Forecasting

This paper explores the applications of Big Data in business network analysis, focusing on how it enhances supply chain visibility, risk management, and demand forecasting. It also addresses challenges like data privacy, security, and managing large datasets.

11p vijiraiya 19-05-2025 1 1   Download

Initial Public Offering (IPO) is considered a strategic decision of utmost importance for every business, especially companies that wish to list on the stock exchange. international. Using the Wilcoxon non-parametric test method, the study shows that IPO activities have a positive impact on the profits of businesses listed on the NASDAQ Global Select Market stock exchange in general and of VinFast in particular.

16p viling 11-10-2024 4 1   Download

Consumer demand is an important factor in any business, especially in the food retail industry whose products are perishable and have a short life cycle. The daily demand for a food product is affected by external factors, such as seasonality, price reduction and holidays.

8p vifilm 11-10-2024 2 1   Download

Accurate daily load forecasting is critical for effective energy management planning. In this study, the article proposes a new method for daily load forecasting that takes advantage of load data and weather data over time in Tien Giang.

10p viengfa 28-10-2024 1 1   Download

Accurate forecasting of the electrical load is a critical element for grid operators to make well-informed decisions concerning electricity generation, transmission, and distribution. In this study, an Extreme Learning Machine (ELM) model was proposed and compared with four other machine learning models including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU).

10p viengfa 28-10-2024 2 1   Download

This article conducts an exhaustive investigation into the utilization of machine learning (ML) methods for forecasting the maximum load capacity (MLC) of circular reinforced concrete columns (CRCC) using Fiber-Reinforced Polymer (FRP). Extreme Gradient Boosting (XGB) algorithm is combined with novel metaheuristic algorithms, namely Sailfish Optimizer and Aquila Optimizer, to fine-tune its hyperparameters.

18p viengfa 28-10-2024 2 2   Download

The results of this study would be useful in quickly and accurately predicting CPI to the management agencies, investors, construction contractors to pre-plan the construction investment costs. This will also help in suitably adjusting changing construction cost with time.

11p viengfa 28-10-2024 2 2   Download

This paper is aimed to apply hybrid machine learning model namely GA-ANFIS, which is a combination of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Genetic Algorithm (GA), for the prediction of total bearing capability of driven piles.

8p viengfa 28-10-2024 3 2   Download

This article uses Random Forest (RF) and k-fold cross-validation to predict the hourly count of rental bikes (cnt/h) in the city of Seoul (Korea) using information related to rental hour, temperature, humidity, wind speed, visibility, dewpoint, solar radiation, snowfall, and rainfall.

9p viengfa 28-10-2024 3 2   Download

In this study, we propose a machine learning technique for estimating the shear strength of CRC beams across a range of service periods. To do this, we gathered 158 CRC beam shear tests and used Artificial Neural Network (ANN) to create a forecast model for the considered output.

12p viengfa 28-10-2024 3 2   Download

This paper develops an Artificial Neural Network (ANN) model based on 96 experimental data to forecast the dynamic modulus of asphalt concrete mixtures. This study applied the repeated KFold cross-validation technique with 10 folds on the training data set to make the simulation results more reliable and find a model with more general predictive power.

9p viengfa 28-10-2024 5 2   Download

This study proposes the application of Ensemble Decision Tree Boosted (EDT Boosted) model for forecasting the surface chloride concentration of marine concrete Cs. A database of 386 experimental results was collected from 17 different sources covering twelve variables was used to build and verify the predictive power of the EDT model.

12p viengfa 28-10-2024 5 2   Download

This article presents the frequency and trends of meteorological drought in Thai Binh province for the period 1991-2021 and forecasts drought trends for the period 2025-2065 based on climate change scenarios. The PED drought index is calculated using the corresponding daily temperature and rainfall data for each of these periods.

11p viaburame 14-03-2025 2 1   Download

The fuzzy time series model has become a research topic attracting attention because of its practical value in the field of time series forecasting, specifically, it is useful for time series with small observations or the one of strong fluctuations. This paper introduces a fuzzy time series model based on hedge algebra with a new formula for calculating forecasting values.

9p viengfa 28-10-2024 2 1   Download

This study aimed to externally validate the population pharmacokinetic (popPK) model of amikacin and assess the applicability of the Bayesian forecasting approach in individualizing amikacin dosing for critically ill patients.

10p vihyuga 04-03-2025 3 1   Download

This research proposes strategic solutions for attracting Foreign Direct Investment (FDI) to develop eco-industrial parks in the Red River Delta region through 2030, with a vision for 2050. The author's proposed solutions are grounded in a comprehensive analysis of the current status and developmental trends of eco-industrial park models, forecasted impacts of international and domestic contexts on FDI flows, and the competitive advantages of the Red River Delta region in attracting FDI specifically for eco-industrial parks.

8p vihyuga 20-02-2025 8 1   Download

This study’s significance lies in its contribution to the academic discourse on the practical applications of blockchain and smart contracts in a specific regional context. It aims to provide actionable insights for businesses and policymakers, facilitating informed decisions to optimize supply chain processes, bolster competitiveness, and navigate the evolving market context efficiently.

8p viyamanaka 06-02-2025 13 2   Download

Severe air pollution in Vietnam's tourism areas has become a significant economic issue in recent years. While many studies have found a link between population exposure to air pollution and poor health outcomes, short-term exposure to air pollutants in high-pollution zones can result in acute health consequences; thus, poor air quality jeopardizes visitors' health and well-being and threatens the tourism industry's sustainability.

14p viyamanaka 06-02-2025 3 2   Download

This research paper focuses on the critical role of demand forecasting in FMCG, emphasizing the need for LSTM-based deep learning models to deal with demand uncertainty and improve predictive outcomes. Through this exploration, we aim to illuminate the link between demand forecasting and advanced deep learning, enabling FMCG companies to thrive in a highly dynamic business landscape.

8p vifilm 11-10-2024 10 1   Download

Time series analysis is an essential field in data analysis, particularly within forecasting and prediction domains. Researching and building time series models play a crucial role in understanding and predicting the temporal dynamics of various phenomena. In mathematics, time series data is defined as data points indexed in chronological order and have a consistent time interval between consecutive observations.

10p vibenya 31-12-2024 5 2   Download