Search Results

Now showing 1 - 3 of 3

Some of the metrics are blocked by your
consent settings
Gold-Price Forecasting Method Using Long Short-Term Memory and the Association Rule
(2023-01-01)
Boongasame, Laor
;
Viriyaphol, Piboonlit
;
Tassanavipas, Kriangkrai
;
Temdee, Punnarumol
Since gold prices influence international economic and monetary systems, numerous studies have been conducted to forecast gold prices. Nonetheless, studies employing the linear relationship method usually fail to explain the change in the pattern of the gold price. This study introduces a new paradigm that incorporates association rules and long short-term memory (LSTM) as a nonlinear-based method. For simulation, the proposed method was analyzed with data from Yahoo Finance from January 2010 to December 2020. The association rule was used to choose features relevant to the gold spot (GS) in the US Dollar Index (DXY). The LSTM forecast the gold price with a range of hyperparameter settings. The simulation results showed that the proposed method—the LSTM with GS and DXY, or LSTM-GS-DXY—resulted in low mean absolute percentage error (MAPE) metrics. In addition, the proposed LSTM-GS-DXY system outperformed the simple moving average (SMA), weight moving average (WMA), exponential moving average (EMA), and auto-regressive integrated moving average (ARIMA).
Some of the metrics are blocked by your
consent settings
Blockchain-based Trusty Buyer Coalition Scheme Using A Group Signature
(2022-01-01)
Boongasame, Laor
;
Chaising, Supansa
;
Temdee, Punnarumol
Without trust, buyers may not join a coalition. Despite the tremendous need for trustworthy relationships in buyer coalitions, no current buyer coalition scheme explicitly tackles confidence issues with blockchain technology. This study proposes an algorithmic design, the blockchain-based trusty buyer coalition scheme, to satisfy the trust requirement among different actors while forming the coalition. All activities forming a coalition through a decentralized public ledger can be explicitly examined. Consequently, the proposed algorithm can ensure anonymity within a community, resulting in trusting relationships. Furthermore, the proposed algorithm can ensure correctness and accountability by recognizing misbehavior and enforcing alternative forms of punishment. Additionally, the discovered algorithm can be applied to mobile commerce applications.
Some of the metrics are blocked by your
consent settings
A Genetic Algorithm Approach for Intermodal Cooperation with High-Speed Rail: The Case of Thai Transportation System
(2020-12-01)
Boongasame, Laor
;
Temdee, Punnarumol
;
Kumnungkit, Kanchana
The Thai government has a plan to start the first operation of the Thai High-Speed Rail (THSR) in 2021. However, ensuring the profit of THSR while limiting the project impacts on existing transport options is challenging. In this study, an approach for identifying the optimal travel frequency for impacted transportation services after the THSR operation is implemented. The genetic algorithm (GA) is introduced with specific value functions of various transport options, including rail, bus, and van, to reschedule each travelling option under the intermodal cooperation model. The constraint of GA is that the profit of the individual transport option in the next generation will have to be higher than the total profit of the previous generation. From the case study between Nakhon Ratchasima and Bangkok, the simulation results show that THSR and other transport options have overall gain higher profits after the start of THSR operation. Regarding social welfare theory, the simulation results show that the profit of each transport option is proven to be stable concerning travel schedule frequency after implementation of the THSR system.

KMITL

Browse

Filters

Settings

Sort By

Results per page

Search Results