Rainfall Forecasting Using Fourier Series

Afshar, Nasser Rostam; Fahmi, Hedayat

doi:10.17265/1934-7359/2012.09.019

Cited by 7 publications

(4 citation statements)

References 1 publication

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“…The future electricity consumption curve for the residential and commercial part was modelled by Fourier series and also achieved useful results with RMSE accuracy (0.18-0.53). For another example of modelling and predicting the cyclic behaviour of data from Afshar and Fahmi (2012), the Fourier series method was used again. They used this model to predict monthly rainfall in the country of Iran but the accuracy of their model is not stated.…”

Section: Literature Reviewmentioning

confidence: 99%

Forecast of sales of selected food products in retail using Fourier series analysis and non-linear regression

Kačmáry,

Bindzár,

Kovalčík

et al. 2024

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Purpose The purpose of this paper is to apply and verify Fourier series analysis in combination with non-linear regression as a tool of forecasting and planning of inputs in the logistics process of a retail chain store. Design/methodology/approach For many popular products, a significant effect of seasonality of sales is expected; therefore, the method of Fourier series was chosen as one of the main forecast calculation techniques. However, the use of this method directly for forecasting sales has a limitation in the form of a complete reconstruction of the shape of the curve from of the given monitored time. Thus, the forecast is based only on the significant harmonic components from the Fourier series analysis that will participate in forecast forming. In addition, to respect the trend of series, the results of Fourier series analysis are combined with the non-linear regression. Findings The results showed that the number of significant harmonic components from the Fourier series analysis is suitable to reflect the future behaviour of the sale in standard market conditions. Forecasting of the sale and accurate purchase planning of goods has a positive effect on reducing the waste of unsold products after their shelf and on increasing of a customer satisfaction. Research limitations/implications This study has an application in a certain period of time (relatively calm behaviour of the food market) and only for a certain region. Therefore, it is not possible to generalize these results as the behaviour of consumers, e.g. within the state. It will also be interesting to monitor and forecast sales of other food items. Practical implications This provides a practical and relatively simple tool for implementing or improving the process of forecasting seasonally dependent products in the food industry. Originality/value This study shows the possibility of forecast that is based on adding the significant harmonic components from the Fourier series analysis to form forecast with the non-linear regression.

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Section: Literature Reviewmentioning

confidence: 99%

Forecast of sales of selected food products in retail using Fourier series analysis and non-linear regression

Kačmáry,

Bindzár,

Kovalčík

et al. 2024

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“…Observed and simulation model were compared from the year 2003 to 2011 (Figure 1). The simulation result was evaluated for x 2 and RMS and compared with the observed data as well as simulation result using Fitting N-term Harmonic Series Rostam Afshar and Fahmi [2]. Figure 1 shows that although, the simulation was unable to accurately match the observed data, however, the model had succeeded in simulating the pattern of the observed rainfall where the simulated data was found to be closely scattered near to the mean value.…”

Section: Modellingmentioning

confidence: 99%

“…Further study in rainfall forecasting focusing on the state of Sarawak is crucial to improve the estimation accuracy for long-term rainfall prediction for the purpose of planning and management in various sectors where rain is considered as a major driving factor such as agriculture and water resources. Recent study by Rostam Afshar and Fahmi [2] reveals the ability of Fourier Series to simulate long-term rainfall up to 300 years is viewed as an important finding in the study of rainfall forecast. For this reason, the main goal of the study is to simulate rainfall using Fourier Series for Sarawak River Basin hence verify the simulation result using statistical tests.…”

Section: Introductionmentioning

confidence: 99%

Application of Mathematical Modelling in Rainfall Forcast: A Csae Study in Sgs. Sarawak Basin

.¹

2014

IJRET

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Malaysia receives rainfall from 2000 mm to 4000 mm annually where it is greatly influenced by two monsoon periods in November to March and May to September. The state of Sarawak is well known for its long and wide rivers. Numerous activities such as commercial, industrial and residential can always be found in the vicinity of the rivers. The activities have started since decades ago and still continue to grow and spatially expanding through times providing incomes ranging from small farmers to the largest corporations. Unfortunately, these areas are expected to experience frequent flood events as well as possible receding water level in rivers based on the findings of previous studies. If the projections are accurate, the productivity of these activities will be reduced, hence, in a longer term may affect the economy of the state as whole as well. Therefore, there is an urgent need for existing knowledge on rainfall behavior to be revised as effects of climate change with the intention that the state can fully utilize the favorable conditions and make scientific based decisions in the future.Recent study reveals that the Fourier series (FS), has the ability to simulate long-term rainfall up to 300 years is viewed as an important finding in the study of rainfall forecast. Long-term rainfall forecasting is viewed to be beneficial to the state of Sarawak in its future planning in various sectors such as water supply, flood mitigation, river transportation as well as agriculture. The main goal of the study is to apply a mathematical modeling in rainfall forecasting for the Sungai Sarawak basin. Data from eight rain gauge stations was analyzed and prepared for missing data, consistency check and adequacy of number of stations. Simple statistical analysis was conducted on the data such as maximum, minimum, mean and standard deviation. 27 years of annual rainfall data were simulated with the Fourier Series equation using spreadsheet. Hence, the result was compared with the Fitting N-term Harmonic Series. The model result reveals that the Fourier Series has the ability to simulate the observed data by being able to describe the rainfall pattern and there is a reasonable relationship between the simulation and observed data with p-value of 0.93.

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“…Then, the rainfall is predicted by using multiple linear regression model, the model is able to predict the annual rainfall in Cuttack District, Odisha, India [5]. Furthermore, rainfall is predicted using the Fourier series, with this series high accuracy is obtained [6]. In predicting rainfall, it is done by comparing the Fast Fourier Transformation (FFT), ARIMA and Artificial Neural Network (ANN) methods [7].…”

Section: Introductionmentioning

confidence: 99%

Forecasting rainfall and potential for repeated events to predict flood areas in Banten province, Indonesia

Ruhiat¹

2022

J. meas. eng.

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In a period of ten years, from 2011-2020 rainfall in Indonesia is relatively high, with annual rainfall between 460.5-4,627.4 mm. The high rainfall has implications for flooding in several provinces. During this period, almost every year several areas in Banten Province experienced floods. To predict areas of Banten Province that have the potential for flooding, forecasts of rainfall and the potential for repeated occurrences of high rainfall are carried out. In making the forecast, observations were made at the Serang Meteorological Station, the Budiarto Curug Meteorological Station, the South Tangerang Climatology Station, and the Tangerang Geophysics Station. Rainfall data from the four stations were analyzed by Fourier transform, Gumbel method and Mononobe method. Distribution analysis results obtained rainfall in Banten Province between 0.0-607.9 mm with the length of rainy days per month between 0-26 days. Then, the results of the Fourier transform analysis; Banten Province included a monsoon rain pattern with unimodial rainfall. Furthermore, the results of the analysis of the Gumbel method and the Mononobe method, Banten Province included the category of moderate rain and tended to be heavy, even extreme. Based on the results of the analysis using these two methods, in 2025 in Banten Province, it is predicted that 11 % heavy rain, 3 % very heavy rain and 1 % extreme rain are predicted. In that year, it is predicted that there will be 65 sub-districts in Banten Province that have the potential for flooding. The sub-districts that have the potential for flooding are mostly located in Serang Regency, Serang City, Tangerang City, and South Tangerang City. This potential flood is predicted to occur in: January, February, March, April, May, October and November.

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Rainfall Forecasting Using Fourier Series

Cited by 7 publications

References 1 publication

Forecast of sales of selected food products in retail using Fourier series analysis and non-linear regression

Forecast of sales of selected food products in retail using Fourier series analysis and non-linear regression

Application of Mathematical Modelling in Rainfall Forcast: A Csae Study in Sgs. Sarawak Basin

Forecasting rainfall and potential for repeated events to predict flood areas in Banten province, Indonesia

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