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Forecasting Malaysia load using a hybrid model
... a hybrid model to forecast Malaysia load. Using the mean absolute percentage error (MAPE) as performance measurement, we found that, by using only one hidden node, the ... See full document
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An Effective Artificial Neural Network based Power Load Prediction Algorithm
... hybridized model of ANN with GA is used to optimize the number of input neurons and the number of neurons in the hidden layer of the neural network ...(GAs) using the method of evolution and survival of the ... See full document
7
HYBRID AND INTEGRATED APPROACH TO SHORT TERM LOAD FORECASTING
... for load forecasting are time series based models, similar-day approach and intelligent system based ...conventional forecasting methods have major drawbacks especially their inability to map the ... See full document
6
24-Hours Load Forecasting Using a Hybrid of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for Optimized Neural Network
... develop hybrid method for short term load forecasting models using Genetic Algorithm and Particle Swarm Optimization (HGAPSO-ANN) to train Artificial Neural ...evaluated using the ... See full document
16
SHORT-TERM LOAD FORECASTING WITH SPECIFIC MODEL OF FLN USING ARTFICIAL NEURAL NETWORK
... of hybrid neural models with significant advantage when compared to conventional artificial neural ...The hybrid model using the Functional Link Networks presents a good performance and is ... See full document
7
Tourism forecasting using hybrid modified empirical mode decomposition and neural network
... in Malaysia started to blossom around the year 1999 when Malaysia Tourism Promotion Board (MTPB) promoted Malaysia through a worldwide campaign ‘Malaysia, Truly ...promote Malaysia ... See full document
18
A hybrid forecasting model for Malaysian exports earning of natural rubber-based products
... a hybrid model for forecasting export earning for NR ...proposed model and naïve individual model (multiple regression) is ...and hybrid model can be used as ... See full document
7
Double seasonal ARIMA model for forecasting load demand
... Several forecasting methods with varying degrees of success have been implemented for load forecasting including multiple linear regression (Al-Hamadi & Soliman [2]) and nonlinear multiple ... See full document
15
Forecasting Strategies for Predicting Peak Electric Load Days
... electric load demand for ...complex load behavior for the Tunisian Company of Electricity and ...Their model facilitated in capturing some of the special cases with high temperature events and moving ... See full document
87
Short Term Load Forecasting Using A Hybrid Model Based On Support Vector Regression
... a hybrid method based on SVR and KH algorithm to predict the load data with more ...SVR model is ...for forecasting the load ...for forecasting the ... See full document
7
Forecasting of River Sediment Amount using Machine Model
... by using hydro-meteorological parameters such as river flow, air temperature and precipitation measured between 2011 - 2017 at Omaha Station in Nebrask ...by using correlation coefficient (R), mean absolute ... See full document
7
Electrical Load Forecasting Using Fuzzy System
... electrical load of an interconnected power system of a country, we need to forecast its demand in ...electrical load on short-term ...by using the centroid ...the load demand. The difference ... See full document
11
Weather forecasting based on hybrid neural model
... finalized using layers interconnec- tion concept for 2 days advanced weather ...proposed hybrid model for weather fore- casting, data is collected from ... See full document
6
Simulation of Forecasting Performance Comparison of a Hybrid Model Integrated By Binomial Smoothing and Bayesian Model Averaging Techniques
... a hybrid JPSN-AR model is proposed based on binomial smoothing (BS) and Bayesian model averaging ...best forecasting performance for the proposed hybrid ...The forecasting ... See full document
13
Use of Artificial Neural Networks for Short Term Electricity Load Forecasting of Kenya National Grid Power System
... ANN has to be configured such that the application of a set of inputs produces the desired set of outputs. Various methods to set the strengths of the connections exist. One way is to set the weights explicitly, ... See full document
6
Impact of Earnings per Share on Market Price of Share with Special Reference to Selected Companies Listed on NSE
... In the future, other advanced optimization algorithms can be used to select the best appropriate structure and parameters for the BPNN to handle complex forecasting problems for enterprises in the network economic ... See full document
7
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... Electric load forecasting is essential for planning in advance to meet the continuous supply of electricity ...peak load demand forecasting in Nigeria. The time series model used ... See full document
5
Power Load Forecasting using Back Propagation Algorithm
... A large volume of work has been done, with respect to the choice of number of hidden layers and number of hidden layer nodes during the training process where the input patterns are presented, with initial random weights ... See full document
6
Dynamic Forecasting method for Shariah-compliant Share Price of Healthcare sector in Malaysian Stock Exchange
... of forecasting model Balli and Elsamadisy (2012)[9] recommended that the ARIMA model is a good estimation for short-term ...series model to forecast the future gold price in order to mitigate ... See full document
9
Design And Development Of Hybrid Power Generation Model Using Wind And Solar Energy For Residential Building
... of hybrid system in remote or rural areas are famous now a days as renewable energy are becoming more and more popular and advance at this era (Nema et ...for hybrid stem in remote regions is rapidly ... See full document
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