scholarly journals Study On Multiscale-Multivariate Attribution Analysis and Prediction of Urban Rainstorm Flood

2021 ◽  
Author(s):  
Jinping Zhang ◽  
Yuhao Wang
Keyword(s):  
Prediction Model ◽  
Influencing Factors ◽  
Underlying Surface ◽  
Good Prediction ◽  
Attribution Analysis ◽  
Flood Volume ◽  
Multivariate Prediction ◽  
Micro Level ◽  
Relative Errors ◽  
The Impact

Abstract In order to explore the impact of the changing environment on urban rainstorm flood, and reveal the relationship between flood volume and its influencing factors at the micro level, the rainfall and flood volume are decomposed by the wavelet analysis method to perform the multiscale attribution analysis. Then the multiscale-multivariate prediction model of urban rainstorm flood is constructed in the Jialu River Basin in Zhengzhou city of China. The results show that the main influencing factors of flood volume are rainfall and underlying surface, where the latter causes the mutation of flood volume in 1994 and 2005. At the micro level, there is a constant linear relationship between rainfall and flood volume in d1, d2 and d3, while the impact of underlying surface on flood volume is mainly reflected in a3. The multiscale-multivariate prediction model has a good simulation effect on the flood volume of the first 45 rainstorm floods, NSE, R2 and Re are 0.966, 0.964 and 10.80%, respectively. Moreover, the model also has a good prediction effect, and the relative errors between the predicted and observed flood volume of 46th~50th rainstorm floods are all less than 20%.

scholarly journals Multi-scale flood prediction based on GM (1,2)-fuzzy weighted Markov and wavelet analysis

2021 ◽  
Author(s):  
Jinping Zhang ◽  
Yuhao Wang ◽  
Yong Zhao ◽  
Hongyuan Fang
Keyword(s):  
Wavelet Analysis ◽  
Flood Prediction ◽  
Forecasting Accuracy ◽  
Multi Scale ◽  
Flood Volume ◽  
Micro Level ◽  
Relative Errors ◽  
The Impact ◽  
The Relationship ◽  
Markov Method

AbstractIn order to forecast flood accurately and reveal the relationship between rainstorm and flood at the micro level, a model which combines wavelet analysis, GM (1,2) and fuzzy weighted Markov is built. Taking the Jialu River of Zhengzhou City in China as study area, the GM (1,2) model is constructed between the components of rainfall and flood volume by wavelet decomposition to connect the two variables, then a fuzzy weighted Markov method is introduced to correct the predicted component of flood volume. The corrected results are superimposed to obtain the predicted value of flood. To verify the reliability of the model, the maximum daily, 3-, 5- and 7-day flood volume of the next five floods in Zhongmu and Jiangang hydrological stations are predicted in turn. The results show that the multi-scale flood forecasting model has high overall forecasting accuracy, with the average relative errors all less than 10%. The forecasting accuracy of maximum five-day flood volume is higher than other periods. On the micro level, the results indicate that the fluctuation trend and period of rainfall-flood volume in d1, d2 and d3 are basically the same. Among the components of forecasted flood, the impact of rainfall on flood volume is most significant in the d3 component.

scholarly journals Establishment of Landslide Groundwater Level Prediction Model Based on GA-SVM and Influencing Factor Analysis

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 845 ◽  
Author(s):  
Ying Cao ◽  
Kunlong Yin ◽  
Chao Zhou ◽  
Bayes Ahmed
Keyword(s):  
Prediction Model ◽  
Influencing Factors ◽  
Groundwater Level ◽  
Influencing Factor ◽  
Hybrid Genetic Algorithm ◽  
Early Warning Systems ◽  
Three Gorges Reservoir Area ◽  
Support Vector ◽  
Single Factor ◽  
The Impact

The monitoring and prediction of the landslide groundwater level is a crucial part of landslide early warning systems. In this study, Tangjiao landslide in the Three Gorges Reservoir area (TGRA) in China was taken as a case study. Three groundwater level monitoring sensors were installed in different locations of the landslide. The monitoring data indicated that the fluctuation of groundwater level is significantly consistent with rainfall and reservoir level in time, but there is a lag. In addition, there is a spatial difference in the impact of reservoir levels on the landslide groundwater level. The data of two monitoring locations were selected for establishing the prediction model of groundwater. Combined with the qualitative and quantitative analysis, the influencing factors were selected, respectively, to establish the hybrid Genetic Algorithm-Support Vector Machine (GA-SVM) prediction model. The single-factor GA-SVM without considering influencing factors and the backpropagation neural network (BPNN) model were adopted to make comparisons. The results showed that the multi-factor GA-SVM performed the best, followed by multi-factor BPNN and single-factor GA-SVM. We found that the prediction accuracy can be improved by considering the influencing factor. The proposed GA-SVM model combines the advantages of each algorithm; it can effectively construct the response relationship between groundwater level fluctuations and influencing factors. Above all, the multi-factor GA-SVM is an effective method for the prediction of landslides groundwater in the TGRA.

scholarly journals Dynamic Route Choice Prediction Model Based on Connected Vehicle Guidance Characteristics

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Jiangfeng Wang ◽  
Jiarun Lv ◽  
Chao Wang ◽  
Zhiqi Zhang
Keyword(s):  
Prediction Model ◽  
Information Acquisition ◽  
Route Choice ◽  
Route Planning ◽  
Calibration Model ◽  
Good Prediction ◽  
Connected Vehicle ◽  
Vehicle Guidance ◽  
Simulation Scenario ◽  
The Impact

A route choice prediction model is proposed considering the connected vehicle guidance characteristics. This model is proposed to prevent the delay in the release of guidance information and route planning due to inaccurate timing predictions of the traditional guidance systems. Based on the analysis of the impact of different connected vehicle (CV) guidance strategies on traffic flow, an indexes system for CV guidance characteristics is presented. Selecting five characteristic indexes, a route choice prediction model is designed using the logistic model. A simulation scenario is established by programming different agents for controlling the flow of vehicles and for information acquisition and transmission. The prediction model is validated using the simulation scenario, and the simulation results indicate that the characteristic indexes have a significant influence on the probability of choosing a particular route. The average root mean square error (RMSE) of the prediction model is 3.19%, which indicates that the calibration model shows a good prediction performance. In the implementation of CV guidance, the penetration rate can be considered an optional index in the adjustment of the guidance effect.

scholarly journals The Impact of Micro-Level Influencing Factors on Home Value: A Housing Price-Rent Comparison

2018 ◽  
Vol 10 (12) ◽  
pp. 4343 ◽  
Author(s):  
Nana Cui ◽  
Hengyu Gu ◽  
Tiyan Shen ◽  
Changchun Feng
Keyword(s):  
Influencing Factors ◽  
School Quality ◽  
School Attendance ◽  
Housing Prices ◽  
Housing Price ◽  
Living Environment ◽  
Hedonic Price ◽  
Micro Level ◽  
Employment Center ◽  
The Impact

The housing sales market in China has flourished and gained considerable interest, while the housing rental market has lagged behind and been ignored over the past two decades. With the acceleration of urbanization, the housing rental demand is rising rapidly. Exploring and comparing the influencing factors on housing sale prices and rental prices has significance for sustainable urban planning and management. Using house purchase transaction and rent transaction data in 2017, as well as the average housing price and rent data in 2016 in Beijing, China, this paper compares the spatial distribution and it employs the hedonic price model and quantile regression model to quantify the average and distributional effects of micro-level influencing factors on housing prices and housing rents. Results show that housing prices and housing rents both have a decentralized distribution with multiple centers, but rents of residential communities with high housing prices may not necessarily be high. Both homeowners and renters prefer properties with good structural, locational, and neighborhood characteristics, as well as a good school attendance zone, whereas they still differ in terms of preferences. Homeowners prefer a higher-quality living environment. Renters are more concerned with proximity to an employment center and public transit convenience. Moreover, the price premium of school quality for homeowners exceeds the premium for renters. Higher-priced homeowners or renters differ in the preferences from lower-priced homeowners or renters. Higher-priced homeowners and higher-priced renters are more willing to live in property with a larger number of bedrooms, proximity to a major employment center, park, or school, as well as a location in a school attendance zone with higher school quality.

Is technological change a devourer of jobs?

2017 ◽  
pp. 111-140 ◽  
Author(s):  
R. Kapeliushnikov
Keyword(s):  
Technological Change ◽  
Critical Analysis ◽  
New Technologies ◽  
Employment Growth ◽  
Foreseeable Future ◽  
Employment Effects ◽  
Technological Unemployment ◽  
Micro Level ◽  
Task Sets ◽  
The Impact

The paper provides a critical analysis of the idea of technological unemployment. The overview of the existing literature on the employment effects of technological change shows that on the micro-level there exists strong and positive relationship between innovations and employment growth in firms; on the sectoral level this correlation becomes ambiguous; on the macro-level the impact of new technologies seems to be positive or neutral. This implies that fears of explosive growth of technological unemployment in the foreseeable future are exaggerated. Our analysis further suggests that new technologies affect mostly the structure of employment rather than its level. Additionally we argue that automation and digitalisation would change mostly task sets within particular occupations rather than distribution of workers by occupations.

THE MODEL FOR MANAGING INVESTMENTS IN THE MOSCOW ENVIRONMENT BASED ON A POWER REGRESSION EQUATION

2020 ◽  
Vol 2 (7) ◽  
pp. 91-99
Author(s):  
E. V. KOSTYRIN ◽  
◽  
M. S. SINODSKAYA ◽  
Keyword(s):  
Solid Waste ◽  
Influencing Factors ◽  
Pair Correlation ◽  
Approximation Error ◽  
Regression Equation ◽  
Regression Equations ◽  
The Impact ◽  
The Relationship ◽  
Average Approximation ◽  
Average Approximation Error

The article analyzes the impact of certain factors on the volume of investments in the environment. Regression equations describing the relationship between the volume of investment in the environment and each of the influencing factors are constructed, the coefficients of the Pearson pair correlation between the dependent variable and the influencing factors, as well as pairwise between the influencing factors, are calculated. The average approximation error for each regression equation is determined. A correlation matrix is constructed and a conclusion is made. The developed econometric model is implemented in the program of separate collection of municipal solid waste (MSW) in Moscow. The efficiency of the model of investment management in the environment is evaluated on the example of the growth of planned investments in the activities of companies specializing in the export and processing of solid waste.

scholarly journals Tailored Prediction Model of Survival after Liver Transplantation for Hepatocellular Carcinoma

2021 ◽  
Vol 10 (13) ◽  
pp. 2869
Author(s):  
Indah Jamtani ◽  
Kwang-Woong Lee ◽  
Yun-Hee Choi ◽  
Young-Rok Choi ◽  
Jeong-Moo Lee ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Transplantation ◽  
Prediction Model ◽  
Risk Group ◽  
Significant Risk ◽  
Risk Scores ◽  
Accurate Information ◽  
Survival Prediction ◽  
Good Prediction ◽  
Recurrence Rates

This study aimed to create a tailored prediction model of hepatocellular carcinoma (HCC)-specific survival after transplantation based on pre-transplant parameters. Data collected from June 2006 to July 2018 were used as a derivation dataset and analyzed to create an HCC-specific survival prediction model by combining significant risk factors. Separate data were collected from January 2014 to June 2018 for validation. The prediction model was validated internally and externally. The data were divided into three groups based on risk scores derived from the hazard ratio. A combination of patient demographic, laboratory, radiological data, and tumor-specific characteristics that showed a good prediction of HCC-specific death at a specific time (t) were chosen. Internal and external validations with Uno’s C-index were 0.79 and 0.75 (95% confidence interval (CI) 0.65–0.86), respectively. The predicted survival after liver transplantation for HCC (SALT) at a time “t” was calculated using the formula: [1 − (HCC-specific death(t’))] × 100. The 5-year HCC-specific death and recurrence rates in the low-risk group were 2% and 5%; the intermediate-risk group was 12% and 14%, and in the high-risk group were 71% and 82%. Our HCC-specific survival predictor named “SALT calculator” could provide accurate information about expected survival tailored for patients undergoing transplantation for HCC.

scholarly journals Aphid–Plant–Phytovirus Pathosystems: Influencing Factors from Vector Behaviour to Virus Spread

Agriculture ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 502
Author(s):  
Junior Corneille Fingu-Mabola ◽  
Frédéric Francis
Keyword(s):  
Influencing Factors ◽  
Virus Transmission ◽  
Physical Factors ◽  
Factors Affecting ◽  
Vector Borne Diseases ◽  
Vector Behaviour ◽  
Crop Fields ◽  
Host Seeking ◽  
The Impact ◽  
Vector Efficiency

Aphids are responsible for the spread of more than half of the known phytovirus species. Virus transmission within the plant–aphid–phytovirus pathosystem depends on vector mobility which allows the aphid to reach its host plant and on vector efficiency in terms of ability to transmit phytoviruses. However, several other factors can influence the phytoviruses transmission process and have significant epidemiological consequences. In this review, we aimed to analyse the aphid behaviours and influencing factors affecting phytovirus spread. We discussed the impact of vector host-seeking and dispersal behaviours mostly involved in aphid-born phytovirus spread but also the effect of feeding behaviours and life history traits involved in plant–aphid–phytovirus relationships on vector performances. We also noted that these behaviours are influenced by factors inherent to the interactions between pathosystem components (mode of transmission of phytoviruses, vector efficiency, plant resistance, …) and several biological, biochemical, chemical or physical factors related to the environment of these pathosystem components, most of them being manipulated as means to control vector-borne diseases in the crop fields.

Transnational logic of gratitude: Marriage migrants’ narratives on marital satisfaction in South Korea

2021 ◽  
pp. 026858092199469
Author(s):  
Gowoon Jung
Keyword(s):  
Marital Satisfaction ◽  
Cognitive Processes ◽  
Gender Ideology ◽  
Marriage Migrants ◽  
Sociology Of Emotion ◽  
Micro Level ◽  
And Gender ◽  
The Impact ◽  
Depth Interviews

Scholarship on marriage migrants has examined the impact of class and gender ideology of receiving countries on their marital satisfaction. However, little is known about the role of transnational background in explaining women’s feelings of gratitude for husbands. Drawing on qualitative in-depth interviews with marriage migrant women residing in the eastern side of Seoul, Korea, this article explores the micro-level cognitive processes in understanding women’s gratitude for their husbands. Categorizing marriage migrants into two groups, ‘gratified’ and ‘ungratified’ wives, the author demonstrates how the gratified wives’ feelings of contentment is mediated by their active comparison of Korean husbands with local men in their homelands, and how these viewpoints conversely affect their aspirations for return. Bringing the sociology of emotion into an explanation of marriage migrants’ marital satisfaction, this study aims to develop a transnational frame of reference as an underlying dynamic for comprehending marriage migrants’ (in)gratitude.

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