Heilongjiang is a large agriculture province.Problems of agriculture,rural areas and farmers are urgent to be solved.The development of agriculture needs the support of agricultural credits,because finance is the cent...Heilongjiang is a large agriculture province.Problems of agriculture,rural areas and farmers are urgent to be solved.The development of agriculture needs the support of agricultural credits,because finance is the center of agriculture economy.However,the low comparative advantage in agriculture and pursuit of the capital interests which aggravate the conflicts of supply and demand of agricultural funds.Lacking of fund is the main factor that constrains the development of agricultural economy.In order to analyze the economic effect of agricultural credits on agricultural economy,an error correction model was set up to research the relationship between them,which based on the least square methods.Through the study of the contribution from agricultural credits to total value of agricultural out-put,the empirical evidence for developing the rural financial vigorously was provided,in order to promote the agricultura leconomic development.展开更多
Based on the theory of the post method pedagogy and the teaching practice,this paper proposes a new teaching model,the self-correction model,and explains it from the point of view of linking theory.
In view of the learners Chinglish,this paper puts forward a new teaching model-the Self-correction Model and makes an analysis of it from the view of cognitive psychology.
Errors inevitably exist in numerical weather prediction (NWP) due to imperfect numeric and physical parameterizations. To eliminate these errors, by considering NWP as an inverse problem, an unknown term in the pred...Errors inevitably exist in numerical weather prediction (NWP) due to imperfect numeric and physical parameterizations. To eliminate these errors, by considering NWP as an inverse problem, an unknown term in the prediction equations can be estimated inversely by using the past data, which are presumed to represent the imperfection of the NWP model (model error, denoted as ME). In this first paper of a two-part series, an iteration method for obtaining the MEs in past intervals is presented, and the results from testing its convergence in idealized experiments are reported. Moreover, two batches of iteration tests were applied in the global forecast system of the Global and Regional Assimilation and Prediction System (GRAPES-GFS) for July-August 2009 and January-February 2010. The datasets associated with the initial conditions and sea surface temperature (SST) were both based on NCEP (National Centers for Environmental Prediction) FNL (final) data. The results showed that 6th h forecast errors were reduced to 10% of their original value after a 20-step iteration. Then, off-line forecast error corrections were estimated linearly based on the 2-month mean MEs and compared with forecast errors. The estimated error corrections agreed well with the forecast errors, but the linear growth rate of the estimation was steeper than the forecast error. The advantage of this iteration method is that the MEs can provide the foundation for online correction. A larger proportion of the forecast errors can be expected to be canceled out by properly introducing the model error correction into GRAPES-GFS.展开更多
By using error correction model, I conduct co-integration analysis on the research of the relationship between the per capita practical consumption and per capita practical disposable income of urban residents in Huna...By using error correction model, I conduct co-integration analysis on the research of the relationship between the per capita practical consumption and per capita practical disposable income of urban residents in Hunan Province from 1978 to 2009. The results show that there is a co-integration relationship between the per capita practical consumption and the practical per capita disposable income of urban residents, and based on these, the corresponding error correction model is established. Finally, corresponding countermeasures and suggestions are put forward as follows: broaden the income channel of urban residents; create goods consuming environment; perfect socialist security system.展开更多
In order to understand the effect of hardening ductility parameters and softening ductility parameters of the concrete damage plastic model in LS-DYNA,a sensitivity and reliability analysis of these parameters through...In order to understand the effect of hardening ductility parameters and softening ductility parameters of the concrete damage plastic model in LS-DYNA,a sensitivity and reliability analysis of these parameters through a convenient cube unit test was conducted. The results showed that the peak strength strain was independent of the hardening ductility parameter DH,but affected by AH,BH,and CH. The softening ductility was mainly related to the softening ductility parameter AS,but not affected by the damage ductility exponent BS. In case that the model with default parameters failed to match the AS-controlled damage softening phase,an optimized model with an AS correction was developed. The corrected model with the AS value of 2 matched well with the code model,and exhibited good feasibility in predicting the stress-strain curve of different grades of concrete. Moreover,the practicability of the corrected model was further validated by the conventional triaxial test. The simulated curve exhibited favorable consistence with the trial curve. Therefore,the model with parameter correction could provide a prospective reference for predicting the mechanical properties of concrete.展开更多
An online systematic error correction is presented and examined as a technique to improve the accuracy of real-time numerical weather prediction, based on the dataset of model errors (MEs) in past intervals. Given t...An online systematic error correction is presented and examined as a technique to improve the accuracy of real-time numerical weather prediction, based on the dataset of model errors (MEs) in past intervals. Given the analyses, the ME in each interval (6 h) between two analyses can be iteratively obtained by introducing an unknown tendency term into the prediction equation, shown in Part I of this two-paper series. In this part, after analyzing the 5-year (2001-2005) GRAPES- GFS (Global Forecast System of the Global and Regional Assimilation and Prediction System) error patterns and evolution, a systematic model error correction is given based on the least-squares approach by firstly using the past MEs. To test the correction, we applied the approach in GRAPES-GFS for July 2009 and January 2010. The datasets associated with the initial condition and SST used in this study were based on NCEP (National Centers for Environmental Prediction) FNL (final) data. The results indicated that the Northern Hemispheric systematically underestimated equator-to-pole geopotential gradient and westerly wind of GRAPES-GFS were largely enhanced, and the biases of temperature and wind in the tropics were strongly reduced. Therefore, the correction results in a more skillful forecast with lower mean bias and root-mean-square error and higher anomaly correlation coefficient.展开更多
The"state and domain phenomenon"emerged at the modeling period of the crowd system,and with the development of cities,communities are extruded by the multivariate space and the crowd system,forming the socia...The"state and domain phenomenon"emerged at the modeling period of the crowd system,and with the development of cities,communities are extruded by the multivariate space and the crowd system,forming the social need of a basic guarantee of community correction. After the expansion of communities,the functional integration period begins,which leads to the period of urban transition,when community and the jurisprudential basis begin to coincide with each other,bringing the community correction model. In the industrialized period,the urban population made great contribution to the community correction of cities. Fromthe perspective of globalization,urban integration will experience the anguish of community correction,and crime and punishment will enter communities of the whole society,forming normal community correction model,so the service systemof community correction begins with the formation of the community-based management system,the crowd-based management range,the fundamental organization structure and the coincidence of the organizing function.展开更多
This letter presents a new chunking method based on Maximum Entropy (ME) model with N-fold template correction model.First two types of machine learning models are described.Based on the analysis of the two models,the...This letter presents a new chunking method based on Maximum Entropy (ME) model with N-fold template correction model.First two types of machine learning models are described.Based on the analysis of the two models,then the chunking model which combines the profits of conditional probability model and rule based model is proposed.The selection of features and rule templates in the chunking model is discussed.Experimental results for the CoNLL-2000 corpus show that this approach achieves impressive accuracy in terms of the F-score:92.93%.Compared with the ME model and ME Markov model,the new chunking model achieves better performance.展开更多
This study presents a simplified multivariate bias correction scheme that is sequentially implemented in the GEOS5 data assimilation system and compared against a control experiment without model bias correction. The ...This study presents a simplified multivariate bias correction scheme that is sequentially implemented in the GEOS5 data assimilation system and compared against a control experiment without model bias correction. The results show considerable improvement in terms of the mean biases of rawinsonde observation-minus-background (OmB) residuals for observed water vapor, wind and temperature variables. The time series spectral analysis shows whitening of bias-corrected OmB residuals, and mean biases for rawinsonde observation-minus-analysis (OmA) are also improved. Some wind and temperature biases in the control experiment near the equatorial tropopause nearly vanish from the bias-corrected experiment. Despite the analysis improvement, the bias correction scheme has only a moderate impact on forecast skill. Significant interaction is also found among quality-control, satellite observation bias correction, and background bias correction, and the latter positively impacts satellite bias correction.展开更多
The problem of population development has always been the key problem of restricting the development of our country. In order to increase the prediction accuracy, we analyze the exponential model, logistic model and c...The problem of population development has always been the key problem of restricting the development of our country. In order to increase the prediction accuracy, we analyze the exponential model, logistic model and continuous model. Also, the improved discrete population development model is provided to control the quantity and improve the quality of population.展开更多
This study aims to address the deviation in downstream tasks caused by inaccurate recognition results when applying Automatic Speech Recognition(ASR)technology in the Air Traffic Control(ATC)field.This paper presents ...This study aims to address the deviation in downstream tasks caused by inaccurate recognition results when applying Automatic Speech Recognition(ASR)technology in the Air Traffic Control(ATC)field.This paper presents a novel cascaded model architecture,namely Conformer-CTC/Attention-T5(CCAT),to build a highly accurate and robust ATC speech recognition model.To tackle the challenges posed by noise and fast speech rate in ATC,the Conformer model is employed to extract robust and discriminative speech representations from raw waveforms.On the decoding side,the Attention mechanism is integrated to facilitate precise alignment between input features and output characters.The Text-To-Text Transfer Transformer(T5)language model is also introduced to handle particular pronunciations and code-mixing issues,providing more accurate and concise textual output for downstream tasks.To enhance the model’s robustness,transfer learning and data augmentation techniques are utilized in the training strategy.The model’s performance is optimized by performing hyperparameter tunings,such as adjusting the number of attention heads,encoder layers,and the weights of the loss function.The experimental results demonstrate the significant contributions of data augmentation,hyperparameter tuning,and error correction models to the overall model performance.On the Our ATC Corpus dataset,the proposed model achieves a Character Error Rate(CER)of 3.44%,representing a 3.64%improvement compared to the baseline model.Moreover,the effectiveness of the proposed model is validated on two publicly available datasets.On the AISHELL-1 dataset,the CCAT model achieves a CER of 3.42%,showcasing a 1.23%improvement over the baseline model.Similarly,on the LibriSpeech dataset,the CCAT model achieves a Word Error Rate(WER)of 5.27%,demonstrating a performance improvement of 7.67%compared to the baseline model.Additionally,this paper proposes an evaluation criterion for assessing the robustness of ATC speech recognition systems.In robustness evaluation experiments based on this criterion,the proposed model demonstrates a performance improvement of 22%compared to the baseline model.展开更多
MODTRAN model was used for the atmospheric correction of one HJ-1B / CCD2 image,and the effect of atmospheric correction was evaluated from the changes of spectral characteristics of typical ground objects,the compari...MODTRAN model was used for the atmospheric correction of one HJ-1B / CCD2 image,and the effect of atmospheric correction was evaluated from the changes of spectral characteristics of typical ground objects,the comparison with the MODIS surface reflectance product,and the effect on normalized differential vegetation index( NDVI). The results show that atmospheric correction eliminated the increase effect in visible bands and the absorption in near-infrared band. Atmospheric correction results and the MODIS surface reflectance product with high accuracy were highly consistent in the reflectance of vegetation,water and residents,and the average error of vegetation was 12.8%. According to the comparison of changing characteristics of NDVI before and after atmospheric correction,it could be found that atmospheric correction had corrected NDVI of mixed pixels and made it more reasonable. NDVI of each kind of ground objects improved,among which NDVI of vegetation increased most greatly,which can help differentiate vegetation from other ground objects. In a word,MODTRAN model has a good effect on atmospheric correction of HJ /CCD images.展开更多
基金Supported by the Fund for Heilongjiang Province Philosophy and Social Sciences Project (08E015)Social Sciences Fund of the Heilongjiang Provincial Education Department (11542014)Scientific Research Fund of Northeast Agricultural University
文摘Heilongjiang is a large agriculture province.Problems of agriculture,rural areas and farmers are urgent to be solved.The development of agriculture needs the support of agricultural credits,because finance is the center of agriculture economy.However,the low comparative advantage in agriculture and pursuit of the capital interests which aggravate the conflicts of supply and demand of agricultural funds.Lacking of fund is the main factor that constrains the development of agricultural economy.In order to analyze the economic effect of agricultural credits on agricultural economy,an error correction model was set up to research the relationship between them,which based on the least square methods.Through the study of the contribution from agricultural credits to total value of agricultural out-put,the empirical evidence for developing the rural financial vigorously was provided,in order to promote the agricultura leconomic development.
文摘Based on the theory of the post method pedagogy and the teaching practice,this paper proposes a new teaching model,the self-correction model,and explains it from the point of view of linking theory.
文摘In view of the learners Chinglish,this paper puts forward a new teaching model-the Self-correction Model and makes an analysis of it from the view of cognitive psychology.
基金funded by the National Natural Science Foundation Science Fund for Youth (Grant No.41405095)the Key Projects in the National Science and Technology Pillar Program during the Twelfth Fiveyear Plan Period (Grant No.2012BAC22B02)the National Natural Science Foundation Science Fund for Creative Research Groups (Grant No.41221064)
文摘Errors inevitably exist in numerical weather prediction (NWP) due to imperfect numeric and physical parameterizations. To eliminate these errors, by considering NWP as an inverse problem, an unknown term in the prediction equations can be estimated inversely by using the past data, which are presumed to represent the imperfection of the NWP model (model error, denoted as ME). In this first paper of a two-part series, an iteration method for obtaining the MEs in past intervals is presented, and the results from testing its convergence in idealized experiments are reported. Moreover, two batches of iteration tests were applied in the global forecast system of the Global and Regional Assimilation and Prediction System (GRAPES-GFS) for July-August 2009 and January-February 2010. The datasets associated with the initial conditions and sea surface temperature (SST) were both based on NCEP (National Centers for Environmental Prediction) FNL (final) data. The results showed that 6th h forecast errors were reduced to 10% of their original value after a 20-step iteration. Then, off-line forecast error corrections were estimated linearly based on the 2-month mean MEs and compared with forecast errors. The estimated error corrections agreed well with the forecast errors, but the linear growth rate of the estimation was steeper than the forecast error. The advantage of this iteration method is that the MEs can provide the foundation for online correction. A larger proportion of the forecast errors can be expected to be canceled out by properly introducing the model error correction into GRAPES-GFS.
基金Supported by the Scientific Research Subject of Department of Education in Hunan Province(10C0556)
文摘By using error correction model, I conduct co-integration analysis on the research of the relationship between the per capita practical consumption and per capita practical disposable income of urban residents in Hunan Province from 1978 to 2009. The results show that there is a co-integration relationship between the per capita practical consumption and the practical per capita disposable income of urban residents, and based on these, the corresponding error correction model is established. Finally, corresponding countermeasures and suggestions are put forward as follows: broaden the income channel of urban residents; create goods consuming environment; perfect socialist security system.
基金Supported by the National Natural Science Foundation of China(10272109)
文摘In order to understand the effect of hardening ductility parameters and softening ductility parameters of the concrete damage plastic model in LS-DYNA,a sensitivity and reliability analysis of these parameters through a convenient cube unit test was conducted. The results showed that the peak strength strain was independent of the hardening ductility parameter DH,but affected by AH,BH,and CH. The softening ductility was mainly related to the softening ductility parameter AS,but not affected by the damage ductility exponent BS. In case that the model with default parameters failed to match the AS-controlled damage softening phase,an optimized model with an AS correction was developed. The corrected model with the AS value of 2 matched well with the code model,and exhibited good feasibility in predicting the stress-strain curve of different grades of concrete. Moreover,the practicability of the corrected model was further validated by the conventional triaxial test. The simulated curve exhibited favorable consistence with the trial curve. Therefore,the model with parameter correction could provide a prospective reference for predicting the mechanical properties of concrete.
基金funded by the National Natural Science Foundation Science Fund for Youth (Grant No.41405095)the Key Projects in the National Science and Technology Pillar Program during the Twelfth Fiveyear Plan Period (Grant No.2012BAC22B02)the National Natural Science Foundation Science Fund for Creative Research Groups (Grant No.41221064)
文摘An online systematic error correction is presented and examined as a technique to improve the accuracy of real-time numerical weather prediction, based on the dataset of model errors (MEs) in past intervals. Given the analyses, the ME in each interval (6 h) between two analyses can be iteratively obtained by introducing an unknown tendency term into the prediction equation, shown in Part I of this two-paper series. In this part, after analyzing the 5-year (2001-2005) GRAPES- GFS (Global Forecast System of the Global and Regional Assimilation and Prediction System) error patterns and evolution, a systematic model error correction is given based on the least-squares approach by firstly using the past MEs. To test the correction, we applied the approach in GRAPES-GFS for July 2009 and January 2010. The datasets associated with the initial condition and SST used in this study were based on NCEP (National Centers for Environmental Prediction) FNL (final) data. The results indicated that the Northern Hemispheric systematically underestimated equator-to-pole geopotential gradient and westerly wind of GRAPES-GFS were largely enhanced, and the biases of temperature and wind in the tropics were strongly reduced. Therefore, the correction results in a more skillful forecast with lower mean bias and root-mean-square error and higher anomaly correlation coefficient.
文摘The"state and domain phenomenon"emerged at the modeling period of the crowd system,and with the development of cities,communities are extruded by the multivariate space and the crowd system,forming the social need of a basic guarantee of community correction. After the expansion of communities,the functional integration period begins,which leads to the period of urban transition,when community and the jurisprudential basis begin to coincide with each other,bringing the community correction model. In the industrialized period,the urban population made great contribution to the community correction of cities. Fromthe perspective of globalization,urban integration will experience the anguish of community correction,and crime and punishment will enter communities of the whole society,forming normal community correction model,so the service systemof community correction begins with the formation of the community-based management system,the crowd-based management range,the fundamental organization structure and the coincidence of the organizing function.
基金Supported by National Natural Science Foundation of China (No.60504021).
文摘This letter presents a new chunking method based on Maximum Entropy (ME) model with N-fold template correction model.First two types of machine learning models are described.Based on the analysis of the two models,then the chunking model which combines the profits of conditional probability model and rule based model is proposed.The selection of features and rule templates in the chunking model is discussed.Experimental results for the CoNLL-2000 corpus show that this approach achieves impressive accuracy in terms of the F-score:92.93%.Compared with the ME model and ME Markov model,the new chunking model achieves better performance.
文摘This study presents a simplified multivariate bias correction scheme that is sequentially implemented in the GEOS5 data assimilation system and compared against a control experiment without model bias correction. The results show considerable improvement in terms of the mean biases of rawinsonde observation-minus-background (OmB) residuals for observed water vapor, wind and temperature variables. The time series spectral analysis shows whitening of bias-corrected OmB residuals, and mean biases for rawinsonde observation-minus-analysis (OmA) are also improved. Some wind and temperature biases in the control experiment near the equatorial tropopause nearly vanish from the bias-corrected experiment. Despite the analysis improvement, the bias correction scheme has only a moderate impact on forecast skill. Significant interaction is also found among quality-control, satellite observation bias correction, and background bias correction, and the latter positively impacts satellite bias correction.
文摘The problem of population development has always been the key problem of restricting the development of our country. In order to increase the prediction accuracy, we analyze the exponential model, logistic model and continuous model. Also, the improved discrete population development model is provided to control the quantity and improve the quality of population.
基金This study was co-supported by the National Key R&D Program of China(No.2021YFF0603904)National Natural Science Foundation of China(U1733203)Safety Capacity Building Project of Civil Aviation Administration of China(TM2019-16-1/3).
文摘This study aims to address the deviation in downstream tasks caused by inaccurate recognition results when applying Automatic Speech Recognition(ASR)technology in the Air Traffic Control(ATC)field.This paper presents a novel cascaded model architecture,namely Conformer-CTC/Attention-T5(CCAT),to build a highly accurate and robust ATC speech recognition model.To tackle the challenges posed by noise and fast speech rate in ATC,the Conformer model is employed to extract robust and discriminative speech representations from raw waveforms.On the decoding side,the Attention mechanism is integrated to facilitate precise alignment between input features and output characters.The Text-To-Text Transfer Transformer(T5)language model is also introduced to handle particular pronunciations and code-mixing issues,providing more accurate and concise textual output for downstream tasks.To enhance the model’s robustness,transfer learning and data augmentation techniques are utilized in the training strategy.The model’s performance is optimized by performing hyperparameter tunings,such as adjusting the number of attention heads,encoder layers,and the weights of the loss function.The experimental results demonstrate the significant contributions of data augmentation,hyperparameter tuning,and error correction models to the overall model performance.On the Our ATC Corpus dataset,the proposed model achieves a Character Error Rate(CER)of 3.44%,representing a 3.64%improvement compared to the baseline model.Moreover,the effectiveness of the proposed model is validated on two publicly available datasets.On the AISHELL-1 dataset,the CCAT model achieves a CER of 3.42%,showcasing a 1.23%improvement over the baseline model.Similarly,on the LibriSpeech dataset,the CCAT model achieves a Word Error Rate(WER)of 5.27%,demonstrating a performance improvement of 7.67%compared to the baseline model.Additionally,this paper proposes an evaluation criterion for assessing the robustness of ATC speech recognition systems.In robustness evaluation experiments based on this criterion,the proposed model demonstrates a performance improvement of 22%compared to the baseline model.
基金Supported by National Natural Science Foundation of China(41171336)
文摘MODTRAN model was used for the atmospheric correction of one HJ-1B / CCD2 image,and the effect of atmospheric correction was evaluated from the changes of spectral characteristics of typical ground objects,the comparison with the MODIS surface reflectance product,and the effect on normalized differential vegetation index( NDVI). The results show that atmospheric correction eliminated the increase effect in visible bands and the absorption in near-infrared band. Atmospheric correction results and the MODIS surface reflectance product with high accuracy were highly consistent in the reflectance of vegetation,water and residents,and the average error of vegetation was 12.8%. According to the comparison of changing characteristics of NDVI before and after atmospheric correction,it could be found that atmospheric correction had corrected NDVI of mixed pixels and made it more reasonable. NDVI of each kind of ground objects improved,among which NDVI of vegetation increased most greatly,which can help differentiate vegetation from other ground objects. In a word,MODTRAN model has a good effect on atmospheric correction of HJ /CCD images.