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KNN-WG The KNN-WG is a tool for lead time simulation of daily weather data based on Knn affordable

The KNN-WG is a tool for lead time simulation of daily weather data based on Knn affordable
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O in short: the user can load seven different variables for example Tmin Tmax Rain Srad ETo WSPD and Humidity. Then the user can load the input data and run KNN-WG.well known

Easy software similar to KNN-WG, about:
Weather Generator, K nearest neighbors and Non Parametric



KNN-WG 1.0
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Description:
The K-nearest neighbors (K-NN) is an analogous approach. This method has its origin as a non-parametric statistical pattern recognition procedure to distinguish between different patterns according to a selection criterion. Through this method, researchers can generate future data. In other words, the KNN is a technique that conditionally resamples the values from the observed record based on the conditional relationship specied. The KNN is most simple approach.

The most promising non-parametric technique for generating weather data is the K-nearest neighbor (K-NN) resampling approach. The K-NN method is based on recognizing a similar pattern of target le within the historical observed weather data which could be used as reduction of the target year (Young, 1994; Yates, 2003; Eum et al., 2010). The target year is the initial seed of data which, together with the historical data, are required as

input les for running the model. This method relies on the assumption that the actual weather data observed during the target year could be a replication of weather recorded in the past. The k-NN technique does not use any predened mathematical functions to estimate a target variable.

Actually, the algorithm of this method typically involves selecting a specied number of days similar in characteristics to the day of interest. One of these days is randomly resampled to represent the weather of the next day in the simulation period. The nearest neighbor approach involves simultaneous sampling of the weather variables, such as precipitation and temperature. The sampling is carried out from the observed data, with replacement.

The K-NN method is widely used in agriculture (Bannayan and Hoogenboom, 2009), forestry (Lopez et al., 2001) and hydrology (Clark et al., 2004; Yates et al., 2003).

 
best Generates 7 Weather Data and Compares Them
  
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Type: Commercial
File size: 57649 Kb
Date: 01/01/2017
Homepage
Install support: Install and Uninstall
OS: Win2000, WinXP, Win7 x32, Win7 x64, Windows 8, Windows 10, WinServer, WinOther, WinVista, WinVista x64
System requirements:
Language: English
Recent changes in this New Release:


 
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