Evaluating Forecasting Methods by Considering Different Accuracy Measures

Mehdiyev, Nijat; Enke, David; Fettke, Peter; Loos, Peter

doi:10.1016/j.procs.2016.09.332

Cited by 54 publications

(34 citation statements)

References 23 publications

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“…In addition, a number of evaluation criteria including MAE, MSE, RMSE and MAPE [37][38][39] are proposed to evaluate the forecasting performances. To begin with, we define x as the forecasting values of a model, ref as the observed true values and t = 48 which means 48 points are required to predict within a day.…”

Section: Resultsmentioning

confidence: 99%

A hybrid model for short term real-time electricity price forecasting in smart grid

2018

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Background: With the prominent growth of power market, real-time electricity price has become a trend in smart grid as it enables moderation of power consumption of customers. Accurate forecast of real-time price (RTP) has much influence on customers' behaviors, such as better scheduling operating time of domestic appliances in order to maximize benefit. In this paper, an innovative hybrid RTP forecasting model considering linear and non-linear behaviors within input data, is proposed to forecast the short-term electricity prices in smart grid. Results: The effectiveness of the proposed hybrid forecasting model is verified by numerical results in terms of forecasting performance evaluations. The results clearly demonstrate that our approach is effective in RTP forecasting with a high accuracy. The mean absolute percentage error (MAPE) is approximate to 3.5% and it also significantly outperforms the existing models. Conclusion: Based on the achieved results, we can conclude that the proposed hybrid model is an accurate and efficient tool in short-term RTP forecasting and it is potentially effective to a variety of forecasting tasks.

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Section: Resultsmentioning

confidence: 99%

A hybrid model for short term real-time electricity price forecasting in smart grid

2018

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“…Shock score is a scoring that tells if there is an abnormality in blood circulation which result in hypertension and tachycardia. Research conducted by [5,12] also conclude that Rockall scores shows medical shock to be one of the risk factor of mortality.…”

Section: Discussionmentioning

confidence: 96%

“…Similarly, [18] also point out that rebleeding is an important factor of mortality and occurs in 10-30% of successfully treated patients. Research conducted by [5] and [12] also concluded that rebleeding is an influential factor of mortality. Even though there are advance treatments available in treating patients with UGIB, rebleed remains the life-threatening factor of UGIB patients [9].…”

Section: Discussionmentioning

confidence: 98%

Model-Building of Multiple Binary Logit using Model Averaging

Padzil¹,

Pillay²,

Salleh³

2018

IJET

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Many researchers had been carried out on the study of statistical modelling, making it easier for new researchers in many sectors (social sciences, economics, medical, and etc.) to obtain knowledge in order to ease their research study. Nevertheless, there is still no agreed guidelines in obtaining the best model for multiple binary logit (MBL) using model averaging (MA). This research will demonstrate the proper guidelines to obtain best MBL model by using MA. Upper Gastrointestinal Bleed (UGIB) data were studied to illustrate the process of model-building using the proposed guidelines. This study will pinpoint the factors with high possibility leading to mortality of UGIB patients using obtained best model. Corrected Akaike Information Criteria (AICc) and Bayesian Information Criteria (BIC) were used to compute the weights in model averaging method. The performance of the models was computed by using Root mean square error (RMSE) and mean absolute error (MAE). Model obtained by using BIC weights showed a better performance since the RMSE and MAE values are lower compared to model obtained using AICc weights. The factors that affects the survivability of UGIB patients are shock score, comorbidity and rebleed. In conclusion, model-building of multiple binary logit using model averaging showed a better performance when using BIC.

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“…Clearly, there is a need for an algorithm of decision making for selecting the best prediction models by consid-ering several accuracy measures simultaneously. Mehdiyev et al (2016) proposed a multi-criteria decision analysis approach for solving this problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Problems in evaluating accuracy and consistency of macroeconomic forecasts

Jarkinbayev

Kosherbayeva

2018

Problems and Perspectives in Management

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The paper focuses on the analysis of the quality of macroeconomic forecasts, as well as on general issues of the functioning of the system of macroeconomic forecasting in the Republic of Kazakhstan. It provides a comparative analysis of errors of initial and revised macroeconomic forecasts of the real sector of economy indicators. To assess forecast accuracy, the authors use the world’s most widespread measures, such as the mean error and the mean absolute percentage error, as well as official statistical data and records. The overall forecast consistency and congruence of assumptions on the dynamics of indicators of the real sector and fiscal policy are estimated using the basic identities of the System of National Accounts. The paper also considers institutional aspects of the system of macroeconomic forecasting in the Republic of Kazakhstan. The authors conclude that revised forecasts, with the exception of monetary policy indicators, exhibit a smaller error, which can indicate a need for greater coordination of public authorities in the process of preparing forecasts, developing the system of independent assessment of their quality and improving their transparency.

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Evaluating Forecasting Methods by Considering Different Accuracy Measures

Cited by 54 publications

References 23 publications

A hybrid model for short term real-time electricity price forecasting in smart grid

A hybrid model for short term real-time electricity price forecasting in smart grid

Model-Building of Multiple Binary Logit using Model Averaging

Problems in evaluating accuracy and consistency of macroeconomic forecasts

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