in order to compare the precision of predictions of nrc (2001) and cncps models, 17 holstein fresh cows were assigned in a randomized complete block design to a balanced diet with nrc (2001) and cncps software. the predicted dmi, energy allowable milk and protein allowable milk by both models were compared with observed values. the precision of the predictions of models was evaluated by calcula...

Soil moisture is generally regarded as the limiting factors in rangeland production. Although many studies have been conducted to estimate soil moisture in semiarid areas, there is little information on mountainous rangelands in west of Iran. The present study aims to investigate the soil moisture estimation in rangelands as compared to the other land uses over a mountainous area in central Zag...

In drying seaweeds, it is important to describe its behavior using semi-theoretical models. Predicting the best model for seaweed was commonly done by testing goodness of curve models calculating coefficient determination R2, reduced chi square X2, root means error (RMSE) and mean bias (MBE). However, essential rank before selection assessing performance index Φ relative deviation (MRD). It als...

Forecasting is a systematic attempt to examine the future by inference from known facts. Sales forecasting is an ballpark figure of sales during a specified future period. Formerly, it was a manual process using the mathematical formulas. Due to the advent of computer the process of sale forecasting is fast and accurate. Machine learning, a subfield of Artificial Intelligence, has many algorith...

This paper presents a scheme using Differential Evolution based Functional Link Artificial Neural Network (FLANN) to predict the Indian Stock Market Indices. The Model uses Back-Propagation (BP) algorithm and Differential Evolution (DE) algorithm respectively for predicting the Stock Price Indices for one day, one week, two weeks and one month in advance. The Indian stock prices i.e. BSE (Bomba...

Recent years have witnessed a controversy over Heisenberg’s famous error-disturbance relation. Here we resolve the conflict by way of an analysis of the possible conceptualizations of measurement error and disturbance in quantum mechanics. We discuss two approaches to adapting the classic notion of root-mean-square error to quantum measurements. One is based on the concept of noise operator; it...

This paper presents the application of feed-forward multilayer perceptron networks to forecast hourly nitrogen oxides levels 24 hours in advance. Input data were meteorological variables, average hourly traffic and nitrogen oxides hourly levels. The introduction of four periodic components (sine and cosine terms for the daily and weekly cycles) was analyzed in order to improve the models’ predi...

this paper presents the prediction of vehicle's velocity time series using neural networks. for this purpose, driving data is firstly collected in real world traffic conditions in the city of tehran using advance vehicle location devices installed on private cars. a multi-layer perceptron network is then designed for driving time series forecasting. in addition, the results of this study a...

An neural network model of data mining is used to identify error sources in satellite-derived tropical sea surface temperature (SST) estimates from thermal infrared sensors onboard the Geostationary Operational Environmental Satellite (GOES). By using the Back Propagation Network (BPN) algorithm, it is found that air temperature, relative humidity, and wind speed variation are the major factors...