local extremum 中文意思是什麼
local extremum
解釋
局部極值-
The reason why we integrate them is that k - means algorithm is a mountain climbing method, which is easy convergent to local extremum, and sensitive to the original condition, but its convergent speed is relatively fast, and that genetic algorithm is a random searching method, which can find the whole extremum in a rather big probability, and non - sensitive to the original condition, but its convergent speed relatively slow
之所以將：二者結合在一起，是回為k一均值演算法是一種爬山法，容易收斂到岡部極小值，對初始條件較敏感，但收斂速度較快，而遺傳演算法是卞dl隨機搜索演算法，能夠以較大概率找到全局最憂解，且對們始條件個敏感，但收斂速度較慢。 -
The bp neural network has the ability to solve many practical problems because of its strong mapping. however, it has slow convergence rate and is prone to fall into local extremum
Bp神經網路具有很強的映射能力，可以解決許多實際問題，但同時還存在著收斂速度慢，易陷於局部極小的缺點。 -
This paper discusses the statistical rule of maximum corrosive pit depth and determination method of extremum estimation for local corrosion depth, and presents a practical example of calculation
文章討論了管道最深點蝕孔深度的統計規律以及局部腐蝕深度最大極值估計值的確定方法，並給出了實際算例。 -
In the course of searching the optimum solution, it can accept a value make objective function good, but also a bad one. in this way it will avoid falling into a local extremum and get a global optimum value
而且在搜索的過程中，不僅接受使目標函數變好的解，而且還能以一定的概率接受壞解，這樣將盡量避免陷入局部極值解而達到全局最優解。 -
Aimed at the ga ' s disadvantages : weak local optimization, easiness of falling into local extremum, this thesis presents an improved ga which introduces two operators " local search " and " adaptively avoid entropy decreasing "
針對遺傳演算法局部搜索能力差及容易陷入局部極值點的缺陷，提出一種改進的遺傳演算法，引入了「局部搜索?均值方差閥值」和「自適應防止熵減」兩個運算元。 -
For standard genetic algorithm has the defects of slowly converging and easily falling into local extremum ， the author designed and realized the adaptive multi - population parallel genetic algorithm ( ampga ) to solve the reliability allocation problem of large and complicated software systems. finally, we experimented on the comity center subsystem, delivery center subsystem and system management subsystem of the project : the jiangsu province postal logistics information system
針對標準遺傳演算法存在著收斂速度慢、易陷入局部極小值等缺點，本文設計並實現了自適應多種群并行遺傳演算法（ ampga ） ，來解決大型、復雜軟體系統的可靠性分配問題。最後，對「江蘇省郵政物流信息系統開發」項目中的「禮儀中心子系統」 、 「遞送中心子系統」及「系統管理子系統」進行了可靠性分配實驗。 -
Many experiments are implemented, the results of which demonstrate the algorithm ’ s efficiency and stability. it overcomes disadvantages of the bp neural network which has slow convergence rate and is prone to fall into local extremum
模擬和實驗結果充分表明了該演算法的有效性和穩定性，克服了bp神經網路收斂速度慢和易陷入局部極小的問題，為混沌時間序列預測運用開辟了新的應用領域。 -
The radar target identification based on artificial neural network is the protagonist of the chapter 4. bp network and wavelet network are used to classified the emulational radar targets. with the powerful capability of non - linnear identification of bp neural network, its ’ born limitations such as local extremum, slow convergence etc. can be reformed by the wavelet network, which is a network with a wavelet function embedded into the node of a bp network
研究了基於人工神經網路模型的雷達目標hrrp識別方法。 bp人工神經網路強大的非線性處理能力，在解決復雜目標分類識別時有優勢;小波神經網路針對bp網路的不足，將bp網路和小波變換相結合，在網路收斂、網路初始化方面彌補了bp網路的部分缺陷，其識別性能和抗噪性能與bp網路相比有所提高。 -
According to feature that goal function has more than one local extremum in displacement back analysis for underground engineering, a new means of displacement back analysis for underground engineering has been established through adopting fem and self - adaptation idea on the basis of the improvement of the determining method of control parameters, such as initial temperature and number of state choice and annealing strategy, moreover, the relevant analytic software is developed
摘要本文針對地下工程圍巖位移反分析問題的目標函數存在多個局部極值的特點，在對模擬退火演算法進程中控制參數，即初始溫度、每一溫度下的狀態選取次數和退火策略的確定方法加以改進的基礎上，引進有限元分析手段和自適應的思想，建立了基於改進模擬退火演算法的位移反分析方法，並開發了相應的分析程序。
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