期刊文献+
共找到2篇文章
< 1 >
每页显示 20 50 100
MATHEMATICAL MODELING AND BIFURCATION ANALYSIS FOR A BIOLOGICAL MECHANISM OF CANCER DRUG RESISTANCE
1
作者 包康博 梁桂珍 +1 位作者 田天海 张兴安 《Acta Mathematica Scientia》 SCIE CSCD 2024年第3期1165-1188,共24页
Drug resistance is one of the most intractable issues in targeted therapy for cancer diseases.It has also been demonstrated to be related to cancer heterogeneity,which promotes the emergence of treatment-refractory ca... Drug resistance is one of the most intractable issues in targeted therapy for cancer diseases.It has also been demonstrated to be related to cancer heterogeneity,which promotes the emergence of treatment-refractory cancer cell populations.Focusing on how cancer cells develop resistance during the encounter with targeted drugs and the immune system,we propose a mathematical model for studying the dynamics of drug resistance in a conjoint heterogeneous tumor-immune setting.We analyze the local geometric properties of the equilibria of the model.Numerical simulations show that the selectively targeted removal of sensitive cancer cells may cause the initially heterogeneous population to become a more resistant population.Moreover,the decline of immune recruitment is a stronger determinant of cancer escape from immune surveillance or targeted therapy than the decay in immune predation strength.Sensitivity analysis of model parameters provides insight into the roles of the immune system combined with targeted therapy in determining treatment outcomes. 展开更多
关键词 mathematical model drug resistance cancer heterogeneity immune system targeted therapy
下载PDF
基于分解–优化–集成学习方法的电价预测 被引量:18
2
作者 蒋锋 何佳琪 +1 位作者 曾志刚 田天海 《中国科学:信息科学》 CSCD 北大核心 2018年第10期1300-1315,共16页
随着新一轮电力市场改革的持续推进,电价作为反映市场运营状况的重要指标,准确预测电价能够帮助电力市场博弈方进行风险规避,达到经济收益最大化.本文提出了一种新的基于分解–优化–集成(decomposition-optimization-ensemble, DOE)的... 随着新一轮电力市场改革的持续推进,电价作为反映市场运营状况的重要指标,准确预测电价能够帮助电力市场博弈方进行风险规避,达到经济收益最大化.本文提出了一种新的基于分解–优化–集成(decomposition-optimization-ensemble, DOE)的混合学习模型来预测电价,首先利用快速集成经验模态分解方法将波动性较大的电价数据分解成一系列本征模态函数和一个残差序列.然后对鲸鱼算法从收敛速度、精度和算法搜索能力3个方面进行改进,再利用改进的鲸鱼算法优化径向基神经网络的扩展系数,采用优化后的径向基神经网络模型对分解得到的本征模态函数和残差序列进行预测.最后对分解后的子序列预测值进行集成,得到电价的预测值.为了验证混合学习模型的预测效果,本文对美国宾夕法尼亚–新泽西–马里兰电力市场的电价进行中长期和短期预测.实证结果显示DOE混合学习模型在水平精度和方向精度上均能获得很好的效果. 展开更多
关键词 电价预测 快速集成经验模态分解 改进的鲸鱼算法 径向基神经网络 方向精度
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部