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Impact of genetic algorithm on time series data

机译:遗传算法对时间序列数据的影响

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Efficient planning of hospital resources and services are the prime concern of any hospital administration in terms of patient care. Predicting Average Length of Stay of patient may help in strategic decision making and effective planning of hospital resources. If the length of stay is decided corresponding to disease treatment patient can plan their hospital days priorly in an efficient manner. In this research work, we have taken Alabama University historical hospital data set of the year 2008 and 2009 month-wise for the forecasting analysis using genetic crossover method. We have evaluated results in terms of Average Forecasting Error Rate (AFER) and Mean Square Error (MSE) values. Aim of this research is to forecast values using genetic approach. The calculated AFER value is compared with existing soft computing models which are evaluated over same data set.
机译:就患者护理而言,有效规划医院资源和服务是任何医院管理部门的首要关注。预测患者的平均住院时间可能有助于战略决策和有效规划医院资源。如果确定住院时间长短与疾病治疗相对应,则患者可以事先以有效的方式计划其住院天数。在这项研究工作中,我们采用了阿拉巴马大学2008年和2009年每月的历史医院数据集,以进行基于遗传交叉法的预测分析。我们根据平均预测错误率(AFER)和均方误差(MSE)值评估了结果。这项研究的目的是使用遗传方法预测价值。将计算出的AFER值与在相同数据集上评估的现有软计算模型进行比较。

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