards; gain on [upon]; approach; crowd on; close in on; draw near 2 [...
  • 速率 : speed; rate; tempo
  1. 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。
  2. The artificial neural net ( ann ) way is universal regard as one of the most effective ways of stlf. in this paper, some research is developed for stlf using ann ways in several parts : the first part is about the arithmetic of ann based on bp model, namely the advanced of traditional bp arithmetic, one alterable step and scale bp arithmetic based on comparability of model and probability of accepting bp arithmetic is used to enhances a lot the convergence rate of learning process of bp network, but also avoid the stagnation problem to some extent. it indicates that the ann ' s efficiency and precision by the way can be ameliorated by the simulation of real data

    神經網路方法在短期預測中已經被公認為較有效的方法，本文針對神經網路用於電力系統短期負荷預測的幾個方面展開研究工作：第一部分研究一般用於負荷預測的神經網路bp模型的演算法，即對傳統的bp演算法的改進，將一種基於模式逼近度和接受概率的變步長快速bp演算法應用到短期負荷預測，模擬結果表明該方法有效的改善了bp演算法收斂速度慢以及容易陷入局部最小點的缺點，從而提高了神經網路用於負荷預測的效率和精度。
  3. With regard to the flow regulation of the best - effort traffic, the controllable traffic in high speed computer communication networks, the present paper proposes a novel control theoretic approach that designs a proportional - integrative ( pi ) controller based on multi - rate sampling for congestion controlling. based on the traffic model of a single node and on system stability criterion, it is shown that this pi controller can regulate the source rate on the basis of the knowledge of buffer occupancy of the destination node in such a manner that the congestion - controlled network is asymptotically stable without oscillation in terms of the buffer occupancy of the destionation node ; and the steady value of queue length is consistent with the specified threshold value

    本文從控制理論的角度出發，針對計算機高速網際網路中最大服務交通流即能控交通流的調節問題提出了一種基於多速率采樣的具有比例積分（ pi ）控制器結構的擁塞控制理論和方法，在單個節點的交通流的模型基礎上，運用控制理論中的系統穩定性分析方法，討論如何利用信終端節點緩沖佔有量的比例加積分的反饋形式來調節信源節點的能控交通流的輸入速率，從而使被控網路節點的緩沖佔有量趨于穩定;同時使被控網路節點的穩定隊列長度逼近指定的門限值。
  4. In the research and preparation procedure, it probes into electric field dynamic impedance variation rules, summarizing a set of sparks critical point discrimination methods in solving the key to detect electric field less - spark technology and realizing the less - sparks operation controlling function under impending arcover voltage, putting forward and realizing constant spark rate operation mode, in fiashover treatment adopting method of small descending amplitude, speedy picking up speed, and unlocking silicon controlled rectifier

    在研製過程中探索了電場動態阻抗變化規律，總結出一套識別火花臨界點的方法，解決了探測電場少火花的技術關鍵，實現了逼近擊穿電壓下少火花運行控制功能，提出和實現了恆定火花率運行方式，在閃絡處理上採取下降幅度小、回升速度快、不封鎖可控硅的方法。
  5. In training of back - propagation neural network, parameter adaptable method which can automatically adjust learning rate and inertia factor is employed in order to avoiding systemic error immersed in a local minimum and accelerating the network ' s convergence ; introduced the further optimization of the network ' s structure, it gives the research result of selection of the hidden layers, neurons, and the strategy of re - learning, compared the sums of the deviation square of this algorithm with conventional bp algorithm, as a result, the approach accuracy and the generalization ability of the network were extremely improved

    在對前饋神經網路的訓練中，使用參數自適應方法實現了學習率、慣性因子的自我調節，以避免系統誤差陷入局部最小，加快網路的收斂速度；提出了優化bp網路結構的實驗研究方法，並給出了有關隱含層數和節點數選擇以及再學習策略引進的研究結果。將該演算法同傳統bp演算法的預測偏差平方和進行比較，結果證實網路的逼近精度及泛化能力均得到了極大的提高和改善。
分享友人
分享到 Line

分享到臉書