A NEURAL NETWORK FOR SETTING TARGET CORN YIELDS
Cited by (134)
Items 101–134 of 134
- Evaluation of indirect and direct scoring methods to relate biochemical soil quality indicators to ecosystem servicesYushu Xia, Michelle M. Wander · 2021 · Soil Science Society of America Journal
- Comparison of mapping soybean areas in Brazil through perceptron neural networks and vegetation indicesAntonio da Silva Junior Carlos, Marcos Rafael Nanni, Eduardo Teodoro Paulo, Fernando Capristo Silva Guilherme, Guerreiro de Lima Mendelson, Eri Marta · 2016 · African Journal of Agricultural Research
- Artificial neural network potential in yield prediction of lentil (Lens culinaris L.) influenced by weed interferenceAlireza Bagheri, Zargarian, Negin, Farzad Mondani, Iraj Nosratti · 2023 · Journal of Plant Protection Research
- Deep neural networks autonomously learn and utilize critical environmental conditions to capture the impacts of weather on spring wheat performanceRyan Benke, Linqian Han, Kimberly A. Garland-Campbell, Xianran Li · 2025 · Computers and Electronics in Agriculture
- A Model for the Estimation of Yield and Investigation on Factors Affecting Irrigated Wheat Production in Various Tillage Methods (Using Artificial Neural Networks)Shahrzad Azari Mobarake, Morteza Almassi, Abbas Hemmat, Reza Moghaddasi, Maryam Zekri · 2014
- Suitability of Soil Water Retention Characteristic Models (SWRC) in Regions and Soil DepthVitalis Kibiwott Too, Christian Omuto, Elijah Kipngetich Biamah, John P. O. Obiero · 2019 · Journal of Water Resource and Protection
- A Neural Network Model for Predicting Cotton YieldsJun Zhang, Yiming Wang, Jinping Li, Ping Yang · 2008 · Springer eBooks
- MLP for prediction of area and rice production of upper Brahmaputra Valley zone of AssamRaju Prasad Paswan, Shahin Ara Begum · 2013 · International Conference on Computing, Communication and Networking Technologies (ICCCNT)
- Statistical and Machine Learning Methods for Crop Yield Prediction in the Context of Precision AgricultureHanna Burdett · 2022
- Fındık Üretimi için Öğrenme Tabanlı Verim TahminiDoğan Yıldız, Gülcan Yıldız, Sercan Demіrcі · 2023 · Black Sea Journal of Engineering and Science
- Contextualized LSTM-DNN Model for County-Level Corn Yield Prediction from Weather and Soil DataMd. Samiul Basir, Yue Shirley Li, Ningning Nikole Kong, Fabio A. Castiblanco, James V. Krogmeier, Dennis R. Buckmaster · 2025 · IEEE Latin Conference on IoT (LCIoT)
- Forecasting agriculture yield in Nepal using machine learning techniquesSandeep Dhakal, Ajaya Dhungana · 2025 · NRB Economic Review
- Rice Yield Prediction Based on the Soil Chemical Properties Using Neural Network ModelJae Hoon Sung, D. H. Lee · 2005 · Journal of Biosystems Engineering
- Estimation of Nitrogen Content by Spectral Responses of Cabbage Seedlings Using Artificial Neural Network ApproachC. T. Chen, K. W. Hsieh, Hao Yang, Sheng‐Huei Hsiao, I‐Chang Yang · 2004 · 2004, Ottawa, Canada August 1 - 4, 2004
- Proactive Crop Supervision with Machine Learning Algorithms for Yield ImprovementKusum Lata, Sajidullah S Khan · 2020 · International Journal of Computer Trends and Technology
- Comparative Soil Parameters Anatomization Using ML to Estimate Fertility in Kitchen GardenKushagra Kaushik, Pooja Gupta, Jitendra Singh Jadon · 2023 · Lecture notes in electrical engineering
- Maize Hybrids Performance Evaluation with Data Fusion by Matrix Factorization AlgorithmMilica Brkić, Stefan Hačko, Miloš Radovanović, Vladimir S. Crnojevic, Sanja Brdar · 2024 · Applied Artificial Intelligence
- Rider Water Cycle Optimization-Based Hierarchical Attention Network and Spark Architecture-Aware IoT System for Crop Yield PredictionAnitha Rajathi Surendran, Arun Sahayadhas · 2025 · Journal of Circuits Systems and Computers
- A Novel Approach for Rice Yield Prediction in Andhra PradeshNagesh Vadaparthi, G. Surya Tejaswini, N. B. S. Pallavi · 2019 · Learning and analytics in intelligent systems
- Improving crop productivity through data-driven optimization and hybrid deep learning-based approachesZahra Khalilzadeh · 2024
- Effect of soil chemical properties on bio-saline production of blue panic grass (Panicum antidotale Retz.) under water-deficit and salinity stress conditionsHamid Reza Eshghizadeh, Mohammad Kafi, Ahmad Nezami · 2012 · Research on Crops
- Nuevos modelos de redes neuronales evolutivas y regresión logística generalizada utilizando funciones de base. AplicacionesPedro Antonio Gutiérrez · 2011 · Institutional Repository of the University of Granada (University of Granada)
- Quantitative retrieval of sparse vegetation coverage by BP neural network based on hyperspectral dataXiaosong Li, Zhihai Gao · 2010 · International Congress on Image and Signal Processing (CISP)
- Structure vs. Property: Algorithms and Models Thesis of HabilitationLorentz Jäntschi · 2012
- DYNAMIC OPTIMIZATION OF WATERING FOR QUALITATIVE IMPROVEMENT OF SATSUMA MANDARIN USING INTELLIGENT CONTROL TECHNIQUEST. Morimoto, Mohammad Safdar Baloch, Kenji HATOU, Yasushi Hashimoto, Yoshinori OUCHI · 2005 · IFAC Proceedings Volumes
- Aprendizado de Máquina aplicado à predição da produtividade da cultura da soja utilizando dados de clima e soloEdson da Silva Guimarães · 2020
- DESIGN AND ANALYSIS OF A PREDICTION MODEL FOR CROP YIELD PRODUCTION IN AGRICULTUREYojna Arora, Ms. Ashima Gambhir · 2020 · International Journal of Innovative Research in Computer Science & Technology
- Prediction of Soil Penetration Resistance with Three Different Artificial Neural Networking Methodsİ̇lker Ünal, Önder Kabaş, Salih Sözer, Süleyman Çetin · 2022 · Romanian Agricultural Research
- Intelligent Computational Techniques for Crop Yield Based On BP Neural NetworkWenwu Xie, Aguwa Dominic Ugochukwu, Jianhui Wu, Zhihe Yang · 2022 · International Journal of Science and Research (IJSR)
- Sunflower Crop Yield Prediction Using Machine Learning MethodsSeda Hatice Gökler · 2024 · Selcuk Journal of Agricultural and Food Sciences
- Predicting fodder crop yield in semi-arid Mongolia using Landsat data: a multivariate analysis approachByambasuren Damdin, Uranbileg Lantuu, Buyanbaatar Avirmed, Batbileg Bayaraa, Enkhjargal Natsagdorj · 2025 · Canadian Journal of Remote Sensing
- Integration of precision farming data and spatial statistical modelling to interpret field-scale maize grain yield variability in New ZealandGuopeng Jiang, Miles C. E. Grafton, Diane M. Pearson, Mike R. Bretherton, Allister W. Holmes · 2019 · Figshare
- Statistical Learning Methodology to Leverage the Diversity of Environmental Scenarios in Crop Data : Application to the prediction of crop production at large-scaleXiangtuo Chen · 2019 · theses.fr (ABES)
- Monitoreo del desarrollo de cultivos de maíz mediante imágenes aéreas multiespectrales procesadas con inteligencia artificialCarlos Martínez Martínez · 2026 · Revista Multidisciplinar Epistemología de las Ciencias