There are a lot of methods in city water consumption short-term forecasting both inside and outside the country. But among these methods there exist many advantages and shortcomings in model establishing, solving and ...There are a lot of methods in city water consumption short-term forecasting both inside and outside the country. But among these methods there exist many advantages and shortcomings in model establishing, solving and predicting accuracy, speed, applicability. This article draws lessons from other realm mature methods after many years′ study. It′s systematically studied and compared to predict the water consumption in accuracy, speed, effect and applicability among the time series triangle function method, artificial neural network method, gray system theories method, wavelet analytical method.展开更多
Rainstorms are one of the most important types of natural disaster in China.In order to enhance the ability to forecast rainstorms in the short term,this paper explores how to combine a back-propagation neural network...Rainstorms are one of the most important types of natural disaster in China.In order to enhance the ability to forecast rainstorms in the short term,this paper explores how to combine a back-propagation neural network(BPNN)with synoptic diagnosis for predicting rainstorms,and analyzes the hit rates of rainstorms for the above two methods using the county of Tianquan as a case study.Results showed that the traditional synoptic diagnosis method still has an important referential meaning for most rainstorm types through synoptic typing and statistics of physical quantities based on historical cases,and the threat score(TS)of rainstorms was more than 0.75.However,the accuracy for two rainstorm types influenced by low-level easterly inverted troughs was less than 40%.The BPNN method efficiently forecasted these two rainstorm types;the TS and equitable threat score(ETS)of rainstorms were 0.80 and 0.79,respectively.The TS and ETS of the hybrid model that combined the BPNN and synoptic diagnosis methods exceeded the forecast score of multi-numerical simulations over the Sichuan Basin without exception.This kind of hybrid model enhanced the forecasting accuracy of rainstorms.The findings of this study provide certain reference value for the future development of refined forecast models with local features.展开更多
Short-term forecasting is a difficult problem because of the influence of non-linear factors and irregular events.A novel short-term forecasting method named TIK was proposed,in which ARMA forecasting model was used t...Short-term forecasting is a difficult problem because of the influence of non-linear factors and irregular events.A novel short-term forecasting method named TIK was proposed,in which ARMA forecasting model was used to consider the load time series trend forecasting,intelligence forecasting DESVR model was applied to estimate the non-linear influence,and knowledge mining methods were applied to correct the errors caused by irregular events.In order to prove the effectiveness of the proposed model,an application of the daily maximum load forecasting was evaluated.The experimental results show that the DESVR model improves the mean absolute percentage error(MAPE) from 2.82% to 2.55%,and the knowledge rules can improve the MAPE from 2.55% to 2.30%.Compared with the single ARMA forecasting method and ARMA combined SVR forecasting method,it can be proved that TIK method gains the best performance in short-term load forecasting.展开更多
The aim of the research was to connect two methods of the chemical control. The first chemical treatments were applied according to the signalling method. The second method was applied according to the phonological cr...The aim of the research was to connect two methods of the chemical control. The first chemical treatments were applied according to the signalling method. The second method was applied according to the phonological criterion i.e., on the basis of the values of effective temperatures sums or heat sums for cutworms. The studies on cutworms infesting sugar beet crops were carried out in the years 2005-2008. The observation performed during the moth flights from May to September included two species, turnip moth （Agrotis segetum Den. ＆ Schiff.） and heart-and-dart moth （A. exclamationis L.）. The dynamics of moth flights was recorded in reference to readings of climatic conditions registered with the field meteorological stations set up near the light traps. Observations on cutworm occurrence during the vegetation season were done every 5-7 days. Moreover, additional studies were conducted under control conditions in the growth chambers at three programmed temperatures （17°C, 20 °C, 24 °C） and relative humidity （50%-70%）. Based on the results the values for the heat sum of 501.1 °C and effective temperatures sum of 230.0 °C were determined for the developmental stages of cutworm. On the base of the results obtained it can be stated that the improved method of short-term forecasting can be an alternative solution in the integrated protection management against pest.展开更多
文摘There are a lot of methods in city water consumption short-term forecasting both inside and outside the country. But among these methods there exist many advantages and shortcomings in model establishing, solving and predicting accuracy, speed, applicability. This article draws lessons from other realm mature methods after many years′ study. It′s systematically studied and compared to predict the water consumption in accuracy, speed, effect and applicability among the time series triangle function method, artificial neural network method, gray system theories method, wavelet analytical method.
基金supported by the National Key Research and Development Program on Monitoring,Early Warning and Prevention of Major Natural Disasters [grant number 2018YFC1506006]the National Natural Science Foundation of China [grant numbers 41805054 and U20A2097]。
文摘Rainstorms are one of the most important types of natural disaster in China.In order to enhance the ability to forecast rainstorms in the short term,this paper explores how to combine a back-propagation neural network(BPNN)with synoptic diagnosis for predicting rainstorms,and analyzes the hit rates of rainstorms for the above two methods using the county of Tianquan as a case study.Results showed that the traditional synoptic diagnosis method still has an important referential meaning for most rainstorm types through synoptic typing and statistics of physical quantities based on historical cases,and the threat score(TS)of rainstorms was more than 0.75.However,the accuracy for two rainstorm types influenced by low-level easterly inverted troughs was less than 40%.The BPNN method efficiently forecasted these two rainstorm types;the TS and equitable threat score(ETS)of rainstorms were 0.80 and 0.79,respectively.The TS and ETS of the hybrid model that combined the BPNN and synoptic diagnosis methods exceeded the forecast score of multi-numerical simulations over the Sichuan Basin without exception.This kind of hybrid model enhanced the forecasting accuracy of rainstorms.The findings of this study provide certain reference value for the future development of refined forecast models with local features.
基金Projects(70671039,71071052) supported by the National Natural Science Foundation of ChinaProjects(10QX44,09QX68) supported by the Fundamental Research Funds for the Central Universities in China
文摘Short-term forecasting is a difficult problem because of the influence of non-linear factors and irregular events.A novel short-term forecasting method named TIK was proposed,in which ARMA forecasting model was used to consider the load time series trend forecasting,intelligence forecasting DESVR model was applied to estimate the non-linear influence,and knowledge mining methods were applied to correct the errors caused by irregular events.In order to prove the effectiveness of the proposed model,an application of the daily maximum load forecasting was evaluated.The experimental results show that the DESVR model improves the mean absolute percentage error(MAPE) from 2.82% to 2.55%,and the knowledge rules can improve the MAPE from 2.55% to 2.30%.Compared with the single ARMA forecasting method and ARMA combined SVR forecasting method,it can be proved that TIK method gains the best performance in short-term load forecasting.
文摘The aim of the research was to connect two methods of the chemical control. The first chemical treatments were applied according to the signalling method. The second method was applied according to the phonological criterion i.e., on the basis of the values of effective temperatures sums or heat sums for cutworms. The studies on cutworms infesting sugar beet crops were carried out in the years 2005-2008. The observation performed during the moth flights from May to September included two species, turnip moth （Agrotis segetum Den. ＆ Schiff.） and heart-and-dart moth （A. exclamationis L.）. The dynamics of moth flights was recorded in reference to readings of climatic conditions registered with the field meteorological stations set up near the light traps. Observations on cutworm occurrence during the vegetation season were done every 5-7 days. Moreover, additional studies were conducted under control conditions in the growth chambers at three programmed temperatures （17°C, 20 °C, 24 °C） and relative humidity （50%-70%）. Based on the results the values for the heat sum of 501.1 °C and effective temperatures sum of 230.0 °C were determined for the developmental stages of cutworm. On the base of the results obtained it can be stated that the improved method of short-term forecasting can be an alternative solution in the integrated protection management against pest.
