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Beneduzzi, H.M

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Authors

Gavioli, A

Souza, E.G

Bazzi, C.L

Betzek, N.M

Schenatto, K

Beneduzzi, H.M

Schenatto, K

de Souza, E.G

Bazzi, C.L

Gavioli, A

Betzek, N.M

Beneduzzi, H.M

Topics

Precision Nutrient Management

Decision Support Systems in Precision Agriculture

Type

Oral

Poster

Year

2016

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Filter results2 paper(s) found.
1. Delineation of Site-specific Management Zones Using Spatial Principal Components and Cluster Analysis The delineation of site-specific management zones (MZs) can enable economic use of precision agriculture for more producers. In this process, many variables, including chemical and physical (besides yield data) variables, can be used. After selecting variables, a cluster algorithm like fuzzy c-means is usually applied to define the classes. Selection of variables comprise a difficult issue in cluster analysis because these will often influence cluster determination. The goal of this study was... A. Gavioli, E.G. Souza, C.L. Bazzi, N.M. Betzek, K. Schenatto, H. Beneduzzi Download paper
2. Data Normalization Methods for Definition of Management Zones The use of management zones is considered a viable economic alternative for the management of crops due to low cost of adoption as well as economic and environmental benefits. The decision whether or not to normalize the attributes before the grouping process (independent of use) is a problem of methodology, because the attributes have different metric size units, and may influence the result of the clustering process. Thus, the aim of this study was to use a Fuzzy C-Means algorithm to evaluate... K. Schenatto, E.G. De souza, C.L. Bazzi, A. Gavioli, N.M. Betzek, H.M. Beneduzzi Download paper

Filter results2 paper(s) found.

1. Delineation of Site-specific Management Zones Using Spatial Principal Components and Cluster Analysis

The delineation of site-specific management zones (MZs) can enable economic use of precision agriculture for more producers. In this process, many variables, including chemical and physical (besides yield data) variables, can be used. After selecting variables, a cluster algorithm like fuzzy c-means is usually applied to define the classes. Selection of variables comprise a difficult issue in cluster analysis because these will often influence cluster determination. The goal of this study was... A. Gavioli, E.G. Souza, C.L. Bazzi, N.M. Betzek, K. Schenatto, H. Beneduzzi

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2. Data Normalization Methods for Definition of Management Zones

The use of management zones is considered a viable economic alternative for the management of crops due to low cost of adoption as well as economic and environmental benefits. The decision whether or not to normalize the attributes before the grouping process (independent of use) is a problem of methodology, because the attributes have different metric size units, and may influence the result of the clustering process. Thus, the aim of this study was to use a Fuzzy C-Means algorithm to evaluate... K. Schenatto, E.G. De souza, C.L. Bazzi, A. Gavioli, N.M. Betzek, H.M. Beneduzzi

Download paper