Ensemble averaging and mean squared error

نویسنده

  • JONATHAN ROUGIER
چکیده

In fields such as climate science, it is common to compile an ensemble of different simulators for the same underlying process. It is a striking observation that the ensemble mean often out-performs at least half of the ensemble members in mean squared error (measured with respect to observations). In fact, as demonstrated in the most recent IPCC report, the ensemble mean often out-performs all or almost all of the ensemble members across a range of climate variables. This paper shows that these could be mathematical results based on convexity and averaging, but with implications for the properties of the current generation of climate simulators.

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

Ensemble Neural Network Approach for Accurate Load Forecasting in a Power System

The paper presents an improved method for 1–24 hours load forecasting in the power system, integrating and combining different neural forecasting results by an ensemble system. We will integrate the results of partial predictions made by three solutions, out of which one relies on a multilayer perceptron and two others on self-organizing networks of the competitive type. As the expert system we...

متن کامل

Application of ensemble learning techniques to model the atmospheric concentration of SO2

In view of pollution prediction modeling, the study adopts homogenous (random forest, bagging, and additive regression) and heterogeneous (voting) ensemble classifiers to predict the atmospheric concentration of Sulphur dioxide. For model validation, results were compared against widely known single base classifiers such as support vector machine, multilayer perceptron, linear regression and re...

متن کامل

A new median filter based fingerprint recognition algorithm

In this paper, a new algorithm for fingerprint recognition is presented. It is called the Histogram-Partitioning, Median-Filtering Fingerprint Recognition Algorithm (HMFA). The performance of the algorithm is tested through ensemble averaging of the mean square error. It is applied on different fingerprints having various backgrounds, resolutions and dimensions. Initially, a database is formed ...

متن کامل

استفاده از POD در استخراج ساختارهای متجانس‌ یک میدان آشفته آماری- همگن

Capability of the Proper Orthogonal Decomposition (POD) method in extraction of the coherent structures from a spatio-temporal chaotic field is assessed in this paper. As the chaotic field, an ensemble of 40 snapshots, obtained from Direct Numerical Simulation (DNS) of the Kuramoto-Sivashinsky (KS) equation, has been used. Contrary to the usual methods, where the ergodicity of the field is need...

متن کامل

Ensemble Methods for Reinforcement Learning with Function Approximation

Ensemble methods allow to combine multiple models to increase the predictive performances but mostly utilize labelled data. In this paper we propose several ensemble methods to learn a combined parameterized state-value function of multiple agents. For this purpose the Temporal-Difference (TD) and Residual-Gradient (RG) update methods as well as a policy function is adapted to learn from joint ...

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 2017