On the public citation graph

A Combined Approach of Systematic Error Reduction with Smoothing Series and Optimal Parameter Selection Techniques for Prediction of Annual Rice Imports

0 signed · 42 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/pa.2016openalex-extracted
Climate variability and its impacts on agriculture production and future prediction using autoregressive integrated moving average method (ARIMA)
inferredcites →https://doi.org/10.1016/bs.agron.2018.04.002openalex-extracted
Basmati Rice in the Indian Subcontinent: Strategies to Boost Production and Quality Traits
inferredcites →https://doi.org/10.1016/c2017-0-00901-1openalex-extracted
Integrated Processing Technologies for Food and Agricultural By-Products
inferredcites →https://doi.org/10.1016/j.advwatres.2020.103656openalex-extracted
Combining statistical machine learning models with ARIMA for water level forecasting: The case of the Red river
inferredcites →https://doi.org/10.1016/j.aei.2017.11.002openalex-extracted
Short-term electricity demand forecasting with MARS, SVR and ARIMA models using aggregated demand data in Queensland, Australia
inferredcites →https://doi.org/10.1016/j.ajsl.2021.06.002openalex-extracted
Forecasting oil tanker shipping market in crisis periods: Exponential smoothing model application
inferredcites →https://doi.org/10.1016/j.apcbee.2014.03.015openalex-extracted
Climate Change Impacts on Agricultural Products in Thailand: A Case Study of Thai Rice at the Chao Phraya River Basin
inferredcites →https://doi.org/10.1016/j.asej.2022.101732openalex-extracted
Monthly runoff prediction at Baitarani river basin by support vector machine based on Salp swarm algorithm
inferredcites →https://doi.org/10.1016/j.cmpbup.2021.100029openalex-extracted
Forecasting COVID-19 pandemic in Alberta, Canada using modified ARIMA models
inferredcites →https://doi.org/10.1016/j.compeleceng.2017.07.006openalex-extracted
Smart grid load forecasting using online support vector regression
inferredcites →https://doi.org/10.1016/j.egyr.2019.06.003openalex-extracted
Short-term load forecasting of urban gas using a hybrid model based on improved fruit fly optimization algorithm and support vector machine
inferredcites →https://doi.org/10.1016/j.ejor.2022.04.040openalex-extracted
A new taxonomy for vector exponential smoothing and its application to seasonal time series
inferredcites →https://doi.org/10.1016/j.energy.2020.117159openalex-extracted
Forecasting based on an ensemble Autoregressive Moving Average - Adaptive neuro - Fuzzy inference system – Neural network - Genetic Algorithm Framework
inferredcites →https://doi.org/10.1016/j.energy.2020.117200openalex-extracted
A hybrid approach based on autoregressive integrated moving average and least-square support vector machine for long-term forecasting of net electricity consumption
inferredcites →https://doi.org/10.1016/j.energy.2021.119955openalex-extracted
Mid-term prediction of electrical energy consumption for crude oil pipelines using a hybrid algorithm of support vector machine and genetic algorithm
inferredcites →https://doi.org/10.1016/j.esr.2021.100788openalex-extracted
Energy demand and production forecasting in Pakistan
inferredcites →https://doi.org/10.1016/j.eswa.2019.06.060openalex-extracted
Hierarchical time series forecasting via Support Vector Regression in the European Travel Retail Industry
inferredcites →https://doi.org/10.1016/j.forpol.2021.102564openalex-extracted
Evaluating a seasonal autoregressive moving average model with an exogenous variable for short-term timber price forecasting
inferredcites →https://doi.org/10.1016/j.ijforecast.2006.03.001openalex-extracted
Another look at measures of forecast accuracy
inferredcites →https://doi.org/10.1016/j.ijpe.2016.08.004openalex-extracted
Demand forecasting with four-parameter exponential smoothing
inferredcites →https://doi.org/10.1016/j.inpa.2021.07.003openalex-extracted
A methodology for coffee price forecasting based on extreme learning machines
inferredcites →https://doi.org/10.1016/j.jag.2018.07.022openalex-extracted
Estimating rice production in the Mekong Delta, Vietnam, utilizing time series of Sentinel-1 SAR data
inferredcites →https://doi.org/10.1016/j.jbi.2021.103887openalex-extracted
Implementation of stacking based ARIMA model for prediction of Covid-19 cases in India
inferredcites →https://doi.org/10.1016/j.jclepro.2018.07.164openalex-extracted
Application of support vector machine models for forecasting solar and wind energy resources: A review
inferredcites →https://doi.org/10.1016/j.jclepro.2018.09.143openalex-extracted
Short-term wind power prediction based on data mining technology and improved support vector machine method: A case study in Northwest China
inferredcites →https://doi.org/10.1016/j.jclepro.2020.125324openalex-extracted
Electricity production based forecasting of greenhouse gas emissions in Turkey with deep learning, support vector machine and artificial neural network algorithms
inferredcites →https://doi.org/10.1016/j.jclepro.2022.131224openalex-extracted
Combining autoregressive integrated moving average with Long Short-Term Memory neural network and optimisation algorithms for predicting ground water level
inferredcites →https://doi.org/10.1016/j.jiph.2019.12.008openalex-extracted
Forecast of the trend in incidence of acute hemorrhagic conjunctivitis in China from 2011–2019 using the Seasonal Autoregressive Integrated Moving Average (SARIMA) and Exponential Smoothing (ETS) models
inferredcites →https://doi.org/10.1016/j.jssas.2018.03.001openalex-extracted
Supply response of rice using time series data: Lessons from Khyber Pakhtunkhwa Province, Pakistan
inferredcites →https://doi.org/10.1016/j.jssas.2019.09.001openalex-extracted
Forecasting Saudi Arabia’s production and imports of broiler meat chickens and its effect on expected self-sufficiency ratio
inferredcites →https://doi.org/10.1016/j.knosys.2019.03.011openalex-extracted
An intelligent hybridization of ARIMA with machine learning models for time series forecasting
inferredcites →https://doi.org/10.1016/j.knosys.2022.108687openalex-extracted
An oil imports dependence forecasting system based on fuzzy time series and multi-objective optimization algorithm: Case for China
inferredcites →https://doi.org/10.1016/j.neuri.2022.100052openalex-extracted
An overview: Modeling and forecasting of time series data using different techniques in reference to human stress
inferredcites →https://doi.org/10.1016/j.procs.2021.05.057openalex-extracted
A Study on the Prediction of Book Borrowing Based on ARIMA-SVR Model
inferredcites →https://doi.org/10.1016/j.scitotenv.2017.11.291openalex-extracted
PM10 concentration forecasting in the metropolitan area of Oviedo (Northern Spain) using models based on SVM, MLP, VARMA and ARIMA: A case study
inferredcites →https://doi.org/10.1016/j.scs.2022.103886openalex-extracted
A Hybrid Model with Applying Machine Learning Algorithms and Optimization Model to Forecast Greenhouse Gas Emissions with Energy Market Data
inferredcites →https://doi.org/10.1038/s41598-022-04923-7openalex-extracted
Proposing a hybrid metaheuristic optimization algorithm and machine learning model for energy use forecast in non-residential buildings
inferredcites →https://doi.org/10.1080/08839514.2021.1981659openalex-extracted
Time Series Forecasting of Price of Agricultural Products Using Hybrid Methods
inferredcites →https://doi.org/10.1109/access.2021.3091162openalex-extracted
Forecast Methods for Time Series Data: A Survey
inferredcites →https://doi.org/10.1155/2021/9939906openalex-extracted
Short-Term Forecasting of Agriculture Commodities in Context of Indian Market for Sustainable Agriculture by Using the Artificial Neural Network
inferredcites →https://doi.org/10.18637/jss.v027.i03openalex-extracted
Automatic Time Series Forecasting: The forecast Package for R
inferredcites →https://doi.org/10.32614/rj-2013-002openalex-extracted
Generalized Simulated Annealing for Global Optimization: The GenSA Package
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.