reduction rule 中文意思是什麼
reduction rule
解釋
簡約規則-
This paper recurred to the basic theory of rough set of data mining and under the direction of the frame of intelligent decision, the main theories include i ) the different methods of data mining on the base of rough set are used to deal with typical decision system namely consistent decision system and inconsistent decision system in order to carry through data reduction and rule distilment ; ii ) in the environment of dynamic increment database, the methods of data reduction to deal with the original data and increment data are discussed in the consistent and inconsistent decision system ; iii ) the method of data mining of rough set is analysized to treat with the attributes with priority ; iv ) on the base of basic rough set theory, the data analysis methods of amalgamation of rough set theory ; v ) and also the pre - disposal method to database is analysize
本文從系統工程進行決策分析的角度出發，藉助數據挖掘技術中粗糙集的基本理論，在智能決策框架的指導下，研究了基於數據挖掘的智能決策理論及方法。主要理論包括：如何利用粗糙集對典型的決策系統即相容性決策系統和不相容性決策系統運用不同的數據挖掘方法進行有效的數據約減和規則提取；在增量動態的數據庫環境下討論了在典型決策系統中對原始數據和增量數據進行數據約減的方法；分析了帶有優先權屬性的粗糙集數據挖掘方法；以基本粗糙集為基礎探討了粗糙集擴展模型的數據分析方法；研究了粗糙集數據預處理方法。 -
Value reduction is rule reduction in essence
值約簡即是對規則的約簡。 -
While putting rough set theory into practice, this thesis pays attention to setting - up the proper data structure. in order to improve the data utilization ratio and promote rule quality, this thesis puts forward the method of " divide equally and examine each other this thesis bring forward the method of dynamic reduce to overcome data noise and confirm the best reduction finally with the help of rosetta tool software we apply the above concept and method to reality, and succeeded in obtaining the optimum rule for the expert system of production scheduling in daye iron ore mine, wuhan iron and steel company
由於標準粗糙集模型對數據噪音高度敏感以及工程應用中數據噪音引入的不可避免性，標準粗糙集模型在實際應用中存在一系列問題，為克服數據噪音以及規則泛化的需要，本文採用變精度模型，由此模型引入近似約簡方法。本文在將粗糙集理論及變精度粗糙集模型應用於實際的同時，注重研究了適當數據結構的建立。為提高數據利用率，提升規則生成的質量，提出了平分互測規則集泛化能力考核方法。 -
The results of simulation show that the rule will help reduction of the positioning error
模擬結果表明，依據選星策略選擇定位衛星能夠明顯減小定位誤差。 -
The rough set theory ( rst ), which was introduced by z. pawlak in 1982, is a tool to deal with vagueness and uncertainty. its main idea is inducing decision or classification rule through knowledge reduction by keeping the classify ability
粗糙集理論是波蘭數學家z . pawlak於1982年提出的一種處理不確定和不精確數據的理論，其主要思想是在保持分類能力不變的前提下，通過知識約簡，導出問題的決策或分類規則。 -
Based on these theoretical work, we design and implement a prototype kdd system which is divided into four sections : preprocessing section, data reduction section, rule induction and decision algorithm section
在理論工作的基礎上，我們設計並實現了一個基於粗集的數據約簡的原型系統。 -
So the inhomogeneity of total solar radiation series has little impact on the a, b coefficient spatial distribution rule as a whole. however, it is necessary to carry out the homogeneity test and reduction concerned with the time series change. several stations " long time series of solar radiation are established
訂正前後a 、 b系數的空間分佈變化不明顯，說明用訂正前的總輻射資料，得到的a 、 b系數的空間變化規律是可靠的，總輻射資料的不均一對a 、 b系數的空間分佈特徵影響不大。 -
Generally, the research of knowledge discovery is based on relational database, database reduction algorithm based on relational database directly obtains core of database, attributes reduction and rule reduction by operator in relational database. it is a simple and effective. essentially, rough relational database model in this paper, which extending classical rough sets model, is a multi - valued information system
知識發現研究的實施對象多為關系數據庫，基於關系數據庫操作的數據庫約簡演算法利用關系數據庫的操作運算元直接對數據庫進行求核、屬性約簡和規則約簡，該方法充分發揮數據庫操作的簡便高效性，使得數據庫約簡演算法簡單易實現。 -
Research of association rule mining almost concentrated on the optimality of frequent sets generation and the reduction of scanning times of transaction sets
在數據挖掘的各分支中，關聯規則挖掘的研究最為深入和廣泛。 -
In order to diagnose complex system, because there exists too many characteristic parameters, the problems, such as over - large scale of neural network, unduly long train time, and redundant rules in expert system ' s rule base, will result in the reduction of whole system ' s practical performance. then the rough set theory that received focus attention in recent years is led into the internal - combustion engine fault diagnosis work. the application of this theory in the attributable optimization of fault diagnosis characteristic parameters is explored
考慮到在對復雜系統進行診斷時，由於特徵參數過多而造成神經網路規模過大、訓練時間過長以及專家系統規則庫存在規則冗餘等問題，最終導致整個系統實用性能的降低，為此將粗糙集理論引入了內燃機故障診斷工作，對其在故障診斷特徵參數屬性優化中的運用進行了探索。
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