The growth of farmer's incomes is cIoseIy reIated to rural finance. The research analyzed the dynamic reIationship of rural financial deveIopment, efficiency and farmer's incomes based on VAR modeI, and the resuIts ...The growth of farmer's incomes is cIoseIy reIated to rural finance. The research analyzed the dynamic reIationship of rural financial deveIopment, efficiency and farmer's incomes based on VAR modeI, and the resuIts indicated that the ex-pansion of rural finance wouId stimuIate farmer's incomes in a Iong term, and the growth of rural financial efficiency significantIy improves farmer's incomes in a short term, instead of a Iong term. Hence, it is necessary to introduce more credit funds and social funds to rural areas, deepen rural financial system reform and acceIerate use rate of Ioan capital and enhance guidance for farmers and township enterprises in use of Ioan capitals.展开更多
针对基于支持向量机的电力系统短期负荷预测算法中,预测模型的精度和泛化能力易受样本集中输入变量的影响,利用主成分分析方法能有效地消除变量之间共线性的特点,通过提取样本集的主成分完成数据预处理,有效地压缩样本集的维数。根据Eas...针对基于支持向量机的电力系统短期负荷预测算法中,预测模型的精度和泛化能力易受样本集中输入变量的影响,利用主成分分析方法能有效地消除变量之间共线性的特点,通过提取样本集的主成分完成数据预处理,有效地压缩样本集的维数。根据East-Slovakia Power Distribution Company提供的电网运行数据进行了预测计算,证明此方法与标准支持向量机算法相比,可以降低样本集的维数,提高负荷预测精度。展开更多
基金Supported by Hubei Provincial Department of Education Science and Technology Research Project(Q20131207)~~
文摘The growth of farmer's incomes is cIoseIy reIated to rural finance. The research analyzed the dynamic reIationship of rural financial deveIopment, efficiency and farmer's incomes based on VAR modeI, and the resuIts indicated that the ex-pansion of rural finance wouId stimuIate farmer's incomes in a Iong term, and the growth of rural financial efficiency significantIy improves farmer's incomes in a short term, instead of a Iong term. Hence, it is necessary to introduce more credit funds and social funds to rural areas, deepen rural financial system reform and acceIerate use rate of Ioan capital and enhance guidance for farmers and township enterprises in use of Ioan capitals.
文摘针对基于支持向量机的电力系统短期负荷预测算法中,预测模型的精度和泛化能力易受样本集中输入变量的影响,利用主成分分析方法能有效地消除变量之间共线性的特点,通过提取样本集的主成分完成数据预处理,有效地压缩样本集的维数。根据East-Slovakia Power Distribution Company提供的电网运行数据进行了预测计算,证明此方法与标准支持向量机算法相比,可以降低样本集的维数,提高负荷预测精度。