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相关概念视频

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

38
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

354
Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
354
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

93
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
93
Decision Making: Traditional Method01:14

Decision Making: Traditional Method

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The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
4.0K
Decision Making: P-value Method01:09

Decision Making: P-value Method

5.2K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
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Machines: Problem Solving II01:30

Machines: Problem Solving II

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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
279

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一个代的贪的算法,用于解决一个多目标分布式组装灵活的工作车间调度问题与模糊的处理时间.

Fuqing Zhao, Yuqing Du, Changxue Zhuang

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    本研究引入了一种新的算法,用于灵活的工厂调度问题,处理时间不确定. 拟议的方法有效地减少了生产时间和能源消耗,优于现有的方法.

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    科学领域:

    • 运营研究 运营研究
    • 制造业 工程 制造工程
    • 人工智能的人工智能

    背景情况:

    • 由于固有的不确定性,决定性处理时间对于现实的制造是不够的.
    • 灵活的工作车间调度问题 (FJSP) 是复杂的,特别是分布式组装和不确定的参数.

    研究的目的:

    • 为了解决多目标分布式组装灵活的工作车间安排问题,使用类型-2模糊时间 (DAT2FFJSP).
    • 在生产计划中优化制造范围和总能耗.

    主要方法:

    • 开发了一个混合整数线性编程模型.
    • 提出了一个基于人口的代贪算法 (PBIGA),与Q学习机制集成.
    • 关键功能包括混合初始化,多种搜索运营商,运营商选择的Q学习和节能策略.

    主要成果:

    • 与最先进的算法相比,PBIGA表现出卓越的性能.
    • 在30个实例上进行了广泛的实验,验证了拟议组件和整体算法的有效性.

    结论:

    • 开发的PBIGA有效地处理了灵活的工作室安排中的不确定性.
    • 该方法成功地优化了产品范围和能源消耗,在该领域取得了重大进展.