A FUZZY NEURAL NETWORK MODEL FOR ANALYZING BALTIC DRY INDEX IN THE BULK MARITIME INDUSTRY

2021 ◽  
Vol 159 (A2) ◽  
Author(s):  
C C Chou ◽  
K S Lin
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Fuzzy Neural Network ◽  
Operation Management ◽  
Maritime Industry ◽  
Bulk Carrier ◽  
Bulk Shipping ◽  
Fuzzy Neural ◽  
Baltic Dry Index

Baltic Dry Index (BDI) is one of the important indexes in the dry bulk shipping market. BDI analysis and forecasting is one of important activities of shipowners, charterers, shipping carriers, importers and exporters, and banks in the dry bulk shipping market. Based on the accurate BDI analysis and forecasting , the shipowners, charterers, shipping carriers, importers and exporters, and banks in the bulk shipping market could make many important decisions of shipping operation, management and financial invest such as building a new bulk carrier, chartering-in or chartering-out a second-hand bulk carrier, demolishing an old bulk carrier, and providing funding for shipowners. Thus, this paper adopts a fuzzy neural network model to analyze the relationship between the BDI in the international bulk shipping market and the major economic indexes in the global financial market. Finally, the proposed fuzzy neural network model is tested by empirical data during the period of 2000-2015. The results show that the fuzzy neural network model has high accuracy of forecasting. The fuzzy neural network model in this study seems to be promising and the model could help the shipowners, charterers, shipping carriers, importers and exporters, and banks forecast future BDI points in the bulk shipping market, and then make important decisions and operation strategies of shipping operation, management and financial invest.

A Fuzzy Neural Network Model for Analysing Baltic Dry Index in the Bulk Maritime Industry

2017 ◽  
Vol Vol 159 (A2) ◽  
Author(s):  
C C Chou ◽  
K S Lin
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Fuzzy Neural Network ◽  
Maritime Industry ◽  
Bulk Carrier ◽  
Bulk Shipping ◽  
Fuzzy Neural ◽  
Economic Indexes ◽  
Baltic Dry Index

Baltic Dry Index (BDI) is one of the important indexes in the dry bulk shipping market. BDI analysis and forecasting is one of important activities of shipowners, charterers, shipping carriers , importers and exporters, and banks in the dry bulk shipping market. Based on the accurate BDI analysis and forecasting , the shipowners, charterers, shipping carriers, importers and exporters, and banks in the bulk shipping market could make many important decision s of shipping operation, management and financial invest such as building a new bulk carrier , chartering in or chartering out a second hand bulk carrier demoli shing an old bulk carrier , and providing funding for shipowners Thus, t his paper adopts a fuzzy neural network model to analyze the relationship between the BDI in the international bulk shipping market and the major economic indexes in the global financial market . Finally, the proposed fuzzy neural network model is tested by empirical data during the period of 2000 2015. The results show that the fuzzy neural network model has high accuracy of forecast ing . The fuzzy neural network model in this study seems to be pro mising and the model could help the shipowners, charterers, shipping carriers , importers and exporters, and banks forecast future BDI points in the bulk shipping market, and then make important decisions and operation strategies of shipping operation, mana gement and financial invest.

Application of T-S Fuzzy Neural Network in the Assessment of River Ecosystem Health

2013 ◽  
Vol 726-731 ◽  
pp. 958-962 ◽  
Author(s):  
Zhen Chun Hao ◽  
Xiao Li Liu ◽  
Qin Ju
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Fuzzy System ◽  
Ecosystem Health ◽  
Fuzzy Neural Network ◽  
Evaluation Model ◽  
Fuzzy Model ◽  
River Ecosystem ◽  
Fuzzy Neural

Healthy river ecosystem has been acknowledged as the object of river management, which is crucial for the sustainable development of cities. Simple and practical evaluation methods with great precision are necessary for the evaluation of river ecosystem health. Fuzzy system has been widely used in evaluation and decision making for its simple reasoning and the adoption of experts knowledge. However, much artificial intervention decreases the precision. Neural network has a strong ability of self-leaning while it is not good at expressing rule-based knowledge. The T-S fuzzy neural network model combines the advantages of fuzzy system and neural network. In this paper, the T-S fuzzy neural network model was used to establish a river ecosystem health evaluation model. Results show that the combination of T-S fuzzy model and neural network eliminates the influences of subjective factors and improve the final precisions efficiently.

scholarly journals Modelling of the Slope Solute Loss Based on Fuzzy Neural Network Model

2022 ◽  
Vol 42 (2) ◽  
pp. 677-688
Author(s):  
Xiaona Zhang ◽  
Jie Feng ◽  
Zhen Hong ◽  
Xiaona Rui
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Fuzzy Neural Network ◽  
Fuzzy Neural
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