收斂參數模型 的英文怎麼說
中文拼音 [shōuliǎnshēnshǔmóxíng]
收斂參數模型
英文
convergent parameter model- 收 : Ⅰ動詞1 (把攤開的或分散的事物聚集、合攏) put away; take in 2 (收取) collect 3 (收割) harvest...
- 斂 : Ⅰ動詞1 (收起; 收住) hold back; keep back 2 (約束) restrain 3 (收集; 徵收) gather; collect; ...
- 參 : 參構詞成分。
- 數 : 數副詞(屢次) frequently; repeatedly
- 模 : 模名詞1. (模子) mould; pattern; matrix 2. (姓氏) a surname
- 收斂 : 1 (減弱或消失) weaken or disappear 2 (約束言行) restrain oneself 3 [數學] convergence; constr...
- 模型 : 1 (仿製實物) model; pattern 2 (制砂型的工具) mould; pattern3 (模子) model set; mould patter...
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Disigning coolant channel on the firebox of liquid rocket engine to loxodrome ( equal - angle helix ) groove can improve firebox coolant capability greatly. because the width dimension of loxodrome groove is narrow and the depth is deep, some machining methods are incapable, such as end - milling or electrochemistry. according to the peculiarities, a cnc disk - cutter - milling method which is composed of five motion axes with four simultaneously interpolated ones is researched. because most firebox generatrix is composed of complex curves, it is very difficult to get cnc cutting program with manual means. in order to deal with the problem, the loxodrome mathematics model is studied, and an auto - programming software system is developed. the software system can generate cnc cutting program of loxodrome on many kinds of turned surface. the constriction - distension segment of firebox is the most representative workpiece. the sharp changing of its generatrix slope makes loxodrome milling difficult. with the theory analyzing and practice cutting experiment, some applied techniques, which include milling mode and direction, choosing cutter diameter and cutting start point setting, are developed. adopting the technology above, tens regular workpiece have been manufacturing. the two - year manufacture practice has confirmed the validity and feasibility of developed loxodrome coolant channel milling method. the developed technology is also worth to be referenced to other similar workpiece
將液體火箭發動機燃燒室的冷卻通道設計為斜航線(等傾角螺旋線)槽形,可以大幅度改善燃燒室的冷卻性能.斜航線冷卻槽的槽寬尺寸較小而槽深尺寸較大,所以無法使用棒銑刀銑削、電化學等加工方式.針對這些特點,提出了五軸控制、四軸聯動的數控片銑刀銑削加工方法.由於燃燒室外表面的母線輪廓復雜,手工編制數控加工程序難度大.為了解決數控加工程序的編制問題,研究了斜航線的數學模型,開發了自動編程軟體系統.使用該系統,可以生成多種母線輪廓回轉體外表面上的斜航線數控加工程序.燃燒室收斂-擴張段的母線斜率變化大,加工難度大,是斜航線冷卻通道加工的最典型工件.經過理論分析和實際切削實驗,研究了針對該類型工件的片銑刀直徑選擇、銑削方式和方向、刀具調整和起刀點的設置等多項實際的加工方案.採用上述的一系列技術,已經成功地加工了數十個合格工件.經過兩年多的實際生產過程應用,驗證了所開發的斜航線冷卻通道加工方法的正確性和可行性.這些加工技術的研製成功,對其他相似類型零件的加工亦具有參考意義A novel dynamic evolutionary clustering algorithm ( deca ) is proposed in this paper to overcome the shortcomings of fuzzy modeling method based on general clustering algorithms that fuzzy rule number should be determined beforehand. deca searches for the optimal cluster number by using the improved genetic techniques to optimize string lengths of chromosomes ; at the same time, the convergence of clustering center parameters is expedited with the help of fuzzy c - means ( fcm ) algorithm. moreover, by introducing memory function and vaccine inoculation mechanism of immune system, at the same time, deca can converge to the optimal solution rapidly and stably. the proper fuzzy rule number and exact premise parameters are obtained simultaneously when using this efficient deca to identify fuzzy models. the effectiveness of the proposed fuzzy modeling method based on deca is demonstrated by simulation examples, and the accurate non - linear fuzzy models can be obtained when the method is applied to the thermal processes
針對模糊聚類演算法不適應復雜環境的問題,提出了一種新的動態進化聚類演算法,克服了傳統模糊聚類建模演算法須事先確定規則數的缺陷.通過改進的遺傳策略來優化染色體長度,實現對聚類個數進行全局尋優;利用fcm演算法加快聚類中心參數的收斂;並引入免疫系統的記憶功能和疫苗接種機理,使演算法能快速穩定地收斂到最優解.利用這種高效的動態聚類演算法辨識模糊模型,可同時得到合適的模糊規則數和準確的前提參數,將其應用於控制過程可獲得高精度的非線性模糊模型For the purpose of discovering the near - globally optimal solution, this paper proposed a hybrid approach of ant colony algorithm and sequential quadratic programming ( sqp )
摘要為了獲得整體近似最優解,提出採用蟻群演算法,搜索發電機可運行狀態的最優組合,並對蟻群演算法的數學模型進行分析,以參數的形式給出具有普遍意義的收斂性定理。Application of the algorithm for different observed head data sets indicate that the model can be successfully applied for aquifer systems where data available may be sparse and with errors. calculated groundwater heads by identification results in fourteen parameter areas are fit for observed heads in field, and flowing filed is similar. the study demonstrates the effectiveness of the ga global optimization model for parameter identification, which is an important step towards real system simulation and effective planning and management of groundwater resources
通過算例研究,表明上述演算法可行,且rbf神經網路方法和退火遺傳演算法對地下水系統參數的識別效果都較好,而退火遺傳演算法較之標準的遺傳演算法具有更好的收斂性將演算法應用到北京市密懷順地區,在收集、分析研究區資料基礎上,建立了北京市密懷順平原區地下水模擬模型,並用遺傳演算法進行了地下水系統參數識別,在十四個分區情況下,計算水位與實際水位擬合的較好,各應力期末的計算與實測等水位線基本一致,表明該識別值較為合理。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。This paper consists of two parts : in the first part, we will discuss the prob - lem of the pth - mean, complete consistency for the estimators of a nonparamet - ric and linear model with l ~ p - mixingale errors ; in the second part, we will dis - cuss the problem of the rth - mean 、 complete consistency for the estimators of themodels above with weak stationary linear process errors and the uniformly mean consistency. to the nonparametric model y _ ni = g ( x _ ni ) + _ ni, 1 i n, let g _ n ( x ) = w _ ni ( x, w _ n1, … ? xnn ) y _ ni estimate the unknown function g ( x ). to the linear model y _ i - x _ i1 1 + … ? + x _ iq ? _ q, we use lse _ nj to estimate the unknown parametric _ j
本篇論文主要是由兩大部分內容構成:一是關于誤差是l ~ p ?混合序列的線性回歸模型參數的最小二乘估計與非參數回歸模型未知函數的權函數估計的p ~ -階平均相合性和完全收斂性問題;另一部分是關于誤差是弱平穩線性過程的線性模型參數的最小二乘估計與非參數回歸模型未知函數的權函數估計的r ?階平均相合性和完全收斂性以及權函數估計的一致平均相合性問題。The system identification method is presented for backcalculating the dielectric property and thickness of pavement structures. the method of singular value decomposition is put forward to diagnose the ill - conditioned governing equation and the problem of finding solution to ill - conditioned governing equation is successfully resolved. the parameter adjustment arithmetic with high accuracy, which is based on precise theory and can be converged rapidly, is established
提出了路面結構層介電特性及其厚度反演分析的系統識別方法,將奇異值分解技術應用於控制方程的病態診斷和求解,有效地解決了控制方程病態時的求解問題,建立了理論嚴謹、收斂快、精度高的模型參數調整演算法,並開發了路面結構層材料介電特性及其厚度反演分析軟體sidthk 。First, based on comprehension analysis of the present study status on optimizing method to displacement back analysis in underground engineering home and abroad, intelligent optimizing method, which fits the features of underground engineering, has been developed by introducing annealing algorithm and genetic algorithm and improving them. second, according to practical features of nonlinear displacement for underground engineering, the mechanical model on back analysis to initial ground stress and mechanical parameters of surrounding rock mass in underground engineering is established, which is based on the measuring results of displacement of convergence in underground holes. while, by introducing finite element method and combining improved annealing algorithm and improved genetic - annealing algorithm, the theory and method of elastic - plastic displacement back analysis to surrounding rock in underground engineering has been founded
首先,本文在綜合分析國內外地下工程優化位移反分析方法研究現狀的基礎上,引進模擬退火與遺傳演算法,並對其進行改進,建立了適合於地下工程問題特點的智能優化演算法;其次,根據地下工程非線性特點,基於地下工程洞周收斂位移量測結果,建立了用於地下工程初始地應力與圍巖力學參數反演分析的力學模型,並引進有限元分析手段,結合改進模擬退火演算法與改進遺傳-模擬退火演算法,分別建立了基於這兩種智能優化演算法的地下工程圍巖彈塑性位移反分析理論與方法,並開發了相應的分析計算程序,為地下工程圍巖穩定性與開挖順序優化分析奠定了基礎;然後,在上述基礎上,根據地下工程開挖施工順序優化設計的特點,建立了基於圍巖塑性區面積的地下工程開挖施工順序優化分析模型,基於改進模擬退火演算法與改進遺傳-模擬退火演算法建立了地下工程開挖施工順序優化分析方法,並開發了相應的分析計算程序;最後,將上述分析計算程序用於工程實例分析,探討了其應用方法,證明了該文研究成果的合理性和可靠性。This literature suggests a non - linear muskingum model which can exactly reflect the above mentioned effect and offers an effective approach : mixed generating arithmetic ( abbreviated as mga ) which is capable of estimating the parameters k 、 x 、 m in a non - linear muskingum approach with considerable accuracy and high speed of convergence
本文提出正確反映這種作用的非線性馬斯京根模型成為必要,並提出一種十分有效的方法混合遺傳演算法(以下簡稱mga ) ,能很好地估計非線性馬斯京根模型中的參數k , x , m之值,而且計算精度高,收斂速度快。The nonrecursive algorithm is proved to terminate in finite steps and turn out to be a constant vector too. because two modifications estimated models are asymptotically uniformly nonsingular, thus the possible singularity in the adaptive pole placement systems is completely avoided. however the prior knowledge required is only the observability indices of systems, thus, the required prior knowledge is greatly reduced
非迭代的修正策略證明了參數修正向量在有限步內收斂於一個常向量;上述兩種修正策略均保證了估計模型的一致能控性,從而徹底解決了自適應極點配中可能出現的奇異性問題,而所需的先驗知識僅為系統的能觀性指數。It comes up with a new notion, d - solution, which is applied to the distance estimation, by virtue of hilbert space ; furthermore, the dissertation has gained a necessary condition which is identity of minimum mean - square value in linear function classes, so that d - solution extends minimum mean - square value within the domain of nonlinear function equation or equation system ; and, the dissertation studies in detail the classical moment estimation and maximal likelihood estimation on the parameters of ar ( p ), a series of theorems in the estimation section shows the moment estimators are consistent on the ground of large samples jikewise, those distribution functions of the estimated parameters accord to maximum likelihood estimation converge gauss distribution if the white noise is gaussan
首先,藉助hilbert空間理論,提出了距離估計的d -解,給出了d -解的必要條件,這個條件在線性函數類里即是極小二乘估計法, d -解的必要條件滿足的方程實質上將極小二乘估計法推廣到多函數及非線性函數類。再而,詳細地研究了多元弱平穩序列自回歸模型ar ( p )的參數經典的矩的替代估計和極大似然估計,獲得矩的替代估計的一致性的結果。對基於gauss白噪聲假設多元弱平穩序列自回歸模型的均值、白噪聲的協方差陣的極大似然估計都有依分佈收斂到多元正態分佈的統計性質。Chapter 5 is focused on the studies on the equivalent conditions for maximum value convergence of sums of independent random matrix sequences, and the sufficiency condition of the strong consistency of m estimator of regression parametric in linear model for negatively associate samples, thus enriching and strengthening the results of a series of papers
第五章得到了獨立陣列和(含加權和)的最大值完全收斂的等價條件,從而豐富和強化了前人的一系列結果獲得了負相關樣本線性模型中回歸參數m估計是強相合的較弱的充分條件By studying the solution to generalized effective medium satori resistivity model in laminated and dispersed shaly sand, it shows that there is a local minimum of the function about w derived from the model in the range from 0 to, and the w corresponding to the minimum varies with or w as well as other parameters, therefore, in order to ensure the iteration convergence, here, we adopt a hybrid algorithm combining newton and bisection, and the calculated result shows that using the hybrid algorithm to solve the equation about w is convergent. it is pointed out that shale distribution largely affects water saturatio n predicted by this model
通過研究混合泥質砂巖有效介質通用satori電阻率模型的求解方法,表明模型導出的關于_ w函數在0 -區間內存在一個局部極小值,且該極小值點對應的_ w隨或_ w及其他參數的變化而變化,因此,為了保證迭代收斂,採用牛頓和二分結合的混合迭代演算法,試算結果表明利用牛頓和二分混合迭代演算法求解關于_ w的方程是收斂。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。As the essential electrical calculation means, load flow calculation provides important basis for power systems operation and studies, and is indispensable to advanced power systems application software. in this thesis, the development of methods for load flow solution of distribution networks at present have been fully analyzed and evaluated in the aspect of convergence. the algorithm for distribution power systems base on the complex matrix was proposed in this paper, the proposed methods is very efficient and required less computer memory storage observably
潮流計算是電力系統中應用最廣泛、最基本,也是非常重要的一種電氣計算。它給電力系統的研究人員和實際運行人員提供了重要參考依據,也是許多電力系統高級應用軟體中不可缺少的一部分。本文針對配電網潮流計算的現狀進行了全面分析,深入討論了目前各方法的特點,並從收斂性能及各方面指標進行了比較分析,提出了基於復數矩陣的配電網潮流的原理、數學模型和實現方法,並通過編程于以實現。And then, the eight - parameter 2d projection model is optimized by ga, including adjusting genetic operators to eliminate the local convergence and premature convergence problem
接著本文採用遺傳演算法優化二維投影模型的8個參數,通過調整遺傳運算元來消除局部收斂和末成熟收斂問題。This method can guarantee the solution matrix of sylvester equation to be inverse and the sum of the input gain norm and the observer gain norm is the minimum. for the linear systems with unknown parameters, we identify the parameters using hopfield network, then design the observers using the identified parameters, the exponential convergence of adaptive observer is also proved. for the linear time - varying systems, a new network to solve the time - varying sylvester equation is proposed, we analysis it ' s convergence and robustness, then, deign the linear time - varying observer using this network model, and we discuss the convergence of the observer and ruboustness to unknown match parameters
同時保證了sylvester方程的解矩陣的可逆性和觀測器的增益矩陣與輸入矩陣范數的和最小;在設計線性時不變自適應觀測器時,首先利用系統的輸入、輸出數據設計一個hopfield網路參數估計器,進一步設計狀態觀測器,證明了參數估計器和狀態觀測器的指數收斂性;為了仍然從神經優化計算的角度設計線性時變系統的狀態觀測器,最後介紹了一種求解時變sylvester矩陣方程的神經網路模型,分析了它的收斂性和魯棒性,然後利用該網路設計時變狀態觀測器,進一步討論該觀測器的在系統存在未建模不確定和外部噪聲時的魯棒性;最後給出了一種基於分離性原理和hopfield網路觀測器的狀態反饋閉環系統的結構,分析了該閉環系統的特點;對于每一種設計方法都給出了相應的數值模擬例子來進一步表明所提方法的可行性和有效性。The pheromone - based parameterized probabilistic model for the aco algorithm is presented as the solution construction graph that the combinatorial optimization problem can be mapped on. based on the solution construction graph, the unified framework of the aco algorithm is presented. an iterative update procedure of the solutions distribution in the problem ' s probabilistic model is proposed, that will converge to the optimal solutions with probability one, then the minimum cross - entropy pheromone update rule is proposed to approximate the iterative update procedure by minimizing the cross - entropy distance and monte - carlo sampling
基於解空間參數化概率分佈模型,首先提出了一個以概率1收斂于最優解的解空間概率分佈的迭代更新過程,然後提出了通過最小化不同分佈間的交互熵距離以及蒙特卡洛采樣來逼近此迭代過程的最小交互熵信息素更新規則,接著分別給出了弧模式以及結點模式信息素分佈模型下的最小交互熵等式。It will eliminate the handicap of slow speed and elevate the correction of recognizing flow type by displacing the traditional arithmetic. it will provide a new method of creating model and measurement to the special parameters in some difficult system. this article is also the development and exploration of two - phase flow measurement and information fusion
利用信息融合代替傳統的數學建模方法,這將克服以往演算法收斂速度慢等缺陷,並能提高流型識別的準確率,這將為復雜系統中難測參數的建模和檢測提供新途徑,本論文也是對兩相流檢測和信息融合的一個發展和探索。On the base of analysing the shortcoming of genetic algotithms, three improved techniques for genetic algorithms are bring forward in this paper : fuzzy penalty fitness function, random dislocation arithmetic crossover, fuzzy parameter adjust policy, which improve genetic algorithms capability of global convergence and convergent speed. at the same time, the improved genetic algorithms are applied to nonlinear mixed integer problems and complex nonlinear function optimization
在分析實數型遺傳演算法不足的基礎上,本文研究了遺傳演算法的關鍵技術,分別提出了模糊懲罰評價函數、隨機錯位算術雜交運算元、模糊自適應參數控制等改進技術,以提高遺傳演算法的全局收斂性和收斂速度,並應用於求解非線性混合整數規劃問題和復雜高維的函數優化問題。分享友人