fusion parameter 中文意思是什麼
fusion parameter
解釋
熔解參數-
The effects of wing - fuselage fusion design parameter have been analyzed
分析了翼身融合設計參數的影響。 -
Secondly, introducing the image analyzing technology with reference to the disadvantages of the traditional ferr - graph analysis technology, and with the combination of characteristic parameter optimizing filtration so as to raise a description method of debris micro - morphologic character. thirdly, with the application of mode recognition method, completing the process of debris auto - recognition based on the collected information of the debris configuration characteristics ; and conducting the diagnosis on the aero - engine wear faults according to the theory of particle tribology. fourthly, introducing information fusion technology to solve the problem that a single method can not collect enough fault premonitory information to conduct the wear fault diagnosis, hence to conduct the research and exploration in the field of comprehensive diagnosis on the aero - engine ' s multi - fault premonitory information
本文的研究工作主要包括以下五個部分：首先，介紹航空發動機常見的磨損故障類型，研究磨損故障的失效機理，分析磨粒的產生機理、分類以及形態特徵：其次，針對傳統鐵譜分析技術的缺點，引入圖像分析技術，再結合特徵參數優化篩選，形成基於圖像的磨粒顯微形態學特徵描述方法：然後，基於提取到的磨粒形態特徵信息，應用模式識別方法完成磨粒自動識別，並根據顆粒摩擦學的基本原理進行航空發動機磨損故障的診斷與定位：再后，鑒于單一方法不能提取足夠的故障徵兆信息進行磨損故障診斷，本文引入信息融合技術，開展航空發動機多故障徵兆信息綜合診斷方法的研究與探索；最後，基於航空發動機滑油光譜分析與鐵譜分析數據，應用時序模型、灰色模型以及組合模型進行磨損故障的預測方法研究。 -
( 5 ) analysis of data measured with multi - element regression, and optimized mathematics model of grain moisture measurement is brought forward based on contrast of several stat parameters. the particular operating of data fusion method based on parameter estimation is used. the validation is proved by increasing the measurement precision and reducing the ucertain factor
（ 5 ）採用多元回歸分析的方法，對檢測數據進行了分析，在運用各種統計參數進行比較分析的基礎上提出了糧食水分檢測的最佳數學模型。分析了採用基於參數估計方法進行數據融合的基本原理，驗證了此方法對于減小不確定因素影響，提高檢測精度的作用。 -
As far as the system observation for accuracy evaluation of carrier rocket is concerned, there may exist different types of observed data and priors. heterogeneous information means that the different information describing the different characteristics of the same object. since all of the information is relevant to the same object, the fusion is possible. it is a key problem that how to fuse the heterogeneous information to obtain the better evaluation result. therefore, the different heterogeneous information and data is thoroughly studied, moreover, the mathematical description for information fusion of different parameter priors and data is constructed in this paper. based on their relationship between different parameters, indirect prior and observation data is transformed into prior in impact point observation space, which is fused with original prior by weight determined by maximum entropy rule to obtain the mixed posterior distribution. therefore, the test results can be given by combining posterior distribution and impact error observed data. then its application on evaluating guidance systematic error is elaborated as it applies trajectory tracking data, test value of coefficients of guidance instrumentation systematic error, impact point observation data and prior. especially, the advantage of this method lies in its application in case that guidance instrumentation systematic error may not be computed precisely. finally a detailed example on evaluation of carrier rocket is given to verify the theory
為充分利用運載火箭觀測中的不同觀測空間和過程的信息來進行精度評估，針對該背景建立了異質先驗融合的數學描述.研究了飛行試驗中不同觀測空間和過程的異質先驗信息和數據，基於不同觀測過程的解析關系，將間接過程的先驗和觀測數據算出的后驗分佈轉換成落點觀測空間上的先驗，與原落點的先驗進行了最大熵加權融合，得到混合后驗分佈，從而結合落點觀測數據給出評定結果.在無法解算出精確的制導工具誤差系數的情況下，這種方法充分利用了彈道跟蹤數據、工具誤差系數的地面測試先驗值、落點先驗及落點數據，穩健性更好，準確性更高 -
Firstly, influence factors of generalization of neural network are presented in this thesis, in order to improve neural network ’ s generalization ability and dynamic knowledge acquirement adaptive ability, a structure auto - adaptive neural network new model based on genetic algorithm is proposed to optimize structure parameter of nn including hidden layer nodes, training epochs, initial weights, and so on ; secondly, through establishing integrating neural network and introducing data fusion technique, the integrality and precision of acquired knowledge is greatly improved. then aiming at the incompleteness and uncertainty problem consisting in the process of knowledge acquirement, knowledge acquirement method based on rough sets is explored to fulfill the rule extraction for intelligent diagnosis expert system, by completing missing value data and eliminating unnecessary attributes, discretization of continuous attribute, reducing redundancy, extracting rules in this thesis. finally, rough sets theory and neural network are combined to form rnn ( rough neural network ) model for acquiring knowledge, in which rough sets theory is employed to carry out some preprocessing and neural network is acted as one role of dynamic knowledge acquirement, and rnn can improve the speed and quality of knowledge acquirement greatly
本文首先討論了影響神經網路的泛化能力的因素，提出了一種新的結構自適應神經網路學習演算法，在新方法中，採用了遺傳演算法對神經網路的結構參數（隱層節點數、訓練精度、初始權值）進行優化，大大提高了神經網路的泛化能力和知識動態獲取自適應能力;其次，構造集成神經網路，引入數據融合演算法，實現了基於集成神經網路的融合診斷，有效地提高了知識獲取的全面性、完善性及精度;然後，針對知識獲取過程中所存在的不確定性、不完備性等問題，探討了運用粗糙集理論的知識獲取方法，通過缺損數據補齊、連續數據的離散、沖突消除、冗餘信息約簡、知識規則抽取等一系列的演算法實現了智能診斷的知識規則獲取;最後，將粗糙集理論與神經網路相結合，研究了粗糙集-神經網路的知識獲取方法。 -
When the survey data sampled by multiple sensors are adopted to estimate the parameter under the interference of measurement noise, the multisensor data fusion demands timeliness and spatiality
摘要當採用分佈在不同空間位置上的多傳感器觀測值對測量噪聲干擾下的參數進行融合估計時，數據融合存在時間性與空間性。 -
The technique allows the existence of various motion states, track many motion states correctly, including the normal motion states, target disruption, target fusion, entering the scene, and departing the scene based on the paper theories, a traffic parameter detection system is setup
以本文理論為基礎，運用智能交通參數檢測技術開發了一個用於流量檢測的軟體系統，能統計車輛速度，車隊隊長，平均車速統計車流量等參數，並且能完成牌號識別等多種功能。 -
The important research is about the theory and methods of the cluster analysis in view of statistical theory, the theory and methods of fuzzy cluster analysis, the fkn " s structure and the fkn ' s study algorithm ( fkn, fuzzy kohonen network ) - the organic fusion of the fuzzy c - means algorithm and self - organized feature map neural network. the paper proposes the ifkn ( improved fkn ) on the basis of the hard classification idea and the soft classification idea, then carries on the cluster analysis of the artificial synthetic control chart time series through matlab program and tt ? cluster result matches the cluster result of the famous dataengine " s software of the intellectual data analysis and data mining from german mit company. finally, the paper discusses the applying of the cluster analysis to the control process, which can be widely applied to the pattern recognition of the parameter " s changing trend during the control process and the image partition processing, and utilizes the ifkn to recognize the thermotechnical parameter " s changing trend based on the engineering of clinker sintering rotary kiln automatic control system of guizhou " s aluminium factory, through which good effect is obtained
數據挖掘技術在商業領域中已廣泛使用，然而在工業過程式控制制中的應用卻極少，本文正是在這種背景下，對數據挖掘中的聚類分析方法及其在工業過程式控制制中的應用研究作了償試，重點研究了基於統計理論的聚類分析理論和方法，模糊聚類分析理論和方法及模糊kohonen網路（ fkn ）的結構與學習演算法，即模糊c ? ?均值演算法與自組織特徵映射神經網路（ kohonen網路）的有機融合，並根據硬分類思想及軟分類思想提出了改進的模糊kohonen網路（ ifkn ） ，通過matlab編程對人工合成控制時序圖數據集進行聚類分析，其聚類效果與當今廣泛使用的數掘挖掘軟體平臺，德國mit公司著名的dataengine智能數據分析和數掘挖掘軟體的聚類效果相當，最後，論述了聚類分析在控制中的應用，它可以用於過程式控制制中的參數變化趨勢的模式識別及圖象分割處理等具體應用中，並以貴州鋁廠熟料燒結回轉窯自動控制系統為工程背景，利用ifkn識別其熱工參量變化趨勢，取得了較理想的效果。 -
In order to improve the measurement precision, based on the parameter estimation theory, a spatial - temporal estimation algorithm for multisensor data fusion is presented
為了提高測量精度，基於參數估計理論，提出一種多傳感器數據時空融合演算法。 -
So the measure technology of gas - solid two - phase flow yet belongs to the research field urgently waiting for developing based on the research achievements obtained by our task team recently, this dissertation further employed information process technology into parameter measurement of gas - solid two - phase flow, where the neural network technology was used to recognize the flow regime and the data fusion technology to measure the flow velocity of solid - phase particles, and the simulation research was worked
因此，氣固兩相流檢測技術尚屬一個急待發展的研究領域。本文在課題研究小組近年來取得的研究成果基礎上，進一步將信息處理技術引用到氣固兩相流參數檢測中。文中主要應用神經網路和數據融合這兩種方法分別進行氣固兩相流流型的辨識及固相顆粒流速的檢測，並進行了模擬研究。 -
This paper studies a design method of decentralized signal detection system which consists of adaptive fuzzied local - detectors and a data fusion rule of on - line self - learning weights. the local - detectors for inaccurate signal parameters are modeled by means of fuzzy sets which can be adapted to change of the inaccurate signal parameteres. the data fusion center where the optimal declsion rules are used as objective function can learn the local decision weights on - line. the robustness of the fuzzied local - detectors and the adaptability of the self - learned fusion rule make it true that the detection performance of the decentralized detection system is improved under uncertainty and this system can also process the decentralized signal detection with a unknown parameter of unknown distribution or non - random unknown parameter
本文研究了一種由局部自適應模糊檢測器和在線自學習融合演算法所構成的分散式信號檢測系統的設計方法.由模糊集對不精確信號參數的局部檢測器進行建模，該模糊模型可自適應不精確信號參數的變化.融合中心以最佳融合規則作為目標函數在線自學習局部判決的權重.局部模糊檢測器的魯棒性和自學習融合演算法的自適應性使該分散式檢測系統在不確定環境下的檢測性能得到提高.也使該系統能夠處理未知分佈的未知參數以及非隨機未知參數的分散式信號檢測 -
In the parameter - based fusion methods, we analyze the applicability of the bayes theory and neyman - pearson rule when they are applied to identity verification systems ; we compare global and local parameter in bayes fusion system ; we further propose weighted method, and apply it to bayes - and neyman - pearson - based identity verification system, and get a more higher verification result
在有參數的融合方法中，分析了bayes理論和neyman - pearson準則在融合時的適用范圍；針對bayes融合系統參數的選取問題，我們分別進行了全局參數和局部參數的融合實驗；並提出了加權思想，將其用於bayes理論和neyman - pearson準則的身份識別融合系統，得到了較好的鑒別效果。 -
And then the paper describes em - mrf iterative algorithm and its realization for the parameter estimation in unsupervised image classiifcation process. the em - mrf - based image classification strategy is introduced into multisensor feature - level image fusion, distributed and centric based fusion methods are proposed. finally, simulated results through sythetic and real remotely sensed image illustrate the effectiveness and advantage of the proposed methods
針對遙感圖像非監督分類中的參數估計問題，重點討論了em - mrf迭代演算法的原理和實現，並將em - mrf迭代演算法引入到多源遙感圖像融合的過程中，提出了兩種分別基於集中式融合模型和分散式融合模型的圖像融合方法。 -
Essentially, multi - sensor information fusion is just an issue of parameter estimation, or an issue of algorithm
多傳感器信息融合技術從本質上說就是一個參數估計問題，或者說是一個演算法問題。 -
We consider multisensor statistical interval estimation fusion for the purpose of estimation of a parameter
在多傳感器分散式估計融合方面，我們考慮了對參數的多傳感器區間估計融合。
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