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2.boundchecker 能找到泄漏发生的地方unlocker  删除不让删除的文件

基于遗传算法的新的异构分布式系统任务调度算法研究(Matlab代码实现)内容概要:本文档围绕基于遗传算法的异构分布式系统任务调度算法展开研究,重点介绍了一种结合遗传算法的新颖优化方法,并通过Matlab代码实现验证其在复杂调度问题中的有效性。文中还涵盖了多种智能优化算法在生产调度、经济调度、车间调度、无人机路径规划、微电网优化等领域的应用案例,展示了从理论建模到仿真实现的完整流程。此外,文档系统梳理了智能优化、机器学习、路径规划、电力系统管理等多个科研方向的技术体系与实际应用场景,强调“借力”工具与创新思维在科研中的重要性。; 适合人群:具备一定Matlab编程基础,从事智能优化、自动化、电力系统、控制工程等相关领域研究的研究生及科研人员,尤其适合正在开展调度优化、路径规划或算法改进类课题的研究者; 使用场景及目标:①学习遗传算法及其他智能优化算法(如粒子群、蜣螂优化、NSGA等)在任务调度中的设计与实现;②掌握Matlab/Simulink在科研仿真中的综合应用;③获取多领域(如微电网、无人机、车间调度)的算法复现与创新思路; 阅读建议:建议按目录顺序系统浏览,重点关注算法原理与代码实现的对应关系,结合提供的网盘资源下载完整代码进行调试与复现,同时注重从已有案例中提炼可迁移的科研方法与创新路径。
pmsampsize(type = "s", csrsquared = 0.3, parameters = 10, shrinkage = 0.95, rate = 0.02, + timepoint = 10, meanfup = 5) NB: Assuming 0.05 acceptable difference in apparent & adjusted R-squared NB: Assuming 0.05 margin of error in estimation of overall risk at time point = 10 NB: Events per Predictor Parameter (EPP) assumes overall event rate = 0.02 Samp_size Shrinkage Parameter CS_Rsq Max_Rsq Nag_Rsq EPP Criteria 1 528 0.950 10 0.3 0.483 0.621 5.28 Criteria 2 343 0.925 10 0.3 0.483 0.621 3.43 Criteria 3 * 528 0.950 10 0.3 0.483 0.621 5.28 Final SS 528 0.950 10 0.3 0.483 0.621 5.28 Minimum sample size required for new model development based on user inputs = 528, corresponding to 2640 person-time** of follow-up, with 53 outcome events assuming an overall event rate = 0.02 and therefore an EPP = 5.28 * 95% CI for overall risk = (0.136, 0.224), for true value of 0.181 and sample size n = 528 **where time is in the units mean follow-up time was specified in > pmsampsize(type = "s", csrsquared = 0.15, parameters = 10, shrinkage = 0.95, rate = 0.02, + timepoint = 10, meanfup = 5) NB: Assuming 0.05 acceptable difference in apparent & adjusted R-squared NB: Assuming 0.05 margin of error in estimation of overall risk at time point = 10 NB: Events per Predictor Parameter (EPP) assumes overall event rate = 0.02 Samp_size Shrinkage Parameter CS_Rsq Max_Rsq Nag_Rsq EPP Criteria 1 1164 0.950 10 0.15 0.483 0.31 11.64 Criteria 2 377 0.861 10 0.15 0.483 0.31 3.77 Criteria 3 * 1164 0.950 10 0.15 0.483 0.31 11.64 Final SS 1164 0.950 10 0.15 0.483 0.31 11.64 Minimum sample size required for new model development based on user inputs = 1164, corresponding to 5820 person-time** of follow-up, with 117 outcome events assuming an overall event rate = 0.02 and therefore an EPP = 11.64 * 95% CI for overall risk = (0.151, 0.21), for true value of 0.181 and sample size n = 1164 **where time is in the units mean follow-up time was specified in(解读,为什么CS_R²从0.3设置为0.15时,样本量增加了????)
09-12
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