Rice Evapotranspiration Forecasting Based on Improved Parameter Projection Pursuit Model

نویسندگان

  • FU Qiang
  • WANG Zilong
چکیده

The method of partial least-squares regression (PLSR) can effectively deal with the problems of multicollinearity among independent variables, but can not ideally solve the complicated problems of nonlinearity between dependent variables and independent variables. The method of coupling model with back propagations artificial neural network (BP-ANN) and projection pursuit (PP) is an ideal tool to deal with the problem of nonlinearity, and it is very steady, but can not ideally solve the problems of multicollinearity among independent variables. The paper combines the two methods to establish the method of coupling model with neural network and projection pursuit based on partial least-squares regression to forecast rice evapotranspiration. The results of forecasting indicate that the combination is superior to either of them, the model was found to be able to give satisfactory effect.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Projection Pursuit Regression Model Based on Real-coded Genetic Algorithm for Flood Forecastion

Combining the advantages of genetic algorithm (GA) and projection pursuit regression (PPR), this article firstly uses improved Hermit polynomial as the ridge function of projection pursuit regression model. And then adopted the real-coded genetic algorithm to optimize the projection direction, a forecasting model for peak flow of short flood forecasting is presented. Applied the presented model...

متن کامل

انجام یک مرحله پیش پردازش قبل از مرحله استخراج ویژگی در طبقه بندی داده های تصاویر ابر طیفی

Hyperspectral data potentially contain more information than multispectral data because of their higher spectral resolution. However, the stochastic data analysis approaches that have been successfully applied to multispectral data are not as effective for hyperspectral data as well. Various investigations indicate that the key problem that causes poor performance in the stochastic approaches t...

متن کامل

Evaluated Crop Evapotranspiration over a Region of Irrigated Orchards with the Improved ACASA–WRF Model Citation

Among the uncertain consequences of climate change on agriculture are changes in timing and quantity of precipitation together with predicted higher temperatures and changes in length of growing season. The understanding of how these uncertainties will affect water use in semiarid irrigated agricultural regions depends on accurate simulations of the terrestrial water cycle and, especially, evap...

متن کامل

An Improved Projection Pursuit Clustering Model and its Application Based on Quantum-behaved Particle Swarm Optimization

Extracting the information with biological significance in amounts of gene expression data is an important research direction. Clustering algorithm in this area has been increasingly widely applied. According to the characteristic of gene expression data, the improved projection pursuit cluster model was introduced in this area and Quantum-behaved Particle Swarm Optimization(QPSO) was put forwa...

متن کامل

The Partially Linear Regression Model: Monte Carlo Evidence from the Projection Pursuit Regression Approach

In a partially linear regression model with a high dimensional unknown component we find an estimator of the parameter of the linear part based on projection pursuit methods to be considerably more efficient than the standard density weighted kernel estimator.

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2010