IEEE Access, 2019 Intelligent transportation system (ITS) is a cutting-edge traffic solution employing state-of-the-art information and communication technologies. Optimized bus-scheduling, being an integral part of ITS, ensures safety, efficiency, traffic congestion ...
Moubeen Farooq Khan +3 more
doaj +1 more source
A Machine Learning-Based Model for Individualized Prediction of Vancomycin Concentration-Time Curves in ICU Patients. [PDF]
Pharmacol Res PerspectA machine learning–integrated pharmacokinetic model improves individualized prediction of vancomycin concentration–time profiles in ICU patients and outperforms traditional pharmacokinetic models, providing a practical decision‐support tool for precision dosing.
Wang JY +11 more
europepmc +2 more sources
Malaysia tourism demand forecasting using box-jenkins approach [PDF]
, 2018 Tourism industry in Malaysia is crucial and has contributes a huge part in Malaysia’s economic growth. The capability of forecasting field in tourism industry can assist people who work in tourism-related-business to make a correct judgment and plan ...
Abd Latif, Amirah +6 more
core +1 more source
Surveying the best volatility measurements to forecast stock market [PDF]
, 2017 This paper investigates methods to forecast future adjusted price of S&P 500 by using geometric Brownian motion (GBM) and geometric fractional Brownian motion (GFBM) for better investment decision.
Alhagyan, Mohammed +2 more
core +1 more source
Weighted Moving Average of Forecasting Method for Predicting Bitcoin Share Price using High Frequency Data: A Statistical Method in Financial Cryptocurrency Technology [PDF]
, 2018 Bitcoin is a type of cryptocurrency that implemented decentralized digital currency method. The transaction is monitored and validated by peer-to peer system using hash programming.
Bakar, N. A. (Nashirah) +1 more
core +1 more source
Case Studies in Thermal Engineering, 2023 Due to the complexity and changeable of lithium-ion batteries, we propose a multi-variable and multi-step Temporal neural network to cover this task. Specially, a novel multi-step training strategy is applied to deal with long time sequences, and multi ...
Yufeng Huang, Jian Sun, Lei Xu
doaj +1 more source
Electricity Consumption Prediction in Oil and Gas Equipment Service and Maintenance Workshops Using RNN LSTM [PDF]
E3S Web of Conferences, 2023 This research offers a Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) model for forecasting power usage in a facility that provides oil and gas equipment service and maintenance.
Rafael Benedict +2 more
doaj +1 more source
A new hybrid of fuzzy c-means method and fuzzy linear regression model in predicting manufacturing income [PDF]
, 2018 Analysis by human perception could not be solved using traditional method since uncertainty within the data have to be dealt with first. Thus, fuzzy structure system is considered.
Ahmad Basri, Nur Ain Zafirah +6 more
core +1 more source
E3S Web of Conferences, 2017 The paper analyses the use of four data mining methods (Support Vector Machines. Cascade Neural Networks. Random Forests and Boosted Trees) to predict sorption on activated carbons.
Dąbek Lidia +2 more
doaj +1 more source
Comparative study of neural network variants for potato (Solanum tuberosum) price modeling
The Indian Journal of Agricultural SciencesThe intricate nature of agricultural price data possesses a formidable challenge in the modeling process, necessitating the careful selection and fine-tuning of methodologies.
S VISHNU SHANKAR +3 more
doaj +1 more source