【摘 要】
：
针对风速具有强随机性而难以准确预测的问题,引入二型模糊逻辑以减小预测误差.基于反向传播-奇异值分解混合迭代算法,建立了区间二型模糊模型用于风速的短期时间序列预测,首
【机 构】
：
西南交通大学电气工程学院,吉林大学珠海学院计算机科学与技术系
论文部分内容阅读
针对风速具有强随机性而难以准确预测的问题,引入二型模糊逻辑以减小预测误差.基于反向传播-奇异值分解混合迭代算法,建立了区间二型模糊模型用于风速的短期时间序列预测,首先通过反向传播算法调节模型输入及规则前、后件集合的参数,然后利用奇异值分解法优选模型规则.同时,基于反向传播算法建立了一型模糊模型和区间二型模糊模型,将其预测结果作为检验性能的基准.仿真结果表明,基于混合迭代算法的区间二型模糊模型能有效精简系统规则并提高预测精度,具有一定的实用价值.
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