Effective prediction of bitcoin price using wolf search algorithm and bidirectional LSTM on internet of things data. (8th March 2022)

• Record Type: Journal Article
• Authors: Niveditha, V.R.; Sekaran, Karthik; Singh, K. Amandeep; Panda, Sandeep Kumar
• Is Part Of: International journal of system of systems engineering. Volume 11:Number 3/4(2021)
• Page Start: 224
• Page End: 236
• Publication Date: 2022-03-08
• Subjects: crypto currency -- wolf search algorithm -- bidirectional LSTM -- optimisation -- internet of things applications; 003.71
• Languages: English
• ISSNs: 1748-0671

Abstract

Internet of things is the concept of establishing relationships and interactions with other connected devices through a network to reach a specific objective. The collected data from devices could be transformed into valuable insights by applying some intelligent learning algorithms. A distributed, permission less ledger called IOTA (MIOTA) manages micro transactions between multiple devices with the help of IoT. It provides the information about the transactions made with the specific type of crypto currency in the market. In this paper, an effective crypto currency price prediction model is proposed to identify the fluctuations in currency value from the past one-year data. Wolf search optimisation algorithm selects the best performing feature subset. Bidirectional long short-term memory (BiLSTM) model is employed to train and validate the data captured from the feature selection process. The proposed model attained 93% accuracy, significantly higher than the existing methods, portraysits significance and efficacy.