scholarly journals An Adaptive Spatial Resolution Method Based on the ST-ResNet Model for Hourly Property Crime Prediction

2021 ◽  
Vol 10 (5) ◽  
pp. 314
Author(s):  
Hong Zhang ◽  
Jie Zhang ◽  
Zengli Wang ◽  
Hao Yin
Keyword(s):  
Spatial Resolution ◽  
Predictive Accuracy ◽  
Property Crime ◽  
Strong Relationship ◽  
Weather Data ◽  
Resolution Method ◽  
Crime Prediction ◽  
Big City ◽  
Crime Risk ◽  
Adaptive Spatial Resolution

Effective predictive policing can guide police patrols and deter crime. Hourly crime prediction is expected to save police time. The selection of spatial resolution is important due to its strong relationship with the accuracy of crime prediction. In this paper, we propose an adaptive spatial resolution method to select the best spatial resolution for hourly crime prediction. The ST-ResNet model is applied to predict crime risk, with historical crime data and weather data as predictive variables. A predictive accuracy index (PAI) is used to evaluate the accuracy of the results. Data on property crimes committed in Suzhou, a big city in China, were selected as the research data. The experiment results indicate that a 2.4 km spatial resolution leads to the best performance for crime prediction. The adaptive spatial resolution method can be used to guide police deployment.

scholarly journals Comparison of the spatial patterns of schistosomiasis in Zimbabwe at two points in time, spaced twenty-nine years apart: is climate variability of importance?

2017 ◽  
Vol 12 (1) ◽  
Author(s):  
Ulrik B. Pedersen ◽  
Dimitrios-Alexios Karagiannis-Voules ◽  
Nicholas Midzi ◽  
Tkafira Mduluza ◽  
Samson Mukaratirwa ◽  
...  
Keyword(s):  
Climate Change ◽  
Geographical Distribution ◽  
Predictive Accuracy ◽  
Weather Data ◽  
Geostatistical Model ◽  
Prevalence Data ◽  
Time Period ◽  
Long Time ◽  
Potential Risk Factors ◽  
The Impact

Temperature, precipitation and humidity are known to be important factors for the development of schistosome parasites as well as their intermediate snail hosts. Climate therefore plays an important role in determining the geographical distribution of schistosomiasis and it is expected that climate change will alter distribution and transmission patterns. Reliable predictions of distribution changes and likely transmission scenarios are key to efficient schistosomiasis intervention-planning. However, it is often difficult to assess the direction and magnitude of the impact on schistosomiasis induced by climate change, as well as the temporal transferability and predictive accuracy of the models, as prevalence data is often only available from one point in time. We evaluated potential climate-induced changes on the geographical distribution of schistosomiasis in Zimbabwe using prevalence data from two points in time, 29 years apart; to our knowledge, this is the first study investigating this over such a long time period. We applied historical weather data and matched prevalence data of two schistosome species (<em>Schistosoma haematobium</em> and <em>S. mansoni</em>). For each time period studied, a Bayesian geostatistical model was fitted to a range of climatic, environmental and other potential risk factors to identify significant predictors that could help us to obtain spatially explicit schistosomiasis risk estimates for Zimbabwe. The observed general downward trend in schistosomiasis prevalence for Zimbabwe from 1981 and the period preceding a survey and control campaign in 2010 parallels a shift towards a drier and warmer climate. However, a statistically significant relationship between climate change and the change in prevalence could not be established.

scholarly journals Near Real-Time Biophysical Rice (Oryza sativa L.) Yield Estimation to Support Crop Insurance Implementation in India

Agronomy ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1674
Author(s):  
Ponraj Arumugam ◽  
Abel Chemura ◽  
Bernhard Schauberger ◽  
Christoph Gornott
Keyword(s):  
Oryza Sativa ◽  
Real Time ◽  
Spatial Resolution ◽  
Yield Loss ◽  
Smallholder Farmers ◽  
Oryza Sativa L ◽  
Crop Insurance ◽  
Weather Data ◽  
Insurance Scheme ◽  
Agricultural Income

Immediate yield loss information is required to trigger crop insurance payouts, which are important to secure agricultural income stability for millions of smallholder farmers. Techniques for monitoring crop growth in real-time and at 5 km spatial resolution may also aid in designing price interventions or storage strategies for domestic production. In India, the current government-backed PMFBY (Pradhan Mantri Fasal Bima Yojana) insurance scheme is seeking such technologies to enable cost-efficient insurance premiums for Indian farmers. In this study, we used the Decision Support System for Agrotechnology Transfer (DSSAT) to estimate yield and yield anomalies at 5 km spatial resolution for Kharif rice (Oryza sativa L.) over India between 2001 and 2017. We calibrated the model using publicly available data: namely, gridded weather data, nutrient applications, sowing dates, crop mask, irrigation information, and genetic coefficients of staple varieties. The model performance over the model calibration years (2001–2015) was exceptionally good, with 13 of 15 years achieving more than 0.7 correlation coefficient (r), and more than half of the years with above 0.75 correlation with observed yields. Around 52% (67%) of the districts obtained a relative Root Mean Square Error (rRMSE) of less than 20% (25%) after calibration in the major rice-growing districts (>25% area under cultivation). An out-of-sample validation of the calibrated model in Kharif seasons 2016 and 2017 resulted in differences between state-wise observed and simulated yield anomalies from –16% to 20%. Overall, the good ability of the model in the simulations of rice yield indicates that the model is applicable in selected states of India, and its outputs are useful as a yield loss assessment index for the crop insurance scheme PMFBY.

Derivation of plasmonic resonances in the Fourier modal method with adaptive spatial resolution and matched coordinates

2011 ◽  
Vol 28 (2) ◽  
pp. 238 ◽  
Author(s):  
Thomas Weiss ◽  
Nikolay A. Gippius ◽  
Sergei G. Tikhodeev ◽  
Gérard Granet ◽  
Harald Giessen
Keyword(s):  
Spatial Resolution ◽  
Fourier Modal Method ◽  
Modal Method ◽  
Adaptive Spatial Resolution

Applied-Information Technology in Power System with Short-Term Load Forecasting Based on SPSS and BP Neural Network

2014 ◽  
Vol 1022 ◽  
pp. 241-244 ◽  
Author(s):  
Jian Ping Chen ◽  
Chang Hao Xia ◽  
Zhi Peng Tian
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Predictive Accuracy ◽  
Load Forecasting ◽  
Influence Factors ◽  
Principal Component ◽  
Weather Data ◽  
Power Load ◽  
Bp Neural Network Model ◽  
Bp Model

In the study of power load forecasting, the factors influencing power load have data redundancy and data nonlinearity. The traditional load forecasting methods can’t eliminate redundant or nonlinear law between data, which result in reduced accuracy. In order to improve the predictive accuracy of power load, a prediction model based on BP neural network and SPSS (SPSS-BP) is established. The paper first analyzes the correlation and principal component of influence factors of electric power load, which eliminates the redundancy between various factors, accelerates the speed of BP neural network forecasting and improves predictive accuracy; then model the processed data and forecast through the BP neural network model. One-month weather data and load data of Yichang city have been confirmatory tested and analyzed through application of SPSS-BP model. The results show that SPSS-BP model significantly improves the accuracy, verify the feasibility and effectiveness of the model.

scholarly journals Matched coordinates and adaptive spatial resolution in the Fourier modal method

2009 ◽  
Vol 17 (10) ◽  
pp. 8051 ◽  
Author(s):  
Thomas Weiss ◽  
Gérard Granet ◽  
Nikolay A. Gippius ◽  
Sergei G. Tikhodeev ◽  
Harald Giessen
Keyword(s):  
Spatial Resolution ◽  
Fourier Modal Method ◽  
Modal Method ◽  
Adaptive Spatial Resolution
Sign in / Sign up

Export Citation Format

Share Document