2014
DOI: 10.1007/978-3-319-07467-2_15
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BDI Forecasting Based on Fuzzy Set Theory, Grey System and ARIMA

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Cited by 6 publications
(5 citation statements)
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References 29 publications
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“…Han et al [2] presented the improved support vector machine model which is combined model of wavelet transform and support vector machine in order to forecast dry bulk freight index. Wong [4] introduced that Autoregressive integrated moving average fits better than Fuzzy heuristic model for the prediction of BDI in their studies. Ming-Tao Chou [7] applied fuzzy time series model to forecast the BDI.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…Han et al [2] presented the improved support vector machine model which is combined model of wavelet transform and support vector machine in order to forecast dry bulk freight index. Wong [4] introduced that Autoregressive integrated moving average fits better than Fuzzy heuristic model for the prediction of BDI in their studies. Ming-Tao Chou [7] applied fuzzy time series model to forecast the BDI.…”
Section: Related Workmentioning
confidence: 99%
“…BDI, a powerful tool for shipping industry, has been the average of BCI, BPI and BSI since 2006. It reflects bulk shipping market sentiment as a price reference for transaction platform of bulk shipping companies and investors [4].…”
Section: Introductionmentioning
confidence: 99%
“…It can be thought of as a combination of the steepest descent and Gauss-Newton methods [3,4]. In order to acquire the nearest output values to collected data, different numbers of neurons (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15) in the hidden layer are tried. The logsig activation function is employed in the hidden layer and the purelin activation function is utilized in the output layer.…”
Section: Modeling With Artificial Neural Networkmentioning
confidence: 99%
“…In their study, a support vector machine was implemented and trends with the forecast precision were modeled. Another BDI forecasting approach using fuzzy sets, gray theory, and ARIMA was employed by Wong [14]. Forecasting of dry cargo freight rates using bivariate long-term fuzzy time series forecasting was studied by Duru et al [15].…”
Section: Introductionmentioning
confidence: 99%
“…As the basis of economic and social research, population prediction has been widely used in various aspects of national development. Over the past few years, researchers have studied issues such as population aging [2], sex ratios [3], and demographic dividend [4]. Some researchers have focused too much on the effectiveness of policies.…”
Section: Introductionmentioning
confidence: 99%