The cycle scanner framework provides background on the algorithms. The algorithm has a filter for detrending in the data preprocessing. The detrending assures that the data trends in time series for successful cycle research.
Extraction of linear trends in time series
In the business cycle indicator HP filters are the standard method of filters used for removing long-run movements like trends and decompose macroeconomic time series data into trend components.

The HP filter helps to remove the trend component from the data series delivers the pure underlying cyclic behaviours.

Cycle Toolbox Application
Business cycles are the basic fundamental concepts in macroeconomics. The cycle toolbox application has integrated data sources for data sets. It is mainly used for global stocks, crypto-currencies, and forex data.
There is a Java program used to implement the cycle scanner algorithm. Cycle detection is an algorithm problem used to find a cycle in a sequence of iterated function values. The java program is compiled and run in a windows system for a successful scanning algorithm.
Cycle detection Algorithm
The cycle detection algorithm is an algorithm that uses two pointers that are moving at different speeds. Many applications use this algorithm for their output.

The cycle detection algorithm is used in Linked List to determine whether the linked list has a complete cycle or not. To make this algorithm work under good condition, all you have to do is just keep the two pointers in the head node.

At each iteration, it starts to move one of the pointers and observe the operation. Eventually, only two cases exist in the algorithm

1. The pointer will reach the null of the linked lists, which means it returns null, i.e. no cycle in it.

2. The two pointers meet each other; it means there is a cycle that exists.