A neuro-genetic based short-term forecasting framework for network intrusion prediction system

2009 ◽  
Vol 6 (4) ◽  
pp. 406-414 ◽  
Author(s):  
Siva S. Sivatha Sindhu ◽  
S. Geetha ◽  
M. Marikannan ◽  
A. Kannan
Keyword(s):  
Prediction System ◽  
Short Term ◽  
Network Intrusion ◽  
Short Term Forecasting

MODELING AND SHORT-TERM FORECASTING OF TECHNOLOGY COMPONENT OF ELECTRICAL LOAD OF THE REGIONAL ELECTRIC POWER SYSTEM

2016 ◽  
Vol 2016 (4) ◽  
pp. 68-70 ◽  
Author(s):  
P. Chernenko ◽  
◽  
O. Martyniuk ◽  
V. Miroshnyk ◽  
◽  
...  
Keyword(s):  
Power System ◽  
Electric Power ◽  
Electric Power System ◽  
Electrical Load ◽  
Short Term ◽  
Short Term Forecasting

Short-Term Flood Prediction System

2014 ◽  
Vol 13 (1) ◽  
Author(s):  
Konrad Nering
Keyword(s):  
Flash Floods ◽  
Prediction System ◽  
Short Term ◽  
Data Set ◽  
Flood Prediction ◽  
Full Operation

AbstractThis paper describes a fully functional short-term flood prediction system. Its effect has been tested on watershed of Lubieńka river in Małopolska. To use this system it must have a data set also described in this paper. A modification of the system to adopt for predicting flash floods was described. Full operation of the system is shown on example of real flood on Lubieńka river in June 2011.

The causes of poverty in Russia

2020 ◽  
Vol 13 (1) ◽  
pp. 21-36
Author(s):  
I.S. Ivanchenko
Keyword(s):  
Regression Analysis ◽  
Regional Development ◽  
Financial Market ◽  
Russian Federation ◽  
Short Term ◽  
Financial Situation ◽  
Macroeconomic Variables ◽  
Development Plans ◽  
The Russian Federation ◽  
Short Term Forecasting

Subject. This article analyzes the changes in poverty of the population of the Russian Federation. Objectives. The article aims to identify macroeconomic variables that will have the most effective impact on reducing poverty in Russia. Methods. For the study, I used the methods of logical, comparative, and statistical analyses. Results. The article presents a list of macroeconomic variables that, according to Western scholars, can influence the incomes of the poorest stratum of society and the number of unemployed in the country. The regression analysis based on the selected variables reveals those ones that have a statistically significant impact on the financial situation of the Russian poor. Relevance. The results obtained can be used by the financial market mega-regulator to make anti-poverty decisions. In addition, the models built can be useful to the executive authorities at various levels for short-term forecasting of the number of unemployed and their income in drawing up regional development plans for the areas.

Very short-term forecasting of wind power generation using hybrid deep learning model

2021 ◽  
Vol 296 ◽  
pp. 126564
Author(s):  
Md Alamgir Hossain ◽  
Ripon K. Chakrabortty ◽  
Sondoss Elsawah ◽  
Michael J. Ryan
Keyword(s):  
Power Generation ◽  
Deep Learning ◽  
Wind Power ◽  
Learning Model ◽  
Wind Power Generation ◽  
Short Term ◽  
Short Term Forecasting ◽  
Deep Learning Model
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