不可微函数

Bush连续不可微函数的分形性质

The fractal properties of Bush continuous and non-differentiable function

一个七进位制小数定义的连续不可微函数的Hausdorff维数

Hausdorff Dimension of A Continuous and Non-differentiable Function Defined by Septenary Decimal

BP算法因收敛速度慢、易于陷入局部极小值等缺点，使得对于较大的搜索空间、多峰值和不可微函数常常不能搜索到全局极小点，这些制约了BP网络在各个领域中的应用。

BP algorithm has weaknesses such as slow convergent speed and easy getting into local minimum , insurable to find global extreme value point for multi-modal and non-differential function in larger searching zone , which restrict neural network 's application in every field .

他首先讨论了其连续不可微函数的例子。

He first discussed his example of a continuous nondifferentiable function .

一个五进位制小数下的连续不可微函数及推广

An continuous and non-differentiable function defined by quinary decimal and extending

不可微函数单调性的充要条件

Necessary and sufficient conditions for monotonicity of nondifferentiable functions

不可微函数的广义中值定理

Extended Mean Value Theorems for Nondifferentiable Functions

作为最优化理论中的一个重要性质&迫近次梯度对于研究不可微函数的微分性质有着重要的作用。

As a fundamental theory of optimization theory , the proximal subgradient is a crucial point for the differentiation property in non-differentiable functions .

该方法的基本思想是将模型辨识问题转化为非线性不可微函数优化问题，然后采用进化策略获得该优化问题的解。

The basic idea of the method is that the model identification is changed into a nonlinear non-differentiable function optimization problem , and the evolution strategy is then adopted to solve the optimization problem .

一种求解不可微非线性函数的全局解的混合遗传算法

A Hybrid Genetic Algorithm for Global Solution of Indifferentiable Nonlinear Function

关于不可微凸函数的高阶算法

A high order algorithm of nondifferentiable convex function

结合精确不可微罚函数求解非线性约束优化问题。

To solve nonlinear constraint optimization problems , COA is combined with exact non differentiable penalty function .

非光滑分析是数学上近年来得到迅速发展的专门研究非光滑（不可微）函数性质及相应算法的理论。

The nonsmooth analysis is an area on the nonsmooth ( non-differentiable ) function and its corresponding algorithms which developed rapidly in the recent years .

由于交易模型中存在离散和连续两类不同性质的变量，其目标函数为非连续、不可微的函数，本文提出了一种启发式优化算法，算法计算简单方便，收敛速度快。

Involving discrete and continuous variables , the goal function of the model is a discontinuous and differential function . A heuristic algorithm is presented to solve the model .

论文研究了上述数学模型中目标函数的基本性质，证明了目标函数是不可微的函数，利用实测数据分析了目标函数的连续性及其解的唯一性。

It has proved that the objective functions are non-differentiable functions . And it has analyzed that the objective functions are convex and continuous functions by using measured data .

提出利用混沌搜索方法结合精确不可微罚函数求解约束优化问题的新方法，并将该方法用于闪蒸过程优化。

In this paper , a new optimization method & chaos optimization combined with exact non-differentiable penalty function is proposed for solving chemical process optimization problems which are often regarded as nonlinear constraint optimization problems .

研究一种新型优化算法&混沌优化，提出加快解的收敛速度和精度新方法，并与精确不可微罚函数结合来求解非线性约束优化问题。

Chaos optimization method combined with exact nondifferentiable penalty function is proposed for solving nonlinear constraint optimization problems , and linear search is applied to speed the rate of convergence and improve the accuracy of solution .

证明了直线度误差最小区域评定法的目标函数是一维欧式空间R1中的连续、不可微的凸函数，从而证明了目标函数的全局极小值是唯一的。

It is proved that the objective function for straightness error by minimum zone evaluation is a continuous and non-differentiable and convex one defined in one-dimensional Euclidean space R. Therefore , the uniqueness of its global optimum is proved .

采用不可微精确罚函数的约束优化演化算法

Evolutionary Algorithm for Constrained Optimization Using Nondifferentiable Exact Penalty Functions

不可微伪凸函数的最优性条件

The optimality conditions of nondifferentiable pseudoconvex functions

精确罚函数又分为不可微精确罚函数和连续可微精确罚函数。

Exact penalty function is divided into nondifferentiable exact penalty function and continuously differentiable exact penalty function .

借助不可微精确罚函数把约束问题转化为单个无约束问题来处理。

Nondifferentiable exact penalty functions are used to transform a constrained optimization problem into a single unconstrained optimization problem .

这种方法通过严密的数学变换，将不可微的目标函数转化为具有单一极值点的可微函数，从而可以通过最优化方法求取目标函数的全局极小值，从而得到正确的编群结果。

This method utilizes rigorous mathematical transformation to substitute the non-differentiable objective function with a differentiable function which has single extreme point .

遗传算法适合于解决混合整数规划问题，能够有效地处理不可微的目标函数。

Genetic algorithm is an effective optimization algorithm to deal with the mixed integer programming , and it could solve the un-differential objective function effectively .

提出一种新的基于遗传算法求解非线性约束优化的方法，通过自适应的退火罚因子和不可微精确罚函数来处理约束条件，可以使算法逐渐收敛于可行的极值点。

A new optimal method based on genetic algorithms can solve nonlinear constrained optimization problems effectively , which adopted adaptive annealing penalty factors and undifferentiable accuracy penalty function .