Mohamed Abd Allah El-Hadidy, Alaa Awad Alzulaibani
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引用次数: 0
摘要
本文研究了流体中一维布朗粒子的协调搜索方法。这项技术有助于清除流体中的污染物和杂质。为了找到沿 n 条不相交实线之一运动的布朗粒子,我们让 2n 个合作式纳米传感器协调工作,使每条实线包含两个传感器。所有这些纳米传感器都从原点开始搜索。由于原点左右的距离是随机的,因此每条线路上的距离序列也是随机的。由于这种不确定性,我们可以将贴现努力-回报搜索整合为距离函数中的一个参数。这样,其中一个纳米传感器与布朗粒子首次相遇时间的期望值就会降低。除了确定该预期值有限的条件外,我们还确定了该预期值的近似值。我们用一个例子来说明这一模型的实用性和应用。
A study on the existence of a cooperative search method with reducing the first metting time between one of several nano-sensors and a Brownian particle
The coordinated search method for a one-dimensional Brownian particle in the fluid is investigated in this paper. This technique helps to remove pollutants and impurities from the fluid. To locate a Brownian particle that moves along one of n disjoint real lines, we have 2n cooperative nano-sensors coordinate their efforts such that each line contains two of them. All of these nano-sensors begin their searches at the origin. Because of random travelled distances right and left of the origin, we have a random sequence of distances on each line. Due to this uncertainty, we are able to integrate the discounted effort-reward search as a parameter in the distance function. By doing this, the expected value of the first meeting time between one of the nano-sensors and a Brownian particle will be reduced. We determine the approximate value of this expected value in addition to identifying the conditions under which it is finite. We use an example to illustrate the usefulness and application of this model.