基于云的智能物联网空气污染预测模型,使用单变时间序列分析.
1Department of Computer Science, Jamia Millia Islamia, New Delhi, India.
概括
一个新的贝叶斯优化混合时间序列 (BO-HyTS) 模型使用物联网 (IoT) 数据准确预测空气质量指数 (AQI). 这种人工智能方法增强了公共卫生和环境管理策略.
科学领域:
- 环境科学与工程环境科学与工程
- 计算机科学和人工智能 人工智能
- 数据科学和分析数据科学和分析
背景情况:
- 空气污染对全球健康和环境构成重大风险,工业和车辆排放加剧了这种风险.
- 预测空气质量指数 (AQI) 对公共卫生至关重要,但传统模型难以应对物联网 (IoT) 数据的数量.
- 人工智能 (AI) 和时间序列模型为准确的AQI预测提供了潜在的解决方案.
研究的目的:
- 评估基于物联网云的模型在不同气象条件下预测AQI的有效性.
- 引入和评估一个新的贝叶斯优化-混合时间序列 (BO-HyTS) 模型用于空气污染预测.
- 将拟议的BO-HyTS模型的性能与各种经典,机器学习和深度学习预测方法进行比较.
主要方法:
- 开发了一种新的BO-HyTS模型,将季节自回归集成移动平均 (SARIMA) 和长短期记忆 (LSTM) 结合起来,通过贝叶斯优化进行优化.
- 利用物联网 (IoT) 设备在云环境中实时收集空气质量数据.
- 采用五个统计评估指标和一个非参数的弗里德曼测试,用于严格的模型性能评估.
主要成果:
- 拟议的BO-HyTS模型表现出卓越的性能,平均平方误差 (MSE) 为632.200,根平均平方误差 (RMSE) 为25.14,中位数绝对误差 (Med AE) 为19.11,最大误差为51.52,平均绝对误差 (MAE) 为20.49.
- BO-HyTS有效地捕获了时间序列空气污染数据的线性和非线性特征,提高了预测准确度.
- 统计学意义测试证实了BO-HyTS在竞争中的AQI预测模型中表现优越.
结论:
- 该BO-HyTS模型提供了一个高度准确和高效的解决方案,用于使用物联网数据进行AQI预测.
- 研究结果为印度各州未来的AQI模式提供了宝贵的见解,为公共卫生政策提供了信息.
- 拟议的模型可以帮助政府和组织积极主动地进行环境管理和政策制定.
关键词:
空气质量指数是指空气质量指数.云计算是一种云计算.物联网的物联网,就是物联网.这是LSTM的LSTM.非参数统计学测试试验拟议的BO-HyTS模型时间序列分析分析时间序列分析三倍指数级光滑是一种指数级光滑.更多相关视频
相关概念视频
Steps in Outbreak Investigation
155
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
155
Regression Analysis
5.8K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
5.8K
Precipitation Processes
494
The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
494
Variation of Atmospheric Pressure
2.3K
Change in atmospheric pressure with height is particularly interesting. The decrease in atmospheric pressure with increasing altitude is due to the decreasing gravitational force per unit area as we move away from the surface of the earth.
Assuming the air temperature is constant at a given altitude and that the ideal gas law of thermodynamics describes the atmosphere to a good approximation, one can find the variation of atmospheric pressure with height.
Let p(y) be the atmospheric pressure at...
Assuming the air temperature is constant at a given altitude and that the ideal gas law of thermodynamics describes the atmosphere to a good approximation, one can find the variation of atmospheric pressure with height.
Let p(y) be the atmospheric pressure at...
2.3K
Precipitation and Co-precipitation
1.9K
Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...
1.9K
Random Error
934
Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
934


