Feedforward Neural Network Estimation of a Crop Yield Response Function
نویسندگان
چکیده
منابع مشابه
Feedforward Neural Network Estimation of a Crop Yield Response Function
Feedforward networks have powerful approximation capabilities without the “explosion of parameters” problem faced by Fourier and polynomial expansions. This paper first introduces feedforward networks and describes their approximation capabilities, then we address several practical issues faced by applications of feedforward networks. First, we demonstrate networks can provide a reasonable esti...
متن کاملApplication of a Modular Feedforward Neural Network for Grade Estimation
This article presents new neural network (NN) architecture to improve its ability for grade estimation. The main aim of this study is to use a specific NN which has a simpler architecture and consequently achieve a better solution. Most of the commonly used NNs have a fully established connection among their nodes, which necessitates a multivariable objective function to be optimized. Therefore...
متن کاملVisualizing the Function Computed by a Feedforward Neural Network
A method for visualizing the function computed by a feedforward neural network is presented. It is most suitable for models with continuous inputs and a small number of outputs, where the output function is reasonably smooth, as in regression and probabilistic classification tasks. The visualization makes readily apparent the effects of each input and the way in which the functions deviate from...
متن کاملRule Extraction from Feedforward Neural Network for Function Approximation
The paper presents a method of rule-based interpretation of feedforward neural networks trained for function approximation. The rules approximate input-output mappings as well as reveal dependencies between input variables. A simple function approximation example explains the introduced concept and verifies its feasibility.
متن کاملAutomated Crop Yield Estimation for Apple Orchards
Crop yield estimation is an important task in apple orchard management. The current manual sampling-based yield estimation is time-consuming, labor-intensive and inaccurate. To deal with this challenge, we developed a computer vision-based system for automated, rapid and accurate yield estimation. The system uses a two-camera stereo rig for image acquisition. It works at nighttime with controll...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Agricultural and Applied Economics
سال: 1994
ISSN: 1074-0708,2056-7405
DOI: 10.1017/s1074070800019349