A Hybrid Climate Model for Rainfall Forecasting Based on Combination of Self-Organizing Map and Analog Method

Wangsoh, Natita; Watthayu, Wiboonsak; Sukawat, Dusadee

doi:10.17576/jsm-2017-4612-32

Cited by 7 publications

(4 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Not always the principle "the more, the better" is right, so it is also important to discuss and determine the number of potential models that can be combined for prediction. Similar discussions have been observed in recent years by many authors [7][8][9][10][11][12][13][14][15][16][17][18].…”

Section: Introductionsupporting

confidence: 90%

“…The research directions of ANN for forecasting purposes became very popular in recent years. Many authors [15,18,20,21] in their work have proposed a combination of ARIMA and ANN to increase the forecast performance of a time series. Other authors [10,22,23] have proposed combinations of ARIMA models and optimization techniques, such as PSO (Particle Swarm Optimization), to increase the forecasting accuracy of the time series.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Study on the Efficiency of Hybrid Models in Forecasting Precipitations and Water Inflow Albania Case Study

Gjika¹,

Ferrja²,

Kamberi³

2019

Adv. sci. technol. eng. syst. j.

View full text Add to dashboard Cite

Climatic changes have a significant impact on many real life processes. Climacteric position of Albania makes precipitations and water inflows in HPP the main variables influencing the amount of electric energy produced in the country. Taking into account their volatility it has considerably increased the need of using hybrid models to improve the quality of predictions. After a detailed analysis of the time series components, we develop a group of hybrid models and propose modifications to increase the accuracy in prediction. Among the contributions of this work is the challenge to choose between hybrid models presented earlier in literature and the modified version according to the nature of data. The final decision on the most accurate model is made based on many goodness of fit test. This study suggest that an accurate selection of the forecasting techniques increases significantly the quality of forecast on precipitations and water inflow data.

show abstract

Section: Introductionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

A Study on the Efficiency of Hybrid Models in Forecasting Precipitations and Water Inflow Albania Case Study

Gjika¹,

Ferrja²,

Kamberi³

2019

Adv. sci. technol. eng. syst. j.

View full text Add to dashboard Cite

show abstract

“…Although the statistical downscaling has several limitations (Wangsoh et al., 2017), however the SDSM model does not require high computational demand to view the simulation results but has ability to produce high quality of projection results. These advantages, as a whole, had made SDSM a reliable tool for climate downscaling (Samadi et al., 2013, Tukimat and Harun, 2015) and was selected as a downscaling tool to generate the future climate trend at the study site.…”

Section: Methodsmentioning

confidence: 99%

Projection the long-term ungauged rainfall using integrated Statistical Downscaling Model and Geographic Information System (SDSM-GIS) model

Tukimat

Syukri

Malek

2019

Heliyon

View full text Add to dashboard Cite

An accuracy in the hydrological modelling will be affected when having limited data sources especially at ungauged areas. Due to this matter, it will not receiving any significant attention especially on the potential hydrologic extremes. Thus, the objective was to analyse the accuracy of the long-term projected rainfall at ungauged rainfall station using integrated Statistical Downscaling Model and Geographic Information System (SDSM-GIS) model. The SDSM was used as a climate agent to predict the changes of the climate trend in Δ2030s by gauged and ungauged stations. There were five predictors set have been selected to form the local climate at the region which provided by NCEP (validated) and CanESM2-RCP4.5 (projected). According to the statistical analyses, the SDSM was controlled to produce reliable validated results with lesser %MAE (<23%) and higher R. The projected rainfall was suspected to decrease 14% in Δ2030s. All the RCPs agreed the long term rainfall pattern was consistent to the historical with lower annual rainfall intensity. The RCP8.5 shows the least rainfall changes. These findings then used to compare the accuracy of monthly rainfall at control station (Stn 2). The GIS-Kriging method being as an interpolation agent was successfully to produce similar rainfall trend with the control station. The accuracy was estimated to reach 84%. Comparing between ungauged and gauged stations, the small %MAE in the projected monthly results between gauged and ungauged stations as a proved the integrated SDSM-GIS model can producing a reliable long-term rainfall generation at ungauged station.

show abstract

“…Thus, it requires low cost but still capable to provide reliable simulated results likes dynamical downscaling. Large number of researches had been done to compare the performance between SDSM model with others model (Khazaei et al, 2020;Wangsoh, et al, 2017;Othman and Tukimat, 2023). Meanwhile Dong et al, (2020) combined the SDSM with Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) to generate the long-term climate at Xiangjiang River Basin with considered the soil and land cover at the region.…”

Section: Introductionmentioning

confidence: 99%

Investigation on the Impact of Representative Concentration Pathways (RCPs) on Climate Research: Case Study in Malaysia

TUKIMAT,

Azman,

Othman

et al. 2023

Preprint

View full text Add to dashboard Cite

This study evaluated the role of RCPs as a significant development in the climate research. RCP presents different scenarios based on specific radiation forcing that would lead to the climate formulations known as RCP2.6 (2.6W/m2), RCP4.5 (4.5W/m2) and RCP8.5 (8.5W/m2). In recent years, Malaysia has conducted climate research using Fourth Assessment Report (AR4) under the A1B scenario. To address the AR4's flaws, these situations had been updated, and the Fifth Assessment Report (AR5) had been launched since 2014. Therefore, the main objective of this study was to investigate the impact of RCPs on the climate generation and to identify the suitable radiation level for Malaysia. The study used statistical climate model (SDSM) as a climate driver to downscale the long-term local climates with regard to the possible emission changes in the local weather. According to the findings, 4 out of 10 states agreed that the RCP2.6 had a good association to the regional climate with higher R (> 0.8) and lower %MAE (< 23%). This result demonstrated that the RCPs plays a main role in the long-term climate assessment.

show abstract

A Hybrid Climate Model for Rainfall Forecasting Based on Combination of Self-Organizing Map and Analog Method

Cited by 7 publications

References 2 publications

A Study on the Efficiency of Hybrid Models in Forecasting Precipitations and Water Inflow Albania Case Study

A Study on the Efficiency of Hybrid Models in Forecasting Precipitations and Water Inflow Albania Case Study

Projection the long-term ungauged rainfall using integrated Statistical Downscaling Model and Geographic Information System (SDSM-GIS) model

Investigation on the Impact of Representative Concentration Pathways (RCPs) on Climate Research: Case Study in Malaysia

Contact Info

Product

Resources

About