OPTIMASI KONFIGURASI INTER DIGITAL CAPACITORS SENSOR (IDCS) MENGGUNAKAN METODE PARTICLE SWARM OPTIMIZATION

Ulfatul Khasanah
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Abstract

(x). The optimization design is adapted to the mathematical analysis of the permittivity formulation in IDCS. Based on the gradient optimization results, the value of 𝑁 ≠ 1 is obtained, meaning that N cannot be 1. This limitation is in accordance with the principle of parallel plate capacitors, where the requirements for a capacitor configuration are to consist of two plates. For the electrode length variable (L) the Boundary is obtained, namely L≠ 0. After the Boundary for the IDCS configuration is obtained, the second stage is carried out, namely optimization using PSO. The parameters used for optimization are the number of particles = 500, the maximum speed is 20, the learning factor = 2, the inertia weight is 0.8 – 1.2 and the stop condition when it reaches the minimum error. The range of results from the PSO optimization is the width of the electrode 1-3 mm, the distance between the two electrodes is 1-3mm, the number of electrodes is between 3-7, the length of the electrode is 4-7 mm. The values that often appear with the smallest error are a = 3, b = 3, N = 6, L = 5.
优化配置数字电容传感器(idcs)的孟古那坎方法粒子群优化
(x)优化设计适用于IDCS中介电常数公式的数学分析。根据梯度优化的结果,得到的结果是:N不可能是1。这一限制是根据并联板电容器的原理,其中电容器配置的要求是由两个板组成。对于电极长度变量L,得到边界,即L≠0。在得到IDCS配置的边界后,进行第二阶段,即利用粒子群算法进行优化。优化参数为粒子数= 500,最大速度为20,学习因子= 2,惯性权重为0.8 - 1.2,达到最小误差时停止条件。PSO优化得到的结果范围为电极宽度1 ~ 3mm,电极间距1 ~ 3mm,电极数量3 ~ 7个,电极长度4 ~ 7 mm。通常出现误差最小的值是a = 3, b = 3, N = 6, L = 5。
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