目標跟蹤校正 的英文怎麼說
中文拼音 [mùbiāogēnzōngjiàozhēng]
目標跟蹤校正
英文
target track correction- 目 : Ⅰ名詞1 （眼睛） eye 2 （大項中再分的小項） item 3 [生物學] （把同一綱的生物按彼此相似的特徵分為幾...
- 標 : Ⅰ名詞1 [書面語] （樹梢） treetop; the tip of a tree2 （枝節或表面） symptom; outside appearance; ...
- 跟 : Ⅰ名詞（腳的後部或鞋襪 的後部） heel Ⅱ動詞1 （在後面緊接著行動） follow 2 （指嫁給某人） be marrie...
- 蹤 : 名詞（腳印; 蹤跡） footprint; track; trace; trail
- 校 : 校名詞1. （學校） school 2. （校官） field officer3. （姓氏） a surname
- 正 : 正名詞（正月） the first month of the lunar year; the first moon
- 目標 : 1. （對象） target; objective 2. （目的） goal; aim; destination
- 跟蹤 : follow the tracks of; tail after; following; follow up tracing; track; tracking; trail; lock on; ...
- 校正 : check; correction; adjust; revise; proofread and correct; rectify; calibrate; make true; master c...
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This paper, based on normalizing well logging data while drilling and correcting depth into true vertical depth and calculating reservoir parameters and etc, combining the practical ease of mobei oilfield, extracted logging and geological pattern characteristic of target oil - gas formation and geosteering mark formation, and used bp neural network and regressive analysis to create predicting mode of geosteering parameter to build relevant contrast curve ; adopted geometry geosteering method to fix on die drilling direction of bit upper and declination, the position in reservoir, to judge the real drilling case. all finely solved the problem to follow the geological target while drilling for three horizontal well these methods improve the drilling horizontal well ability by using the techniques to follow the geological target while drilling, and then it is convenient and practicable
本文在開展隨鉆測井資料的標準化和斜井校正及儲層參數解釋與含流體性質判釋等工作的基礎上，結合研究工區莫北油田的實際情況，提取了目標油（氣）層和導向標志層的測井地質模式特徵，並採用bp神經網路法和回歸分析法建立了地質導向參數的預測模型、構造了相應的對比曲線；採用幾何導向法確定鉆頭上下傾鉆進方向及其在目標層的位置，以判斷實際鉆進地層情況，很好地解決了研究工區三口水平井的隨鉆跟蹤地質目標的問題。Iterative learning control is an important branch of intelligent control. the basic method of traditional ilc is to achieve control input based on the previous input and the pid - revised error of previous output. after some iteration, perfect tracking can be achieved over a fixed time interval
迭代學習控制理論是智能控制的一個重要分支，傳統迭代學習的基本方法是，基於上次迭代時的輸入信息和輸出誤差的pid校正項，獲得本次迭代的控制輸入，經過若干次迭代，以期達到在給定的時間區間上實現被控對象以較高精度跟蹤一給定目標軌線。Later on, after elaborating the disadvantages of the old methods in detecting and recognizing moving objects, a series of corresponding approaches are proposed, such as grid scan, local tracking bug and dynamic window in object tracing to reduce the huge data needed to be processed, maximum and minimum for selecting a proper segmentation threshold and improved conversion from rgb model to hsv and so on to decrease the influence of inhomogeneous lighting and the color noise, a bilinear interpolation in each quadrant to eliminate the bad effect on the recognition precise because of the distortions of the camera. after that, much emphasis is given on application study in pattern recognition with a feed - forward neural network. both the basic bp algorithm and improved bp algorithm in the study process are described in detail, and the later is used to quicken convergence speed and improve validity of the network
然後，分析和闡明了傳統的運動目標檢測方法的不足，並在此基礎上結合研究中的實際實驗環境，提出了一系列解決方法，包括針對降低龐大數據量而提出的網格掃描、局部「跟蟲」追蹤和動態窗口掃描等目標檢測方法，針對實驗環境中光照不均和顏色干擾提出基於人機交互的最大最小值閾值選取方法和引入改進的rgb模型到hsv模型的轉換方法，為消除圖像畸變對識別精度的惡劣影響而採用的通過控制點進行雙線性插值進行畸變校正的方法；緊接著，概述了神經網路的發展歷史和幾種常用神經網路模型的特點，重點研究了前饋型神經網路在模式識別中的應用問題，詳細闡述了基本的bp演算法和學習過程中bp演算法的改進，從而使網路收斂速度更快，解決問題更有效，並在此基礎上，設計了一個基於bp神經網路的運動目標識別系統，給出了實驗結果。
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