Forecasting Chemical Tanker Freight Rate with ANN (인공신경망을 이용한 케미컬 탱커 운임예측)

Sangseop Lim (임상섭); Seok-Hun Kim (김석훈)

doi:10.9708/jksci.2021.26.04.113

Forecasting Chemical Tanker Freight Rate with ANN

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2021, 26(4), pp.113-118
DOI : 10.9708/jksci.2021.26.04.113
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science
Received : April 6, 2021
Accepted : April 27, 2021
Published : April 30, 2021

Sangseop Lim ¹, Seok-Hun Kim ²

¹한국해양대학교
²배재대학교

Accredited

ABSTRACT

In this paper, we propose an efficient dynamic workload balancing strategy which improves the performance of high-performance computing system. The key idea of this dynamic workload balancing strategy is to minimize execution time of each job and to maximize the system throughput by effectively using system resource such as CPU, memory. Also, this strategy dynamically allocates job by considering demanded memory size of executing job and workload status of each node. If an overload node occurs due to allocated job, the proposed scheme migrates job, executing in overload nodes, to another free nodes and reduces the waiting time and execution time of job by balancing workload of each node. Through simulation, we show that the proposed dynamic workload balancing strategy based on CPU, memory improves the performance of high-performance computing system compared to previous strategies.

KEYWORDS

Chemical Tanker, Shipping Freight rate, Artificial Neural Network, ARIMA, Forecasting

Citation status

* References for papers published after 2023 are currently being built.

[journal] 임상섭 / 2018 / Forecasting Tanker Indices with ARIMA-SVM Hybrid Models / 金融工學硏究 / 한국금융공학회 17(4) : 79~98

[journal] 임상섭 / 2018 / An Analysis on Determinants of the Capesize Freight Rate and Forecasting Models / 한국항해항만학회지 / 한국항해항만학회 42(6) : 539~545

[confproc] Vijh, M. / 2020 / Stock Closing Price Prediction using Machine Learning Techniques / Proceeding of International Conference on Computational Intelligence and Data Science 167 : 599~606

[journal] 임정수 / 2020 / A Study on Stock Trend Determination in Stock Trend Prediction / 한국컴퓨터정보학회논문지 / 한국컴퓨터정보학회 25(12) : 35~44

[confproc] Gupta N. / 2020 / Crude Oil Price Prediction using Artificial Neural Network / Proceeding of International Conference on Emerging Data and Industry 4. 0 170 : 642~647

[journal] Marta Matyjaszek / 2019 / Forecasting coking coal prices by means of ARIMA models and neural networks, considering the transgenic time series theory / Resources Policy / Elsevier BV 61 : 283~292

[journal] Jun Li / 1997 / Forecasting tanker freight rate using neural networks / Maritime Policy & Management / Informa UK Limited 24(1) : 9~30

[journal] D V Lyridis / 2004 / Forecasting Tanker Market Using Artificial Neural Networks / Maritime Economics & Logistics / Springer Science and Business Media LLC 6(2) : 93~108

[confproc] Spreckelsen, C. / 2012 / Short-Term Trading Performance of Spot Freight Rates and Derivatives in the Tanker Shipping Market: Do Neural Networks Provide Suitable Results? / Engineering Applications of Neural Networks(EANN 2012) Communications in Computer and Information Science 311 : 443~452

[journal] Shuangrui Fan / 2013 / Forecasting Baltic Dirty Tanker Index by Applying Wavelet Neural Networks / Journal of Transportation Technologies / Scientific Research Publishing, Inc. 03(01) : 68~87

[journal] André A P Santos / 2014 / Forecasting period charter rates of VLCC tankers through neural networks: A comparison of alternative approaches / Maritime Economics & Logistics / Springer Science and Business Media LLC 16(1) : 72~91

[journal] Payman Eslami / 2017 / Predicting tanker freight rates using parsimonious variables and a hybrid artificial neural network with an adaptive genetic algorithm / Maritime Economics & Logistics / Springer Science and Business Media LLC 19(3) : 538~550

[journal] Guoqiang Zhang / 1998 / Forecasting with artificial neural networks: / International Journal of Forecasting / Elsevier BV 14(1) : 35~62

[book] Box, G. E. P. / 2015 / Time Series Analysis: Forecasting and Control 5th ED / Jhon Wiley & Sons

[journal] Mukta Paliwal / 2009 / Neural networks and statistical techniques: A review of applications / Expert Systems with Applications / Elsevier BV 36(1) : 2~17

[journal] Ahmed Tealab / 2018 / Time series forecasting using artificial neural networks methodologies: A systematic review / Future Computing and Informatics Journal / Future University in Egypt 3(2) : 334~340

This paper was written with support from the National Research Foundation of Korea.

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Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Forecasting Chemical Tanker Freight Rate with ANN

ABSTRACT

KEYWORDS

Citation status

* References for papers published after 2023 are currently being built.

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Forecasting Chemical Tanker Freight Rate with ANN

ABSTRACT

KEYWORDS

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REFERENCES (16) * References for papers published after 2023 are currently being built.

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* References for papers published after 2023 are currently being built.