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Example of positive [[reinforcing loop: Bank balance and Earned interest]]

Example of positive [[reinforcing loop: Bank balance and Earned interest]]

正数的例子[[强化循环: 银行余额和已赚利息]]

正的例子[[强化循环: 银行余额和赚得的利息]]

A '''causal loop diagram''' ('''CLD''') is a [[causal diagram]] that aids in visualizing how different variables in a system are interrelated. The diagram consists of a set of [[node (computer science)|nodes]] and edges. Nodes represent the variables and edges are the links that represent a connection or a relation between the two variables. A link marked '''positive''' indicates a positive relation and a link marked negative indicates a negative relation. A positive causal link means the two nodes change in the same direction, i.e. if the node in which the link starts decreases, the other node also decreases. Similarly, if the node in which the link starts increases, the other node increases as well. A '''negative''' causal link means the two nodes change in opposite directions, i.e. if the node in which the link starts increases, the other node decreases and vice versa. <br />

A '''causal loop diagram''' ('''CLD''') is a [[causal diagram]] that aids in visualizing how different variables in a system are interrelated. The diagram consists of a set of [[node (computer science)|nodes]] and edges. Nodes represent the variables and edges are the links that represent a connection or a relation between the two variables. A link marked '''positive''' indicates a positive relation and a link marked negative indicates a negative relation. A positive causal link means the two nodes change in the same direction, i.e. if the node in which the link starts decreases, the other node also decreases. Similarly, if the node in which the link starts increases, the other node increases as well. A '''negative''' causal link means the two nodes change in opposite directions, i.e. if the node in which the link starts increases, the other node decreases and vice versa. <br />

A causal loop diagram (CLD) is a causal diagram that aids in visualizing how different variables in a system are interrelated. The diagram consists of a set of nodes and edges. Nodes represent the variables and edges are the links that represent a connection or a relation between the two variables. A link marked positive indicates a positive relation and a link marked negative indicates a negative relation. A positive causal link means the two nodes change in the same direction, i.e. if the node in which the link starts decreases, the other node also decreases. Similarly, if the node in which the link starts increases, the other node increases as well. A negative causal link means the two nodes change in opposite directions, i.e. if the node in which the link starts increases, the other node decreases and vice versa. <br />

A causal loop diagram (CLD) is a causal diagram that aids in visualizing how different variables in a system are interrelated. The diagram consists of a set of nodes and edges. Nodes represent the variables and edges are the links that represent a connection or a relation between the two variables. A link marked positive indicates a positive relation and a link marked negative indicates a negative relation. A positive causal link means the two nodes change in the same direction, i.e. if the node in which the link starts decreases, the other node also decreases. Similarly, if the node in which the link starts increases, the other node increases as well. A negative causal link means the two nodes change in opposite directions, i.e. if the node in which the link starts increases, the other node decreases and vice versa. <br />

环路图图是一种因果关系图，有助于可视化地显示一个系统中不同的变量是如何相互关联的。该图由一组节点和边组成。节点表示变量，边是表示两个变量之间的联系或关系的链接。标记为肯定的链接表示肯定关系，标记为否定的链接表示否定关系。一个积极的因果关系意味着两个节点朝着同一个方向改变，即。如果链接开始的节点减少，另一个节点也减少。类似地，如果链接开始的节点增加，其他节点也会增加。负的因果关系是指两个节点朝相反的方向变化，即。如果链接开始的节点增加，另一个节点减少，反之亦然。< br/>

环路图图是一种因果关系图，有助于可视化地显示一个系统中不同的变量是如何相互关联的。该图由一组节点和边组成。节点表示变量，边是表示两个变量之间的联系或关系的链接。标记为肯定的链接表示肯定关系，标记为否定的链接表示否定关系。一个积极的因果关系意味着两个节点朝着同一个方向改变，即。如果链接开始的节点减少，另一个节点也减少。类似地，如果链接开始的节点增加，其他节点也会增加。一个负的因果关系意味着两个节点在相反的方向改变，即。如果链接开始的节点增加，另一个节点减少，反之亦然。< br/>

Closed cycles in the diagram are very important features of the CLDs. A closed cycle is either defined as a '''reinforcing''' or '''balancing''' [[feedback]] loop. A reinforcing loop is a cycle in which the effect of a variation in any variable propagates through the loop and returns to the variable reinforcing the initial deviation i.e. if a variable increases in a reinforcing loop the effect through the cycle will return an increase to the same variable and vice versa. A balancing loop is the cycle in which the effect of a variation in any variable propagates through the loop and returns to the variable a deviation opposite to the initial one i.e. if a variable increases in a balancing loop the effect through the cycle will return a decrease to the same variable and vice versa.

Closed cycles in the diagram are very important features of the CLDs. A closed cycle is either defined as a '''reinforcing''' or '''balancing''' [[feedback]] loop. A reinforcing loop is a cycle in which the effect of a variation in any variable propagates through the loop and returns to the variable reinforcing the initial deviation i.e. if a variable increases in a reinforcing loop the effect through the cycle will return an increase to the same variable and vice versa. A balancing loop is the cycle in which the effect of a variation in any variable propagates through the loop and returns to the variable a deviation opposite to the initial one i.e. if a variable increases in a balancing loop the effect through the cycle will return a decrease to the same variable and vice versa.

Closed cycles in the diagram are very important features of the CLDs. A closed cycle is either defined as a reinforcing or balancing feedback loop. A reinforcing loop is a cycle in which the effect of a variation in any variable propagates through the loop and returns to the variable reinforcing the initial deviation i.e. if a variable increases in a reinforcing loop the effect through the cycle will return an increase to the same variable and vice versa. A balancing loop is the cycle in which the effect of a variation in any variable propagates through the loop and returns to the variable a deviation opposite to the initial one i.e. if a variable increases in a balancing loop the effect through the cycle will return a decrease to the same variable and vice versa.

Closed cycles in the diagram are very important features of the CLDs. A closed cycle is either defined as a reinforcing or balancing feedback loop. A reinforcing loop is a cycle in which the effect of a variation in any variable propagates through the loop and returns to the variable reinforcing the initial deviation i.e. if a variable increases in a reinforcing loop the effect through the cycle will return an increase to the same variable and vice versa. A balancing loop is the cycle in which the effect of a variation in any variable propagates through the loop and returns to the variable a deviation opposite to the initial one i.e. if a variable increases in a balancing loop the effect through the cycle will return a decrease to the same variable and vice versa.

图中的闭合循环是 cld 的重要特征。一个封闭的循环要么被定义为一个强化的或平衡的反馈回路。强化循环是一个循环，在这个循环中，任何变量的变化影响通过循环传播，并返回到强化初始偏差的变量。如果一个变量在一个强化循环中增加，循环中的效应将返回到相同变量的增加，反之亦然。平衡回路是一个循环，在这个循环中，任何变量的变化影响通过回路传播，并返回给变量一个与初始变量相反的偏差。如果一个变量在平衡循环中增加，那么循环中的效应将会使同一个变量减少，反之亦然。

图中的闭合循环是 cld 的重要特征。一个封闭的循环要么被定义为一个强化的或平衡的反馈回路。强化循环是一个循环，在这个循环中，任何变量的变化影响通过循环传播，并返回到强化初始偏差的变量。如果一个变量在一个强化循环中增加，循环中的效应将返回到相同变量的增加，反之亦然。平衡回路是一个循环，在这个循环中，任何变量的变化影响通过回路传播，并返回给变量一个与初始变量相反的偏差。如果一个变量在平衡循环中增加，那么循环中的效应将使同一个变量减少，反之亦然。

If a variable varies in a reinforcing loop the effect of the change reinforces the initial variation. The effect of the variation will then create another reinforcing effect. Without breaking the loop the system will be caught in a vicious cycle of circular chain reactions. For this reason, closed loops are critical features in the CLDs.

If a variable varies in a reinforcing loop the effect of the change reinforces the initial variation. The effect of the variation will then create another reinforcing effect. Without breaking the loop the system will be caught in a vicious cycle of circular chain reactions. For this reason, closed loops are critical features in the CLDs.

如果一个变量在一个强化循环中发生变化，这种变化的影响加强了初始变化。这种变化的影响会产生另一种强化效应。如果不打破循环，系统将陷入循环链反应的恶性循环。因此，闭环是 cld 中的关键特性。

如果一个变量在一个强化循环中发生变化，这种变化的影响加强了初始变化。这种变化的效果会产生另一种强化效果。如果不打破循环，系统将陷入循环链反应的恶性循环。因此，闭环是 cld 中的关键特性。

The use of nodes and arrows to construct directed graph models of cause and effect dates back to the invention of  path analysis by Sewall Wright in 1918, long before System Dynamics. Due to the limitations of genetic data, however, these early causal graphs contained no loops — they were directed acyclic graphs. The first formal use of Causal Loop Diagrams was explained by Dr. Dennis Meadows at a conference for educators (Systems Thinking & Dynamic Modeling Conference for K-12 Education in New Hampshire sponsored by Creative Learning Exchange ).

The use of nodes and arrows to construct directed graph models of cause and effect dates back to the invention of  path analysis by Sewall Wright in 1918, long before System Dynamics. Due to the limitations of genetic data, however, these early causal graphs contained no loops — they were directed acyclic graphs. The first formal use of Causal Loop Diagrams was explained by Dr. Dennis Meadows at a conference for educators (Systems Thinking & Dynamic Modeling Conference for K-12 Education in New Hampshire sponsored by Creative Learning Exchange ).

使用节点和箭头来构建因果关系的有向图模型可以追溯到1918年 Sewall Wright 发明的路径分析，远在系统动力学之前。然而，由于遗传数据的局限性，这些早期因果图不包含环路ーー它们是有向无环图。丹尼斯 · 梅多斯博士在新罕布什尔州的一次教育工作者会议(由创造性学习交流组织主办的 K-12教育系统思考与动态建模会议)上解释了因果循环图的第一次正式使用。

使用节点和箭头来构建因果关系的有向图模型可以追溯到1918年 Sewall Wright 发明的路径分析，远在系统动力学之前。然而，由于遗传数据的局限性，这些早期因果图不包含环路ーー它们是有向无环图。丹尼斯 · 梅多斯博士在新罕布什尔州的一次教育工作者会议上解释了因果循环图的第一次正式使用。

{{Main article|System Dynamics}}

{{Main article|System Dynamics}}

To determine if a causal loop is reinforcing or balancing, one can start with an assumption, e.g. "Node 1 increases" and follow the loop around. The loop is:

To determine if a causal loop is reinforcing or balancing, one can start with an assumption, e.g. "Node 1 increases" and follow the loop around. The loop is:

为了确定一个因果循环是在加强还是在平衡，我们可以从一个假设开始，例如:。“节点1增加”并循环。这个循环是:

为了确定一个因果循环是否在加强或平衡，我们可以从一个假设开始，例如:。“节点1增加”并跟随循环。这个循环是:

==Reinforcing and balancing loops==

==Reinforcing and balancing loops==