In order to improve the prediction precision of grain yield, the grey system theory and the fuzzy neutral network are combined to construct the combined prediction model, which is applied in predicting the grain yield. Firstly, the basic theory of the grey system theory is analyzed. Secondly, the mathematical model of fuzzy neutral network is studied, and the corresponding algorithm procedure i...

in this research, 272977 test day records collected from 659 herds during years 2001 to 2011 by the iranian animal breeding center were used. in the first section the ability of different models to predict daily milk yield from alternative milk recording was tested. the result showed that a complex model including noon milking time plus the effect of lactation curve of ali and schaeffer functio...

This paper presents the importance of understanding defect propagation/growth and its impact on in-line yield prediction. In order to improve the prediction accuracy, impact of defect propagation and growth phenomena needs to be modeled and incorporated into yield prediction system. We developed a new yield prediction model by taking into account defect carryover. The empirical results of inter...

Most of greenhouse growers desire a determined amount of yields in order to accurately meet market requirements. The purpose of this paper is to model a simple but often satisfactory supervised classification method. The original naive Bayes have a serious weakness, which is producing redundant predictors. In this paper, utilized regularization technique was used to obtain a computationally eff...

khorasan province is one of the most important provinces of iran, especially as regards agricultural products. the prediction of crop yield with available data has important effects on socio-economic and political decisions at the regional scale. this study shows the ability of artificial neural network (ann) technology and adaptive neuro-fuzzy inference systems (anfis) for the prediction o...

We investigate the parallel assembly of two-dimensional, geometrically-closed modular target structures out of homogeneous sets of macroscopic components of varying anisotropy. The yield predicted by a chemical reaction network (CRN)-based model is quantitatively shown to reproduce experimental results over a large set of conditions. Scaling laws for parallel assembling systems are then derived...

According to the difference of the modeling theories, the stock yield prediction models can be divided into two sorts. One is the traditional fluctuation rate prediction model based on statistical theory, and the other is the innovational prediction model based on theories such as NN, grey theory, support vector machines (SVM) and so on. In this article, we introduced these two models and their...

The purpose of this paper is to explore the dynamics of neural networks in forecasting crop (wheat) yield using remote sensing and other data. We use the Adaptive Neuro-Fuzzy Inference System (ANFIS). The input to ANFIS are several parameters derived from the crop growth simulation model (CGMS) including soil moisture content, above ground biomass, and storage organs biomass. In addition we use...

This paper performs an extension to conventional regression neural networks (NNs) for replacing the point predictions they produce with prediction intervals that satisfy a required level of confidence. Our approach follows a novel machine learning framework, called Conformal Prediction (CP), for assigning reliable confidence measures to predictions without assuming anything more than that the d...

The present experiment was conducted to evaluate the ability of the U.S. Meat Animal Research Center's beef carcass image analysis system to predict calculated yield grade, longissimus muscle area, preliminary yield grade, adjusted preliminary yield grade, and marbling score under commercial beef processing conditions. In two commercial beef-processing facilities, image analysis was conducted o...