1) multi-step prediction 多步预测1. Adaptively controlling algorithm based on neural network of multi-step prediction was proposed for the industrial processes. 针对工业过程的特点和控制要求,提出一种基于多步预测的神经网络自适应控制算法。2. Due to the autocorrelation of the direct prediction errors,...
In the end, a method to do multi-step prediction with artificial neural networks, MTPF is proposed to conduct the time series prediction, create time series model and forecast time series. The proposed method is applied for a shipping price index time series prediction. Results show that this ...
et al. An active object detection model with multi-step prediction based on deep q-learning network and innovative training algorithm. Appl Intell 55, 185 (2025). https://doi.org/10.1007/s10489-024-05993-y Download citation Accepted30 September 2024 Published19 December 2024 DOIhttps://doi....
只是这篇论文是预测接下来几个时刻的流量(Multi-step)。而为什么作者要提出Multi-step demand prediction呢? 作者认为,Multi-step demand prediction不仅能够体现流量变化的趋势,而且能够表达处全局的变化,从而能够避免因临时突发的需求变化而导致整体预测失误。什么意思呢? 比如 t 1 , t 2 , t 3 , t 4 t_1,t...
3) multi-step dynamic prediction 动态多步预报4) Kalman multi-step predictor Kalman多步预报器5) multistep forecast 多步状态预报6) Multi-step precipitation forecasting 多步降水预报补充资料:短期天气预报(见天气预报和天气图预报) 短期天气预报(见天气预报和天气图预报) u。。,,,:‘,anq,yubao短期...
摘要: This paper develops an agent-based modeling approa 关键词: Experienced travel time Travel time prediction Agent-based model Agent interaction rule Probe data 年份: 2016 收藏 引用 批量引用 报错 分享 全部来源 求助全文 国家科技图书文献中心 (权威机构) 万方 相似文献 参考文献...
The framework structure is detailed in Section “Framework overview: Uncertainty prediction under limited data (UPLD)”, along with key mathematical formulae and assumptions made. Section “Framework implementation and results” applies the framework to two use cases: US SAR cost uncertainty data and...
To make use of the uncertain information and subjective knowledge in complex nonlinear systems, we propose a multi-step prediction method for time series of evidence based on the phase space reconstruction theory and evidence inference theory. In the reconstruction of phase space for time series of...
For time series data collected from WSN environmental monitoring applications, a novel multi-step prediction method based on Gaussian process model was proposed. The method could make prediction for future environmental monitoring data. Kernel functions were used to describe data properties in the ...
simplified.Meanwhile,the dynamic recurrent algorithm is adopted to predict the molten iron silicon content in multi-step,which has strong adaptability.The method was used in a prediction experi- ment with the data collected from a blast furnace of Baosteel on-site.With the prediction error range ...