Study on Energy Consumption Prediction of Liquor-Making Based on GA-BP Neural Net

Qi Yao Han; Li Juan Qian; Xian Yu Chu

doi:10.4028/www.scientific.net/AMM.635-637.1681

Paper Titles

Two Typical Symbols in Human-Machine Interactive Interface
p.1659

Deep Study and Improvement of the Globally Convergent Version of MMA
p.1666

Research on Evaluation of Soil Fertilities of Farmland at County Level in Nongan Based on Data Mining
p.1671

State Attainability Analysis of Petri Net with Discrete Time Span
p.1675

Study on Energy Consumption Prediction of Liquor-Making Based on GA-BP Neural Net
p.1681

AGROTOOL Software as an Intellectual Core of Decision Support Systems in Computer Aided Agriculture
p.1688

Analysis and Simulation of Binary Search Algorithm
p.1692

Application of Grey Model Theory to Forecast Flight Training Time
p.1696

Comparison of Genetic Algorithm and Determinant Method on Solving a System of Linear Equations
p.1700

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 635-637Study on Energy Consumption Prediction of...

Study on Energy Consumption Prediction of Liquor-Making Based on GA-BP Neural Net

Abstract:

Aimed at the Liquor-making with the characteristic of huge consumption of raw materials and energy,this paper presents a predictive method of Liquor-making energy consumption based on GA-BP Neural Net.Genetic algorithm of mixed coding was used to optimize the structure and initial values,and then BP algorithm adjusted weight and thresholding accurately.Construct the B-P model by using the neural networks toolbox of MATLAB. Optimize calculation based on MATLAB genetic algorithm toolbox using the real data of water consumption,electricity consumptionand steam consumption.The prediction results agrees well with the real data.Finally factual data are used to validate the validity and the rationality of the designed result .Liquor-making energy consumption mainly is water consumption,electricity consumption and steam consumption.Results in some extent can reflect the liquor enterprise energy consumption.Experiment shows that the method is effective for the liquor enterprise energy consumption.prediction.

You might also be interested in these eBooks

Advanced Design and Manufacturing Technology IV

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 635-637)

Pages:

1681-1687

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.635-637.1681

Citation:

Cite this paper

Online since:

September 2014

Authors:

Qi Yao Han*, Li Juan Qian, Xian Yu Chu

Keywords:

Consumption Energy, Genetic Algorithm (GA), Liquor-Making, Neural Network (NN), Predictions

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Stoteris A. Kalogirou. Applications of artificial neural-networks for energy systems Applied Energy [J], 2000, 67(1): 17~35.

DOI: 10.1016/s0306-2619(00)00005-2

Google Scholar

[2] Raul Pino, Jose Parreno, Alberto Gomez, Paolo Priore. Forecasting next-day price of electricity in the Spanish energy market using artificial neural networks[J]. Engineering Applications of Artificial Intelligence[J], 2008, (21): 53~62.

DOI: 10.1016/j.engappai.2007.02.001

Google Scholar

[3] J L Yuan, T L Fine. Neural-Network design for small training sets of high dimension[J]. IEEE Trans Neural Networks, vol. 9, 1998(3)：266–236.

DOI: 10.1109/72.661122

Google Scholar

[4] David J C MacKay. A practical bayesian framework for backpropagation networks[J]. Neural Computation, 1992(4): 448-472.

DOI: 10.1162/neco.1992.4.3.448

Google Scholar