algorithm rule 中文意思是什麼
algorithm rule
解釋
演算法規則-
Optimized association rules are permitted to contain uninstantiated attributes. the optimization procedure is to determine the instantiations such that some measures of the roles are maximized. this paper tries to maximize interest to find more interesting rules. on the other hand, the approach permits the optimized association rule to contain uninstantiated numeric attributes in both the antecedence and the consequence. a naive algorithm of finding such optimized rules can be got by a straightforward extension of the algorithm for only one numeric attribute. unfortunately, that results in a poor performance. a heuristic algorithm that finds the approximate optimal rules is proposed to improve the performance. the experiments with the synthetic data sets show the advantages of interest over confidence on finding interesting rules with two attributes. the experiments with real data set show the approximate linear scalability and good accuracy of the algorithm
優化關聯規則允許在規則中包含未初始化的屬性.優化過程就是確定對這些屬性進行初始化，使得某些度量最大化.最大化興趣度因子用來發現更加有趣的規則;另一方面，允許優化規則在前提和結果中各包含一個未初始化的數值屬性.對那些處理一個數值屬性的演算法進行直接的擴展，可以得到一個發現這種優化規則的簡單演算法.然而這種方法的性能很差，因此，為了改善性能，提出一種啟發式方法，它發現的是近似最優的規則.在人造數據集上的實驗結果表明，當優化規則包含兩個數值屬性時，優化興趣度因子得到的規則比優化可信度得到的規則更有趣.在真實數據集上的實驗結果表明，該演算法具有近似線性的可擴展性和較好的精度 -
At the same time, astringency testifying was presented. algorithm a was obtained after modifying quasi - newton iterative learning rule with feedback
並對帶反饋的機械手類牛頓學習控制律（演算法a ）做了簡化，參考了tae - yongkue ， kwangheenamandjins -
The algorithm has many advantages, such as simple discriminative rule, minimum error, incremental operation, etc
將中點演算法運用於三次樣條曲線的光柵顯示，實現了誤差最小及迭代增量計算的要求。 -
Research of efferent data mining algorithm for assocoation rule
高效關聯規則數據挖掘演算法研究 -
We have implemented a series of algorithm, which includes rule adornment, logic program adornment and factorization, magic transformation, factorizing magic transformation. the platform is characteristic of transplant, expansion
處理器中實現了本文中用到的一系列演算法，其中包括：規則修飾、邏輯程序的修飾、魔集轉換、邏輯程序的分解、分解的魔集轉換。 -
According to the least twin multiplication to calculating the sensitivity index in several water production functions. thus, the writer obtains the fitted the value of the sensitivity index and the varied rule. at the same time, the writer puts forward a new method named rag a ( real coding based accelerating genetic algorithm ) and combines raga with dpsa to calculating the best irrigation system under the non - sufficient irrigation of well irrigation rice in sanjiang plain
根據《隨機水文學》理論中的時間序列分析法，建立了適合三江平原井灌水稻需水量預報的非平穩時序隨機模型；通過分析降雨隨機特性，選定季節性時序隨機模型，建立了適合三江平原井灌水稻降雨預報的月平均降雨模型；根據最小二乘法，計算出幾種常用水分生產函數中的敏感指數及敏感系數，進而得到三江平原適宜採用的水分生產函數漠型及模型中敏感指數的變化規律；本文提出遺傳動態規劃法（ raga ? dp ） ，即採用改進的基於實數編碼的加速遺傳演算法（ realcodingbasedacceleratinggeneticalgorithm ，簡稱raga ）與動態規劃法（ dpsa ）相結合，推求非充分灌溉條件下三江平原井灌水稻的最優灌溉制度。 -
On the simplex algorithm with largest improvement rule
關于使用最大改進規則的單純形演算法 -
On single path condition, the multi - user detection algorithm is derived on the basis of the minimal square rule and the ml rule. a space - time multi - user detection structure and an adaptive method on cdma system are proposed
在單徑情況下，基於最小均方誤差原則和最大似然原則，提出了一種多用戶檢測演算法和一種空時二維多用戶檢測器的結構。 -
In the implementation of data classifier, we describe extraction and management of conceptual hierarchy for data, also design an automatic extraction algorithm for numeric data. in this section, we still provide the two algorithms of concept - based attribute - oriented induction and evaluating classification scheme and the visualization of classification rule. finally, the data classifier is tested in databas the results show that it is practical and its performance meet the requirement of designing
然後，在數據分類器的實現中，論述了數據的概念層次提取和管理，並對數值型數據給出了一個自動提取概念層次演算法；同時給出了基於面向屬性歸納的分類演算法、分類模式的評價演算法和分類規則的可視化方法。 -
To solve the problem of rule learning time cost for traditional transformation based part of speech tagging method of latin mongolian, a dynamic partition algorithm was presented
針對傳統基於轉換的詞性標注方法中規則學習速度過慢的問題提出了一種對訓練語料庫進行動態劃分的演算法。 -
Fpga and dvb standard are introduced firstly, dvb - c standard and composition of its system are analyzed completely, development of modulator structure and dvb - c digital modulator composition are presented, more over, analysis of respective modular are given. then, principle of dvb - c digital modulator system are presented, they are error control technique 、 mqam 、 nyquist rule and root raised cosine filter 、 window design method for fir filter 、 multi - rate signal processing ( integer interpolating, conversion of fractional sampling, equal conversion of net structure, polyphase structure for filter, poly - phase structure for interpolator, multi - stage implementation of samplying conversion ) 、 distrubited algorithm 、 cic filter 、 dds 、 cordic algorithm
接著，專門利用一個章節闡述了dvb - c前端調制系統原理，他們了差錯控制技術、多進制調制（ mqam ） 、 nyquist準則與平方根升餘弦濾波器、有限沖擊響應濾波器的窗函數設計法、多抽樣率信號處理包括（整數倍內插原理、分數倍抽樣率轉換、網路結構的等效結構、濾波器的多相表示、內插器的多相表示、抽樣率轉換的多級實現） 、分散式演算法、 cic濾波器、直接數字頻率合成（ dds ） 、 cordic演算法。 -
An algorithm of quantitative association rule based on cloud models
基於雲模型的關聯規則的提取演算法 -
Neural network control is an important mode of intelligent control, and it is widely used in branches of control science, first, the architecture and the learning rule ( error back propagation algorithm ) of multiplayered neural network which is widely used in control system are presentedo especially, the paper refers to the architecture of diagonal recurrent neural network and its learning algorithm - - - - - recurrent prediction error algorithm because of its faster convergence with low computing costo next, before introducing the neural network control to the double close loop dc driver system, the controllers of current and velocity loop are designed using engineering design approach after analysis of the system, simulation models of the system are created
神經網路控制是智能控制的重要方式之一，它廣泛應用於自動控制學科各個領域。本文首先敘述了控制系統中常用的多層前饋網路結構及演算法（ bp演算法） ，特別提及了能夠較好描述系統動態性能的對角遞歸神經網路和在用遞推預報誤差演算法訓練drnn時取得了較快的收斂速度。其次，應用工程方法分析設計了tf - 1350糖分離機的電流、轉速雙閉環直流調速系統的控制器，作為引入神經網路控制的設計基礎，並建立了系統的模擬模型。 -
A novel dynamic evolutionary clustering algorithm ( deca ) is proposed in this paper to overcome the shortcomings of fuzzy modeling method based on general clustering algorithms that fuzzy rule number should be determined beforehand. deca searches for the optimal cluster number by using the improved genetic techniques to optimize string lengths of chromosomes ; at the same time, the convergence of clustering center parameters is expedited with the help of fuzzy c - means ( fcm ) algorithm. moreover, by introducing memory function and vaccine inoculation mechanism of immune system, at the same time, deca can converge to the optimal solution rapidly and stably. the proper fuzzy rule number and exact premise parameters are obtained simultaneously when using this efficient deca to identify fuzzy models. the effectiveness of the proposed fuzzy modeling method based on deca is demonstrated by simulation examples, and the accurate non - linear fuzzy models can be obtained when the method is applied to the thermal processes
針對模糊聚類演算法不適應復雜環境的問題，提出了一種新的動態進化聚類演算法，克服了傳統模糊聚類建模演算法須事先確定規則數的缺陷.通過改進的遺傳策略來優化染色體長度，實現對聚類個數進行全局尋優;利用fcm演算法加快聚類中心參數的收斂;並引入免疫系統的記憶功能和疫苗接種機理，使演算法能快速穩定地收斂到最優解.利用這種高效的動態聚類演算法辨識模糊模型，可同時得到合適的模糊規則數和準確的前提參數，將其應用於控制過程可獲得高精度的非線性模糊模型 -
The content of this paper is arranged as foll owing : chapter 1 introduces the concept of credit, credit risk and credit assessment, as well as the history and development of credit assessment ; chapter 2 introduces the history of ai technology, and the background of expert system and neural network. characters and disadvantages of expert system and neural network are presented respectively and the necessity of combining expert system and neural network is lightened ; chapter 3 shows the process of dealing with sample data, including the treatment of exceptional data and factor analysis, and puts forward the concrete framework of the mixed - expert credit assessment system ; chapter 4 introduces concept of object - oriented technology, and constructs object model and functional model after analyzing the whole system. it also illustrates the implementation of concrete classes by an example of rule class and the inference algorithm in the form of pseudocode ; chapter 5 introduces the structure of the whole system, the major functional models and their interfaces, and the characteristic of the system is also generalized ; chapter 6 summarizes the whole work, and points out the remaining deficiencies as well as the prospective of this method
本文具體內容安排如下：第一章介紹了信用、信用風險、信用評價的概念，回顧了信用評價的歷史、發展和現狀，並綜合各種信用評價模型，指出這些模型各自的優缺點：第二章簡單描述了人工智慧技術，著重介紹有關專家系統與神經網路的基礎知識，通過總結它們的優缺點，指出結合專家系統與神經網路構造混合型專家系統的必要性；本章還介紹了神經網路子模塊的概念，提出了混合型專家系統的一般框架與設計步驟：第三章對樣本數據進行處理，包括異常數據的剔除、因子分析等，提出了信用評價混合型專家系統的具體框架結構，介紹了系統知識庫的主要部分、基於優先級的正向推理機制的流程、以及基於事實的自動解釋機制的具體實現方法；第四章介紹了面向對象技術，進而採用面向對象對信用評價系統進行分析，建立了對象模型和功能模型，並在此基礎上，採用c + +語言以規則類為例說明系統中具體類的實現，用偽代碼的形式描述了推理的演算法；第五章描述了整個系統的結構，對系統主要功能模塊和界面進行了介紹，並總結系統的特點；第六章總結了全文，指出本文所構造系統存在的不足以及對將來的展望。 -
Moreover, this article also made a preliminary discussion on the combination of neural network theory and the differential game guidance law. the bp model and rbf model and their corresponding learning algorithm were employed to design the neural network guiding rule based on the differential game guidance law
另外，本文還將神經網路理論與微分對策制導律相結合作了初步的探討，並結合具體的bp網路和rbf網路及其相應的學習演算法設計出了基於神經網路技術的微分對策制導律。 -
Based on many references, a evaluating function is proposed with performance index of hall call waiting time ( hwt ), people number in a car, energy consuming. the statistic approximation algorithm for hwt is introduced, based on the analysis of elevator traffic state, the calculation of traveling distance and stop number is explained in detail in the thesis. according to the characteristics of the elevator, a group of elevator teaching signals are constructed, by which the weight coefficients are trained according to the widrow - hoff rule
本文在借鑒了大量的文獻基礎上，提出以平均等候時間、轎廂人數、能源消耗為性能指標的評價函數；詳細介紹了乘客待梯時間hwt的統計近似演算法；基於對電梯交通狀況的分析，對停層次數和運行距離這兩個重要參數的計算進行了詳盡的介紹；依據電梯運行特性參數，構造一組電梯運行教師信號，並採用神經網路的widrow - hoff學習規則訓練權系數。 -
In rsdm, binary patterns are replaced by real - valued patterns, accordingly avoiding the coding process ; the outer learning rule is replaced by regression rule, therefore the model has not only the ability of pattern recognition but the ability of function approximation. the prearrangement of the address array bases on the distribution of patterns. if the distribution of patterns is uniform. then the address array is prearranged randomly, otherwise predisposed with the theory of genetic algorithm and the pruneing measure so as to indicate the distribution of patterns and improve the network performance. non - linear function approximation, time - series prediction and handwritten numeral recognition show that the modified model is effective and feasible
在rsdm中，以實值模式代替二值模式，避免了實值到二值的編碼過程：以回歸學習規則代替外積法，使該模型在具有識別能力的同時具有了對函數的逼近能力；地址矩陣的預置根據樣本的分佈採取不同方法，若樣本均勻分佈，則隨機預置，否則利用遺傳演算法的原理和消減措施來預置地址矩陣，使之反映樣本的分佈，改善網路的性能。 -
Therefore, a study of incremental data mining algorithm is urgently needed. incremental data mining only modifies rule sets when database is updated, which takes advantage of previous calculation result and prevents knowledge extraction from the very beginning
把增量演算法與數據庫的更新結合在一起，漸增地進行知識的更新、修正和加強先前業已發現的知識，這樣可以不必重新挖掘全部數據。 -
In this approach, remaining operating time ( rot ) is divided into two types : one is relative rot, and the other is absolute rot. a new dispatching rule, i. e. the maximum relative rot of part is priority, is presented. this scheduling algorithm is proven to be effective by examples and theory analysis
論文重點研究了在單件、小批量生產方式下，基於啟發式的作業車間調度問題，提出了優先分配啟發式演算法的一種新的優先分配規則，即相對剩餘加工時間最大的概念，並從理論分析和軟體實現兩個方面驗證了該演算法的有效性。
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