A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Filters
Genetic Algorithm-Based RBF Neural Network Load Forecasting Model
2007
IEEE Power Engineering Society General Meeting
Preserved Fulltext
To overcome the limitation of the traditional load forecasting method, a new load forecasting system basing on radial basis Gaussian kernel function (RBF) neural network is proposed in this paper. ...
Genetic algorithm adopting the real coding, crossover probability and mutation probability was applied to optimize the parameters of the neural network, and a faster convergence rate was reached. ...
CONCLUSION In this paper, a new load forecasting system basing on RBF neural network was proposed, and genetic algorithm was applied to optimize the parameters of the neural network. ...
doi:10.1109/pes.2007.385710
fatcat:vfnwrezbfnfavir37kqzatw6te
Short-Term Traffic Prediction Based on Genetic Algorithm Improved Neural Network
2020
Tehnički Vjesnik
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The delay time and embedding dimension are calculated by C-C algorithm, and the chaotic characteristics of the time series are verified by small data sets method.Then based on the neural network prediction ...
Due to the poor stability of the network caused by the initial parameters randomness, the genetic algorithm is used to optimize the initial parameters. ...
results of RBF neural network
Figure 5 5 Relative error histogram of measured data 4 GENETIC ALGORITHM IMPROVED NEURAL NETWORK MODEL 4.1 Genetic Algorithm Improved Wavelet Neural Network (GAWNN)
Figure ...
doi:10.17559/tv-20180402112949
fatcat:o3sy2db2l5f7llp67kgsmew7t4
Study on the Prediction of Real estate Price Index based on HHGA-RBF Neural Network Algorithm
2015
International Journal of u- and e- Service, Science and Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
This paper proposes a new approach which is the combination of hierarchical genetic algorithm and least squares method to optimize the RBF neural network such that we can predict the real estate price ...
The hierarchical genetic algorithm is usually used to optimize the topology of the RBF neural network, the radial basis function center and width. ...
The Prediction Model of RBF Neutral Network Optimized by HHGA Hierarchical Genetic Algorithm (HGA) is a novel genetic algorithm introduced in recent years. ...
doi:10.14257/ijunesst.2015.8.7.11
fatcat:2rbw45sefnc3dfkvnocnteyspa
Traffic Flow Control using Neural Network
2012
International Journal of Applied Information Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
TFF is the study of interactions between vehicles, drivers, and infrastructure (which includes highways and traffic control devices), with the aim of understanding and developing an optimal road network ...
Traffic Flow Forecasting is an important part of ITS [1][2]. Traffic Flow Forecasting (TFF) is for Controlling Traffic and Intelligent Traffic Guidance. ...
Based on RBF NN Optimized by PSO [6]
TFF BASED ON BPNN There are many models available for short-term traffic flow prediction out of which Neural Network Model becomes more active because of its adaptive ...
doi:10.5120/ijais12-450115
fatcat:kay5ppaiknanrpmti5ad22kv4m
An RBF Neural Network Combined with OLS Algorithm and Genetic Algorithm for Short-Term Wind Power Forecasting
2013
Journal of Applied Mathematics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
The OLS algorithm is used to determine the optimal number of nodes in a hidden layer of RBF neural network. ...
This paper proposes a hybrid method that combines orthogonal least squares (OLS) algorithm and genetic algorithm (GA) to construct the radial basis function (RBF) neural network for short-term wind power ...
The application of genetic algorithm to optimization has become a useful tool in many fields. ...
doi:10.1155/2013/971389
fatcat:6peugid6ezcgnim3x4skbev5tu
Intelligent Flood Disaster Forecasting Based on Improved Neural Network Algorithm
2018
NeuroQuantology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
based on the improved neural network algorithm, applies it to flood forecasting and flood damage assessment, proposes a flood decision support system consisting of external conversion layer, information ...
Based on the existing researches, and in combination with the knowledge of artificial intelligence, management decision science, and theoretical derivation, this study constructs a flood forecasting model ...
Acknowledgements This work was supported by a General Financial Grant from the National Natural Science Foundation of China (Grant No. 51679191) and the project funded by Research and Extension of Water ...
doi:10.14704/nq.2018.16.6.1626
fatcat:zivxhub5wve27fs3mrwt7ffmem
Stock Index Modeling Using Hierarchical Radial Basis Function Networks
[chapter]
2006
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Empirical results indicate that the proposed method is better than the conventional neural network and RBF networks forecasting models. ...
Based on the pre-defined instruction sets, HRBF model can be created and evolved. ...
Acknowledgment This research was partially supported the Natural Science Foundation of China under contract number 60573065, and The Provincial Science and Technology Development Program of Shandong under ...
doi:10.1007/11893011_51
fatcat:aa4uei247fcxpio7bwnbrjilzi
Volatility Forecasting in Financial Risk Management with Statistical Models and ARCH-RBF Neural Networks
2014
Journal of Risk Analysis and Crisis Response (JRACR)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
We also use a large number of statistical models as well as different optimization techniques for RBF network such as genetic algorithms or clustering. ...
We suggest the ARCH-RBF model that combines information from ARCH with RBF neural network for volatility forecasting. ...
In case of models based on neural network approach, we suggested new model for forecasting volatility with neural networks -the ARCH-RBF neural network. ...
doi:10.2991/jrarc.2014.4.2.4
fatcat:wchontdwybbuxpkuocymtozvdq
The Prediction of Food Safety Composite Index based on BP Neural Network and GA Algorithm
2015
Advance Journal of Food Science and Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
The study established a BP neural network prediction model to test the effect of the application to predict the food safety Index. ...
The GA was used to optimize the weights and thresholds of BP neural network. ...
The genetic algorithm to optimize the BP neural network prediction model: GA algorithm is a global search algorithm, the organic integration of the BP neural network and GA algorithm, GA algorithm is used ...
doi:10.19026/ajfst.8.1473
fatcat:fsy3jhcw6nhlxf5klyhhiaigq4
Financial Time Series Modelling with Hybrid Model Based on Customized RBF Neural Network Combined With Genetic Algorithm
2014
Advances in Electrical and Electronic Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
In this paper, authors apply feed-forward artificial neural network (ANN) of RBF type into the process of modelling and forecasting the future value of USD/CAD time series. ...
To determine the forecasting efficiency, authors perform the comparative out-of-sample analysis of the suggested hybrid model with statistical models and the standard neural network. ...
than the standard model of the RBF neural network and the statistical model and there was a clear benefit of better one-day-ahead forecasts. ...
doi:10.15598/aeee.v12i4.1206
fatcat:biess2e32vb6rfr5pz6zwu4ygm
Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network
2016
The Scientific World Journal
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. ...
To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. ...
forecasts than the standard model of the RBF neural network and as the statistical model and hence there was a clear benefit of better one-day-ahead forecasts. ...
doi:10.1155/2016/3460293
pmid:26977450
pmcid:PMC4761754
fatcat:iuq7b6iqnrfgrmpcule7lo7eyu
Energy Consumption Prediction Model of Public Buildings Based on PSO-RBF
2017
DEStech Transactions on Computer Science and Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
By analyzing thechange characteristics of energy consumption of public buildings in hot summer and cold winter zone, a building energy consumption prediction model based on RBF neural network is established ...
On this basis, particle swarm optimization is used to optimize our model, and the building energy consumption prediction model based on PSO-RBF is established. ...
based on RBF neural network. ...
doi:10.12783/dtcse/aics2016/8183
fatcat:77h5qb3yabbink2p7msekuns5i
Time series sales forecasting for short shelf-life food products based on artificial neural networks and evolutionary computing
2006
Journal of Food Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
The method is a combination of two artificial intelligence technologies, namely the radial basis function (RBF) neural network architecture and a specially designed genetic algorithm (GA). ...
In this paper we present a complete framework that can be used for developing nonlinear time series sales forecasting models. ...
Acknowledgments Financial support by FAGE S.A. and the General Secretariat of Research and Technology in Greece under the PENED 2001 research program (01ED38) is gratefully acknowledged. ...
doi:10.1016/j.jfoodeng.2005.03.056
fatcat:p4gjdxnifzhxfioggjax3tgbke
Survey on short-term load forecasting using hybrid neural network techniques
2018
International Journal of Engineering & Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
The paper investigates the application of artificial neural networks (ANN) with fuzzy logic (FL), Genetic Algorithm(GA), Particle Swarm Optimization(PSO) and Support Vector Machines(SVM) as forecasting ...
In the current work, several latest methodologies based on artificial neural networks along with other techniques have be discussed, in order to obtain short-term load forecasting. ...
The performance of BP neural network based genetic algorithm optimization predictions are compared with that of BP network using load time series from a practical power system. ...
doi:10.14419/ijet.v7i2.8.10486
fatcat:cl5nj5dgazhzppmxkrhwxgywcu
Application of Neural Network Models in Modelling Economic Time Series with Non-constant Volatility
2015
Procedia Economics and Finance
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
We suggest an alternative approach for forecasting time series with non-constant volatilitywe suggest and implement several neural network prediction models; we also use a large number of statistical models ...
We quantify several ARCH and GARCH models; we also implement various RBF neural network prediction models. ...
Acknowledgements This paper was supported by VEGA grant project 1/0942/14: Dynamic modelling and soft techniques in prediction of economic variables. ...
doi:10.1016/s2212-5671(15)01674-3
fatcat:cn7jrpwlajcp5au2gxs3vosrga
« Previous
Showing results 1 — 15 out of 3,330 results