Crop yield prediction using aggregated rainfall-based modular artificial neural networks and support vector regression
出版年份 2019 全文链接
标题
Crop yield prediction using aggregated rainfall-based modular artificial neural networks and support vector regression
作者
关键词
Agriculture, Crop modeling, Machine learning, Support vector regression, Yield prediction
出版物
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
Volume -, Issue -, Pages -
出版商
Springer Science and Business Media LLC
发表日期
2019-08-21
DOI
10.1007/s10668-019-00445-x
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Comparing the Performance of Dynamical and Statistical Downscaling on Historical Run Precipitation Data over a Semi-Arid Region
- (2019) Nasrin Salehnia et al. Asia-Pacific Journal of Atmospheric Sciences
- Prediction of effective climate change indicators using statistical downscaling approach and impact assessment on pearl millet ( Pennisetum glaucum L.) yield through Genetic Algorithm in Punjab, Pakistan
- (2018) Asmat Ullah et al. ECOLOGICAL INDICATORS
- Can current crop models be used in the phenotyping era for predicting the genetic variability of yield of plants subjected to drought or high temperature?
- (2014) Boris Parent et al. JOURNAL OF EXPERIMENTAL BOTANY
- Assimilation of remotely sensed soil moisture and vegetation with a crop simulation model for maize yield prediction
- (2013) Amor V.M. Ines et al. REMOTE SENSING OF ENVIRONMENT
- Efficient stabilization of crop yield prediction in the Canadian Prairies
- (2011) Luke Bornn et al. AGRICULTURAL AND FOREST METEOROLOGY
- Are regional climate models relevant for crop yield prediction in West Africa?
- (2011) Pascal Oettli et al. Environmental Research Letters
- A Fuzzy System Constructed by Rule Generation and Iterative Linear SVR for Antecedent and Consequent Parameter Optimization
- (2011) Chia-Feng Juang et al. IEEE TRANSACTIONS ON FUZZY SYSTEMS
- On the use of statistical models to predict crop yield responses to climate change
- (2010) David B. Lobell et al. AGRICULTURAL AND FOREST METEOROLOGY
- Climate change impact assessment: the role of climate extremes in crop yield simulation
- (2010) M. Moriondo et al. CLIMATIC CHANGE
- Prediction of rainfall time series using modular artificial neural networks coupled with data-preprocessing techniques
- (2010) C.L. Wu et al. JOURNAL OF HYDROLOGY
- Application of Vegetation Indices for Agricultural Crop Yield Prediction Using Neural Network Techniques
- (2010) Sudhanshu Sekhar Panda et al. Remote Sensing
- Climate change impacts on crop yield, crop water productivity and food security – A review
- (2009) Yinhong Kang et al. Progress in Natural Science-Materials International
- Non-linear variable selection for artificial neural networks using partial mutual information
- (2008) Robert J. May et al. ENVIRONMENTAL MODELLING & SOFTWARE
- The future of biocuration
- (2008) Doug Howe et al. NATURE
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now