Top PDF Diseño, análisis e interpretación de indicadores de gestión para la Cooperativa de Ahorro y Crédito el Saragrio Ltda. De la ciudad de Ambato, período 2008"
A Neural Network Model for Forecasting CO2 Emission
... the emission of large amounts of harmful pollutants and greenhouse gases, with serious consequences on health and ...to model such complex phenomena eficiently because they often lead to approximations or ...
An Integrated Intelligent Neuro-Fuzzy Algorithm for Long-Term Electricity Consumption: Cases of Selected EU Countries
... a neural network, a time series and ANOVA ...artificial neural network and genetic algorithm framework to predict electrical energy consumption ...for forecasting electrical energy ...
APPLYING THE ARTIFICIAL NEURAL NETWORK METHODOLOGY FOR FORECASTING THE TOURISM TIME SERIES
... ANN model can accurately classify information as pre-specified ...the model being used by the net to solve a ...simplified neural network with three ...
Analysis of forecasting capabilities of ground surfaces valuation using artificial neural networks
... the neural networks was selected from the parameters established in the design of the experimental tests, in addition to parameters from the workpiece grinding ...the neural networks was adopted to provide ...
Tourism demand modeling and forecasting with artificial neural network models: The Mozambique case study
... and forecasting have been published in the recent years ...used neural networks to modelling and forecast tourism demand ...feed-forward neural network model to forecast Japanese ...
Forecasting Inflation under Globalization with Artificial Neural Network-Based Thin and Thick Models
... thick model [9] outperforms the linear model for real-time and bootstrap forecasts in the Euro area as well as in some other countries considered in their study using the Phillips-Curve ...thick ...
A hierarchical hybrid neural model in short-term load forecasting
... feed-forward neural network trained with the standard error back- propagation algorithm ...short-term forecasting of daily peak load, total daily energy, and hourly daily load, ...
Neural network emulation of a rainfall-runoff model
... in forecasting outputs related to the use of neural solutions was attributed to potential noise in the observed hydro- logical records or to the limited lengths of the datasets upon which the various ...
A hierarchical neural model in short-term load forecasting
... Bakirtzis et al. [4] employed a single fully con- nected NN to predict, on a daily basis, the load along a whole year for the Greek power system. The au- thors made use of the previous year for training pur- poses. ...
A framework for neural network to make business forecasting with hybrid VAR and GA components
... the network acts just like a black ...of neural network and econometrics and genetic ...the network have significant influences on the output ...our model will always select the fittest ...
Electricity Load Forecasting based on Framelet Neural Network Technique
... Load forecasting is very essential to the operation of electricity ...Load Forecasting modeling based on Framelet Neural Network Technique (FNN) for Baghdad ...into neural ...
Forecasting Short Term Electricity Price Using Artificial Neural Network and Fuzzy Regression
... price forecasting the exact model of the system is built ...Artificial neural networks (ANNs) have been applied in many researches for forecasting electricity price ...fuzzy neural ...
Application of Artificial Neural Network for Seasonal Rainfall Forecasting: A Case Study for South Australia
... and forecasting capability of South Australian seasonal rainfall with the aid of climate predictors where maximum of two climate drivers were used instead of single and found some successes regarding correlations ...
Short Term Electrical Load Forecasting by Artificial Neural Network
... ANN network is trained with 100 days of data including electrical load and wind power generation and 48 hours forecasting is ...the model and the data selection for ...
An artificial neural network model for rainfall forecasting in Bangkok, Thailand
... ues of connection weights. These algorithms differ in how the weights are obtained. The selection of training algorithm is related to the network type, computer memory, and the input data. As implied in this ...
An Artificial Neural Network for Data Forecasting Purposes
... artificial neural networks (ANN) in solving the forecast task in the most general case, when the time series are ...feed-forward neural architecture: the nonlinear autoregressive network with ...
Short-Term Load Forecasting Using Artificial Neural Network
... load forecasting methodologies as reported in [1] have their own ...Load forecasting can be performed using many techniques such as regression analysis, statistical methods, artificial neural ...
A Neural Network Approach to Time Series Forecasting
... series forecasting. GRNN is a neural network proposed by Donald ...heterogeneous forecasting models adequate to local ...smallest forecasting error but does not accurately forecast the ...
Application of Artificial Neural Networks for Predicting Generated Wind Power
... forecast model gives satisfactory results on training and testing data ...forecast model. The performance of the forecasting network is tested by using actual wind energy ...the ...
Artificial neural network model applied to a PEM fuel cell
... ANN model when applied to a new set (not influencing the determination of the model ...ARTIFICIAL NEURAL NETWORK MODEL APPLIED TO A PEM FUEL ...