precision attribute 中文意思是什麼
precision attribute
解釋
精度屬性-
In some projects charged by our lab such as national 863 project - " crop planting management components based on weather analyse ", anhui provincial 95 key project - " agricultural meteorology disaster evaluation system base on gis in anhui province " and the project " small coal mine security management and decision system based on gis in anhui province ", this paper combines the theory and arithmetic of rough set with gis and data mining in idss, investiges the application of rough set theory to precision analysis of attribute data and logical operation in gis, analyzes the logical operation based on rough set ( logical union, logical intersection, logical complement, mixed logical operation etc. ), so that it can give a method y to research the gis attribute data and the uncertainty of attribute data after superposition operator, so as to express the roughness and illegibility of attribute data more accurately
在完成試驗室所承擔的國家863項目「基於氣象分析的農作物種植管理軟構件」 、省95攻關項目「基於gis的安徽省重大農業氣象災害測評系統」和「基於gis的安徽省小煤礦安全管理決策系統」等項目中，將粗糙集理論和演算法與gis 、智能決策系統中的知識發現等相結合，對粗糙集理論在gis屬性數據和邏輯運算精度分析中的應用情況進行了研究，分析了基於粗集的gis邏輯運算（邏輯並、邏輯交、邏輯補、混合邏輯等） ，從而為研究gis屬性數據及其疊加運算后屬性數據的不確定性提供了一種方法，能比較準確地表達屬性數據的模糊性和粗糙性。 -
Experimental result and practice shows it is possible using seismic information forecasting subtle trap. integrated using geology % log, drilling data, specia ! seismic processing technique -, interpretation technique, including high precision horizon calibration technique, 3d seismic visualizing interpretation, seismic coherence analyze, attribute analyze, logging - constrained inversion, time frequency analyze, ann forecasting technique, subtle trap object is identified and interpreted. finally, advantage object of subtle trap in this area is determined
綜合地質、測井和鉆井資料，依靠先進的地震特殊處理和解釋新技術，包括高精度的層位標定技術、三維可視化解釋技術、地震相干技術、屬性分析技術、測井約束反演技術、時頻分析技術、多參數油藏檢測技術和神經網路預測等技術，對隱蔽油氣藏目標進行識別、解釋和成藏研究，最後指出工區內隱蔽油氣藏的有利目標。 -
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。 -
Results showed that, attribute data obtained by this way avoided deficiency of polygon overlap way, as a result, the logistical consistency between map data and attribute data reached over 90 % on average. database pivot precision was 0. 18mm, data quantity during manipulation was decreased greatly, data treatment was more convenient, computation velocity was boosted greatly. workload of map and table pretreatment and edition was mitigated on large scale, spatial data precision was increase
研究表明：用該方法獲得的屬性數據，避免了多邊形疊加方法的不足之處，能使圖形數據和屬性數據邏輯一致性平均達到90以上，數據庫點位精度達到0 . 18mm ，且操作中圖層數據量大大減小，數據處理更為方便，運算速度大為提高；減輕了圖表預處理和編輯的工作量，使空間數據精度提高。 -
( 3 ) resolving the symbolization check and presentation of the map attribute data based on the visual variants and visualization technology ; automatically checking the range of the value of the attributes and logic consistency and integrity based on the attribute template technology. the users can evaluate, improve and optimize the precision of the attributes according to the checking results and print the map of the checking results as well as the resulting map consistent with the specification requirements
（ 3 ）採用基於視覺變量、可視化技術解決了地圖屬性數據的符號化檢查和表示；用屬性模板技術，對屬性的值域、邏輯一致性、完整性進行自動檢查；用戶可根據檢查結果對屬性精度進行評價、改進和優化。 -
In view of requires of precision agriculture and specialties of farmers, it tentatively use visual c + + to devise a software without gis platform. the software is developed to process the fused data and use grid graph to express field information. in the software, users can transmit the fused data to computer via serial communication between gps receiver and computer, and users can choose longitude latitude and attribute information from the fused data, and store these data in a data file
在本論文中，通過對國內外獲取、表達基礎農田信息的研究現狀的分析，基於gps接收機獲取的定位信息與常規檢測儀表信息的融合，提出了gps接收機與常規檢測儀表結合，快速實時地獲取農田空間位置信息和屬性信息的方法；針對精細農業實踐的需要和農村用戶的特點，試驗研究脫離gis平臺以圖形的形式表達農田信息，應用visualc + +編程語言從底層開發具有gis功能的應用軟體。
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