In iimom , the general concept of model parameter vector , which refers to the parameter vector determined by the designer in the multi - objective optimization model ( such as the weight vector in the weighted - sum meth 在mom中,給出了模型參數向量的一般概念,表示多目標優化模型中需要由設計者設定的參數向量(如加權系數法中的權重向量) 。
At first , on the basis of the sufficient and necessary optimality conditions , we give a certain algorithm to compute the trust region subproblem ; then , we draw out a different scheme for parameter vector in cim 在分析子問題最優性條件的基礎上,我們給出了錐函數模型信賴域子問題的求解算法;并從數據擬合的角度提出了對錐模型中參數向量的另外一種選擇方案。
The least square estimation in linear model is used to derive the two - stage estimation of the item parameter vector 1 of j th item as follows : noting that xj consists of the nuisance parameters s , j , j , were updated so that the estimation of 6 s could be renewed 修正進而修正x _ j和,從而形成一種新的估計方法?雙重兩步迭代估計蒙特卡洛模擬結果顯示,雙重兩步迭代估計提高了估計對真值的恢復能力。
This research focuses on synthesizing advanced multiobjective optimization such as physical programming with artificial neural networks ( ann ) , fuzzy technology and interactive design technology to develop more effective multiobjective optimization methods : developed fuzzy physical programming , which could deal with the fuzzy uncertainties in engineering design problem more effectively ; developed ann - based interactive physical programming , which is applicable and effective in large scale complex engineering multiobjective optimization problems ; based on the model parameter vector concept and the ann model of the designer ' s preference structure , this thesis developed intelligent interactive multiobjective optimization method ( iimom ) , providing a complete and effective solution for the medium and small scale multiobjective optimization problems 本文主要將物理規劃等先進的多目標優化方法和神經網絡( ann ) 、模糊技術、交互式技術相結合,提出了新的更有效的多目標優化方法:提出了模糊物理規劃方法,能夠更有效地處理工程多目標設計問題中的模糊不確定性;提出了基于神經網絡的交互式物理規劃方法,適用于大規模復雜工程多目標設計問題;以模型參數向量概念和設計者偏好結構的ann模型為基礎,提出了智能交互式多目標設計方法( mom ) ,為中小型多目標優化問題給出了一個完善、有效的解決方案。
In this paper , we consider the optimal parameter vector a of the modified incomplete gauss _ seidel method ( migs ) . we prove that the spectral radius function of the iterative matrix t of migs with parameter vector is strictly monotonic decreasing with respect to a satisfying 0 e if the classical gauss _ seidel method converges for a z _ matrix . some properties of the left and right eigenvectors corresponding to the largest eigenvalue in modulus are given , too . these results are useful to find an optimal parameter for migs 目前主要的方法有兩類:一是充分利用所給矩陣a的特點,采用適當的主元素選取策略,使分解出的因子盡可能地保持稀疏性;二是迭代法。對于第二種方法,迭代矩陣的選取具有決定作用。只有選取的迭代矩陣的譜半徑小于1才能保證迭代法收斂。