斂集率 的英文怎麼說
中文拼音 [liǎnjílǜ]
斂集率
英文
binding fraction-
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。Packing fraction of fibre
纖維斂集率Another advantage, contrast to using convolutional codes or turbo codes, is its low complexity while maintain high ber performance because the check equations are used to terminate the both iterations. we develop the theoretical error free feedback bound for bpcm - id and predict the threshold for decder convergence using the extrinsic information ransfer chart ( exit )
利用非正則ldpc具有不同度的信息節點概率密度演化的差異，對高階星座中具有較高級別的子通道提供額外的保護，可使迭代反饋判決時，星座子集擁有最大的無錯反饋歐氏距離調和均值，從而改善系統的迭代收斂特性。1, q 3, and at last prove the exisitence of ( q, m + n, n, m ) resilient functions when n > q ? 1. intelligentized ids methods, which can make the system more adaptability and self - studying, are important research directions of ids so far. in order to make the ids systems have better identifying ability and efficiency against new intrusions, we propose the intrusion feature extra - ction algorithm based on ikpca by studying the different kinds of intrusion detection feature extraction algorithm based on unsupervised learning, and then theoretically analysis the conver - gence of the algorithm. in addition, we validate the validity of the algorithm by means of experim - ents ; at the same time, through studying ica and neural networks, we propose fastica - nn ids, and then test the kddcup99 10 % date set to make comparison of kpca 、 ikpca and fastica algorithms in intrusion detection advantages and disadvantages
為了使入侵檢測系統對新的入侵行為有更好的識別能力和識別效率，本文在研究了各種基於無監督學習的入侵檢測特徵提取方法的基礎上，提出了基於增量核主成份分析（ ikpca ）的入侵檢測特徵提取方法，並對該方法進行了收斂性分析，同時結合模擬試驗對其正確性進行了驗證;另外，本文通過研究獨立成份分析和神經網路，提出了基於快速獨立成份分析和神經網路的入侵檢測方法（ fastica - nnids ） ，並通過對kddcup99的10 %數據集的檢測比較了核主成份分析（ kpca ） 、增量核主成份分析（ ikpca ）和快速獨立成份分析（ fastica ）在入侵檢測特徵提取方面的優缺點。Gga has been applied successfully in some optimization applications, for example knapsack problem and travelling salesman problem etc. in second chapter, we first introduce how to construct a goog - point set and the steps to solve problem. then give an example of how to arrange sports items in a track and field game to use gga in the end
它採用數論中佳點集的方法來構造新的遺傳運算元，利用佳點集的性質和特點來提高演算法的效率和收斂性，並且已經成功的在一些優化問題中得到了應用，例如背包、貨郎擔等典型的np難問題。Two convergence theorems, which show that under suitable conditions evolution strategy asymptotically converges to a global minimum point with probability one, are given
對于有界閉集上的連續函數，證明了進化策略以概率為1收斂（幾乎處處收斂）于優化問題的全局極小點。Control of continuous affine nonlinear systems with prescribed exponentially convergent rate and performance by using set - valued analysis method. the concept of controlled
用集值分析方法研究了仿射非線性連續時間系統具-指數收斂率和-性能的7. for the purpose of analyzing its asymptotic convergence properties the evolution strategy procedures for real - valued function optimization are described. two convergence theorems, which show that under suitable conditions the evolution strategy asymptotically converges to a global minimum point with probability one, are given
對于有界閉集上的連續函數，利用作者給出的一種簡潔的方法，證明了一類進化策略以概率為1收斂（幾乎處處收斂）于優化問題的全局極小點，為進化演算法的收斂性分析提供了一種新的模式。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。The convergence of the pnn decision rule for the bayesian decision rule is proved with probability. an explicit formulation of pnn generalization ability is proposed. and the accuracy rate of a classification network is explained as the maximum likelihood estimation of the generalization ability
證明了pnn的決策函數依概率收斂于貝葉斯決策函數;給出了pnn的推廣能力表達式;證明了一個分類網路的測試集正確率是該網路推廣能力的極大似然估計;給出了分類網路中需要的測試集數目表達式;證明了pnn推廣能力不大於由貝葉斯決策所帶來的正確識別率分享友人