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智能混合预测
相关语句
  intelligent hybrid prediction
     NEW INTELLIGENT HYBRID PREDICTION MODEL FOR CONDITION TREND OF ELECTROMECHANICAL EQUIPMENT
     一种新的机电设备状态趋势智能混合预测模型
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  “智能混合预测”译为未确定词的双语例句
     Due to the fluctuation and complexity of electromechanical equipment operation condition affected by various factors, it is difficult to use a single prediction method to accurately describe its moving trend. So a new hybrid prediction model based on improved grey system, support vector machine (SVM) and neuro-fuzzy system is proposed.
     针对机电设备运行状态受多因素影响,变化趋势复杂,难以用单一预测方法进行有效预测的问题,提出一种新的基于改进灰色系统—支持向量机—神经模糊系统的智能混合预测模型。
短句来源
     Based on the generation mechanism and anfractuosity of machine tool thermal errors,a new(hybrid) prediction model,synthesizing the advantages of time series analysis and grey system theory,was(applied) to the trend prediction of thermal errors in a spot NC turning center.
     基于机床热变形误差的产生机理及其表现形式的复杂性,综合时序分析方法建模和灰色系统理论建模的优点,研究了一种智能混合预测模型.
短句来源
  相似匹配句对
     A Review of Intelligent Hybrid Systems
     智能混合系统
短句来源
     The Analyse of Hybrid Intelligence System
     浅析混合智能系统
短句来源
     PREDICTIVE INTELLIGENT CONTROL OF THE COLD STORAGE
     冷库的预测智能控制
短句来源
     Hybrid Position/Force Control Based on Intelligent Prediction
     基于智能预测的力/位混合控制方法
短句来源
     Future tendeney of intelligent control is discused.
     预测智能控制的发展。
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Due to the fluctuation and complexity of electromechanical equipment operation condition affected by various factors, it is difficult to use a single prediction method to accurately describe its moving trend. So a new hybrid prediction model based on improved grey system, support vector machine (SVM) and neuro-fuzzy system is proposed. In this model, the fluctuation of the data sequence is weakened by the improved grey system, the SVM can deal with small samples and neuro-fuzzy system is capable of processing...

Due to the fluctuation and complexity of electromechanical equipment operation condition affected by various factors, it is difficult to use a single prediction method to accurately describe its moving trend. So a new hybrid prediction model based on improved grey system, support vector machine (SVM) and neuro-fuzzy system is proposed. In this model, the fluctuation of the data sequence is weakened by the improved grey system, the SVM can deal with small samples and neuro-fuzzy system is capable of processing non-linear fuzzy information. The hybrid prediction model combines these advantages and its prediction result is an adaptive combination of these single method's via improved genetic algorithms. This model was applied to the trend prediction of a fluctuant and complicated benchmark data and a vibration trend signal from machine sets. Testing results show that the prediction performance of this model outperforms any one of the three prediction methods.

针对机电设备运行状态受多因素影响,变化趋势复杂,难以用单一预测方法进行有效预测的问题,提出一种新的基于改进灰色系统—支持向量机—神经模糊系统的智能混合预测模型。该模型首先利用改进灰色系统弱化数据序列波动性、支持向量机处理小样本和模糊神经系统处理非线性模糊信息的优点,分别进行趋势预测,然后通过改进遗传算法对这三者的预测结果进行自适应加权组合。将该模型应用于信号随机波动性较强、趋势变化复杂的标准算例和某机组振动趋势的预测中,研究结果表明,该模型的预测性能均优于上述三种单一预测方法。

Based on the generation mechanism and anfractuosity of machine tool thermal errors,a new(hybrid) prediction model,synthesizing the advantages of time series analysis and grey system theory,was(applied) to the trend prediction of thermal errors in a spot NC turning center.The testing results show that the prediction performance of hybrid prediction model outperforms any one of the two single prediction methods.The prediction precision of the hybrid prediction model for machine tool thermal errors was the highest...

Based on the generation mechanism and anfractuosity of machine tool thermal errors,a new(hybrid) prediction model,synthesizing the advantages of time series analysis and grey system theory,was(applied) to the trend prediction of thermal errors in a spot NC turning center.The testing results show that the prediction performance of hybrid prediction model outperforms any one of the two single prediction methods.The prediction precision of the hybrid prediction model for machine tool thermal errors was the highest among three kinds of prediction models.Therefore,hybrid prediction model can highly improve(machine) tool's processing precision and make it more effective for real-time compensation of NC thermal error.

基于机床热变形误差的产生机理及其表现形式的复杂性,综合时序分析方法建模和灰色系统理论建模的优点,研究了一种智能混合预测模型.将该模型应用于一台数控车削加工中心进行热误差趋势预测,以进行机床热误差补偿研究.结果表明,混合预测模型预测精度高于时序分析模型和灰色系统模型,其优异的预测性能可使数控机床进行实时补偿更加有效,从而大大提高机床热误差的补偿精度.

 
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