Prediction of sunflower grain yield under normal and salinity stress by RBF, MLP and, CNN models

Foliage application of 5-aminolevulinic acid alleviates drought stress in sunflower (Helianthus annuus L.) through improving stay green and antioxidant enzymes activities

(2021) Ahmad Sher et al.   ACTA PHYSIOLOGIAE PLANTARUM

Evaluation of sunflower (Helianthus annuus L.) genotypes for quantitative traits and character association of seed yield and yield components at Oromia region, Ethiopia

(2021) Tarekegn Makiso Lagiso et al.   EUPHYTICA

Application of artificial neural network and support vector regression in predicting mass of ber fruits (Ziziphus mauritiana Lamk.) based on fruit axial dimensions

(2021) Mahmoud Abdel-Sattar et al.   PLoS One

Prediction of Rice Yield in East China Based on Climate and Agronomic Traits Data Using Artificial Neural Networks and Partial Least Squares Regression

(2021) Yuming Guo et al.   Agronomy-Basel

Application of machine learning and genetic optimization algorithms for modeling and optimizing soybean yield using its component traits

(2021) Mohsen Yoosefzadeh-Najafabadi et al.   PLoS One

A deep learning model for predicting river flood depth and extent

(2021) Hossein Hosseiny   ENVIRONMENTAL MODELLING & SOFTWARE

Estimating and understanding crop yields with explainable deep learning in the Indian Wheat Belt

(2020) Aleksandra Wolanin et al.   Environmental Research Letters

A CNN-RNN Framework for Crop Yield Prediction

(2020) Saeed Khaki et al.   Frontiers in Plant Science

Deep learning convolutional neural network in rainfall–runoff modelling

(2020) Song Pham Van et al.   JOURNAL OF HYDROINFORMATICS

Wheat crop yield prediction using new activation functions in neural network

(2020) Shital H. Bhojani et al.   NEURAL COMPUTING & APPLICATIONS

Effect of drought stress on agro-morphological traits in sunflower (Helianthus annuus L.) genotypes and identification of informative ISSR markers

(2020) S. P. Darbani et al.   Plant Genetic Resources-Characterization and Utilization

Winter Wheat Yield Prediction at County Level and Uncertainty Analysis in Main Wheat-Producing Regions of China with Deep Learning Approaches

(2020) Xinlei Wang et al.   Remote Sensing

A deep learning approach for hydrological time-series prediction: A case study of Gilgit river basin

(2020) Dostdar Hussain et al.   Earth Science Informatics

1D convolutional neural networks and applications: A survey

(2020) Serkan Kiranyaz et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Simple model based on artificial neural network for early prediction and simulation winter rapeseed yield

(2019) Gniewko Niedbała   Journal of Integrative Agriculture

Deep Convolutional Neural Network for Flood Extent Mapping Using Unmanned Aerial Vehicles Data

(2019) Asmamaw Gebrehiwot et al.   SENSORS

Towards Predictive Modeling of Sorghum Biomass Yields Using Fraction of Absorbed Photosynthetically Active Radiation Derived from Sentinel-2 Satellite Imagery and Supervised Machine Learning Techniques

(2019) Ephrem Habyarimana et al.   Agronomy-Basel

Multicriteria Prediction and Simulation of Winter Wheat Yield Using Extended Qualitative and Quantitative Data Based on Artificial Neural Networks

(2019) Gniewko Niedbała et al.   Applied Sciences-Basel

Modulation in growth, photosynthetic pigments, gas exchange attributes and inorganic ions in sunflower (Helianthus annuus l.) by strigolactones (GR24) achene priming under saline conditions

(2019) Yasmin Sarwar et al.   PAKISTAN JOURNAL OF BOTANY

Modeling the seed yield of Ajowan ( Trachyspermum ammi L.) using artificial neural network and multiple linear regression models

(2018) Mohsen Niazian et al.   INDUSTRIAL CROPS AND PRODUCTS

Modeling Oil Content of Sesame (Sesamum indicum L.) Using Artificial Neural Network and Multiple Linear Regression Approaches

(2018) Moslem Abdipour et al.   JOURNAL OF THE AMERICAN OIL CHEMISTS SOCIETY

Machine learning methods for crop yield prediction and climate change impact assessment in agriculture

(2018) Andrew Crane-Droesch   Environmental Research Letters

Preliminary evidence of the associations between DNA markers and morphological characters in sunflower under natural and salt stress conditions

(2018) Soheila Ahmadpour et al.   Zemdirbyste-Agriculture

Artificial neural networks and multiple linear regression as potential methods for modeling seed yield of safflower (Carthamus tinctorius L.)

(2018) Moslem Abdipour et al.   INDUSTRIAL CROPS AND PRODUCTS

Cooperative learning for radial basis function networks using particle swarm optimization

(2016) Alex Alexandridis et al.   APPLIED SOFT COMPUTING

Prediction of biological and grain yield of barley using multiple regression and artificial neural network models

(2016) Marzieh Mokarram et al.   Australian Journal of Crop Science

Prediction of output energies for broiler production using linear regression, ANN (MLP, RBF), and ANFIS models

(2016) Sama Amid et al.   Environmental Progress & Sustainable Energy

Seed yield prediction of sesame using artificial neural network

(2015) Samad Emamgholizadeh et al.   EUROPEAN JOURNAL OF AGRONOMY

Within-season yield prediction with different nitrogen inputs under rain-fed condition using CERES-Wheat model in the northwest of China

(2015) Zhengpeng Li et al.   JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE

Deep learning

(2015) Yann LeCun et al.   NATURE

COMPARISON OF OSMOTIC REGULATION IN DEHYDRATION- AND SALINITY-STRESSED SUNFLOWER SEEDLINGS

(2010) Qingsong Zheng et al.   JOURNAL OF PLANT NUTRITION

A fast multi-output RBF neural network construction method

(2010) Dajun Du et al.   NEUROCOMPUTING

Artificial neural networks as an alternative to the traditional statistical methodology in plant research

(2009) J. Gago et al.   JOURNAL OF PLANT PHYSIOLOGY

Mechanisms of Salinity Tolerance

(2008) Rana Munns et al.   Annual Review of Plant Biology

Predict soil texture distributions using an artificial neural network model

(2008) Zhengyong Zhao et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Predicting average regional yield and production of wheat in the Argentine Pampas by an artificial neural network approach

(2008) R. Alvarez   EUROPEAN JOURNAL OF AGRONOMY

Artificial neural network models for predicting soil thermal resistivity

(2008) Yusuf Erzin et al.   INTERNATIONAL JOURNAL OF THERMAL SCIENCES

Modeling of wheat soaking using two artificial neural networks (MLP and RBF)

(2008) M. Kashaninejad et al.   JOURNAL OF FOOD ENGINEERING

Prediction of process and product parameters in an orange juice spray dryer using artificial neural networks

(2007) G.R. Chegini et al.   JOURNAL OF FOOD ENGINEERING