SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Predicting Prices of Staple Crops Using Machine Learning: A Systematic Review of Studies on Wheat, Corn, and Rice
16 references·0 citing·54 second hopsampled
Predicting Prices of Staple Crops Using Machine Learning: A Systematic Review of Studies on Wheat, Corn, and Rice (2025)Predicting Prices of Staple Crops Using M…Yellow corn wholesale price forecasts via the neural network (2023)Yellow corn wholesale price f…PRISMA2020 : An R package and Shiny app for producing PRISMA 2020‐compliant flow diagrams, with interactivity for optimised digital transparency and Open Synthesis (2022)PRISMA2020 : An R package and…Optimal forecast combination based on PSO-CS approach for daily agricultural future prices forecasting (2022)Optimal forecast combination …Commodity price forecasting via neural networks for coffee, corn, cotton, oats, soybeans, soybean oil, sugar, and wheat (2022)Commodity price forecasting v…Agricultural Price Prediction Based on Combined Forecasting Model under Spatial-Temporal Influencing Factors (2022)Agricultural Price Prediction…Deep long short-term memory based model for agricultural price forecasting (2021)Deep long short-term memory b…Corn cash price forecasting with neural networks (2021)Corn cash price forecasting w…An ensemble machine learning approach for forecasting credit risk of agricultural SMEs’ investments in agriculture 4.0 through supply chain finance (2021)An ensemble machine learning …Artificial bee colony-based combination approach to forecasting agricultural commodity prices (2019)Artificial bee colony-based c…A combined neural network model for commodity price forecasting with SSA (2018)A combined neural network mod…Performance Analysis of Four Decomposition-Ensemble Models for One-Day-Ahead Agricultural Commodity Futures Price Forecasting (2017)Performance Analysis of Four …Speculation and volatility spillover in the crude oil and agricultural commodity markets: A Bayesian analysis (2011)Speculation and volatility sp…Assessing the effect of oil price on world food prices: Application of principal component analysis (2010)Assessing the effect of oil p…Forecasting market prices in a supply chain game (2008)Forecasting market prices in …An investigation and comparison of artificial neural network and time series models for Chinese food grain price forecasting (2007)An investigation and comparis…A comparison of artificial neural network and time series models for forecasting commodity prices (1996)A comparison of artificial ne…Time Series Analysis: Forecasting and Control (1977)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)Seasonal forecasting of agricultural commodity price using a hybrid STL and ELM method: Evidence from the vegetable market in China (2017)Forecasting gold price fluctuations using improved multilayer perceptron neural network and whale optimization algorithm (2019)Predictions of steel price indices through machine learning for the regional northeast Chinese market (2024)The Application of Electronic Computers to Factor Analysis (1960)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)Testing for Common Trends (1988)How is Volatility in Commodity Markets Linked to Oil Price Shocks? (2015)Exploring the time-frequency connectedness and network among crude oil and agriculture commodities V1 (2019)Time-frequency causality and connectedness between international prices of energy, food, industry, agriculture and metals (2019)Chaos and Nonlinear Dynamics: Application to Financial Markets (1991)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Time series forecasting for nonlinear and non-stationary processes: a review and comparative study (2015)Forecasting wholesale prices of yellow corn through the Gaussian process regression (2024)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks (1993)Volatility spillover between oil and agricultural commodity markets (2012)Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold (2013)On the links between stock and commodity markets' volatility (2013)The Combination of Forecasts (1969)Comparing Predictive Accuracy (1994)Comparing Predictive Accuracy (2002)Optimal selection of heterogeneous ensemble strategies of time series forecasting with multi-objective programming (2020)Optimized neural network combined model based on the induced ordered weighted averaging operator for vegetable price forecasting (2020)Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)Testing for a Unit Root in Time Series Regression (1988)Testing the null hypothesis of stationarity against the alternative of a unit root (1992)Individual time series and composite forecasting of the Chinese stock index (2021)Wholesale price forecasts of green grams using the neural network (2024)Credit Rationing in Markets with Imperfect Information (1981)Testing the pecking order theory of capital structure (2002)Credit rating analysis with support vector machines and neural networks: a market comparative study (2003)A federated machine learning approach for order-level risk prediction in Supply Chain Financing (2023)Constraints to agricultural finance in underdeveloped and developing countries: a systematic literature review (2024)Prediction of bank credit worthiness through credit risk analysis: an explainable machine learning study (2024)Time Series Analysis Forecasting and Control. (1971)Time Series Analysis: Forecasting and Control. (1978)Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)Predicting open interest in thermal coal futures using machine learning (2024)Forecasts of wholesale food price indices through Gaussian process regressions (2025)Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement (2009)Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement (2009)The PRISMA 2020 statement: an updated guideline for reporting systematic reviews (2021)Artificial intelligence in systematic reviews: promising when appropriately used (2023)Sensitivity analysis in multi-criteria decision making: A state-of-the-art research perspective using bibliometric analysis (2023)Generative AI and Academic Integrity in Higher Education: A Systematic Review and Research Agenda (2025)A test for independence based on the correlation dimension (1996)Testing the equality of prediction mean squared errors (1997)On the use of cross-validation for time series predictor evaluation (2012)Contemporaneous causality among price indices of ten major steel products (2024)Pre-owned housing price index forecasts using Gaussian process regressions (2024)Predictions of residential property price indices for China via machine learning models (2025)
this work references cited by second hop· second hop is a sample of the most-cited connections

References

  • 2022PRISMA2020 : An R package and Shiny app for producing PRISMA 2020‐compliant flow diagrams, with interactivity for optimised digital transparency and Open Synthesis3,462 cited
  • 2011Speculation and volatility spillover in the crude oil and agricultural commodity markets: A Bayesian analysis550 cited
  • 1996A comparison of artificial neural network and time series models for forecasting commodity prices293 cited
  • 2021Corn cash price forecasting with neural networks291 cited
  • 2007An investigation and comparison of artificial neural network and time series models for Chinese food grain price forecasting198 cited
  • 2010Assessing the effect of oil price on world food prices: Application of principal component analysis188 cited
  • 2022Commodity price forecasting via neural networks for coffee, corn, cotton, oats, soybeans, soybean oil, sugar, and wheat141 cited
  • 2021An ensemble machine learning approach for forecasting credit risk of agricultural SMEs’ investments in agriculture 4.0 through supply chain finance120 cited
  • 2019Artificial bee colony-based combination approach to forecasting agricultural commodity prices94 cited
  • 2021Deep long short-term memory based model for agricultural price forecasting88 cited
  • 2023Yellow corn wholesale price forecasts via the neural network84 cited
  • 2018A combined neural network model for commodity price forecasting with SSA79 cited
  • 2022Agricultural Price Prediction Based on Combined Forecasting Model under Spatial-Temporal Influencing Factors

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

54 cited
  • 2022Optimal forecast combination based on PSO-CS approach for daily agricultural future prices forecasting52 cited
  • 2017Performance Analysis of Four Decomposition-Ensemble Models for One-Day-Ahead Agricultural Commodity Futures Price Forecasting51 cited
  • 2008Forecasting market prices in a supply chain game48 cited
  • Cited by

    No citing works inside the corpus for this window.