Forecasting model

Traffic demand forecasting is a crucial step in the process of urban transportation planning, management, and operation. In developed countries around the world, the application of forecasting models is almost mandatory and brings significant benefits. However, in Vietnam, there have been relatively few studies on the application of traffic demand forecasting models.

5p viwalton 02-07-2024 0 0   Download

Part 2 of ebook "CONCREEP 10: Mechanics and physics of creep, shrinkage, and durability of concrete and concrete structures" provides readers with contents including: steel corrosion in reinforced concrete mechanisms, assessment, measures, and forecast models; cracking behaviors caused by the corrosion of reinforcing bars in rc columns; evaluating the performance of recycled aggregate concrete; nanotechnology applied to concrete; towards the next generation of standards for the service life of cement-based materials and structures mini-symposium of COST action TU1404; microstructure and mic...

831p mothoiphong 28-06-2024 1 1   Download

There are generally four factors that determine the performance of the FTS forecasting model (1) determining the length of intervals in the universe of discourse, (2) fuzzification rules or feature representation of crisp time series, (3) establishing fuzzy relation groups (FRGs) and (4) creating defuzzification rule to get crisp forecasted value.

12p viambani 18-06-2024 2 1   Download

The Air Quality Index (AQI) is a tool used to measure the impact of air pollution on health over time. We present a new way for using GP to evolve models for AQI forecasting in this work GP can evolve more accurate AQI forecasting models than other standard machine learning algorithms, according to experimental results using datasets obtained from various stations across multiple cities in India.

11p viambani 18-06-2024 1 1   Download

Stressing the concrete applications of economic forecasting, Practical Business Forecasting is accessible to a wide-range of readers, requiring only a familiarity with basic statistics. The text focuses on the use of models in forecasting, explaining how to build practical forecasting models that produce optimal results. In a clear and detailed format, the text covers estimating and forecasting with single and multi- equation models, univariate time-series modeling, and determining forecasting accuracy.

510p vimeyers 29-05-2024 3 2   Download

Ebook "Air pollution modeling and its application XXII" is focused on local, urban, regional and intercontinental modeling; data assimilation and air quality forecasting; model assessment and evaluation; aerosol transformation; the relationship between air quality and human health and the interaction between climate change and air quality. The work will provide useful reference material for students and professors interested in air pollution modeling at the graduate level as well as researchers and professionals involved in developing and utilizing air pollution models.

738p giangdongdinh 28-05-2024 3 1   Download

Ebook "Air pollution modeling and its application XX" on air pollution modelling and its application is focused on local, urban, regional and intercontinental modelling; data assimilation and air quality forecasting; model assessment and evaluation; aerosol transformation; the relationship between air quality and human health and the effects of climate change on air quality.

608p giangdongdinh 28-05-2024 3 1   Download

This study compares the accuracy of two popular time series forecasting models, namely the autoregressive integrated moving average (ARIMA) model and the long short-term memory (LSTM) model, in predicting daily gold prices from 2000 to 2023. The ARIMA model is a traditional approach that relies on past values to forecast future values, while the LSTM model is a deep learning technique that captures long-term dependencies in time series data.

16p dathienlang1012 03-05-2024 0 0   Download

Part 1 book "Advances in renewable energies and power technologies (Vol 1: Solar and wind energies)" includes contents: Solar cells and arrays - principles, analysis and design; solar PV power plants site selection - A review; forecasting of intermittent solar energy resource; performance of mppt techniques of photovoltaic systems under normal and partial shading conditions; dmppt PV system - modeling and control techniques; flexible power control of photovoltaic systems

257p dianmotminh01 14-05-2024 0 0   Download

This study is conducted based on the hypothesis of an accident from Fengcheng NPP with an incident level of 7, equivalent to the Fukushima accident. A modeling system has been established with different failure scenarios based on the Delft3D model. The research results will provide more insights into the extent and scope of the incident and the impact of meteorological conditions and dynamics on the propagation and distribution of radiation when an incident occurs.

17p dianmotminh02 03-05-2024 2 1   Download

Salinity intrusion forecasting is essential and challenging for hydrometeorology, especially in climate change. Employing machine learning (ML) algorithms and conventional forecasting techniques are gaining popularity and providing high performance. This study presents a method to optimize a machine learning model based on the Long Short-Term Memory (LSTM) algorithm for multistep-ahead salinity forecasting (up to 7 days) at Dai Ngai station, Soc Trang province.

11p dianmotminh02 03-05-2024 2 1   Download

The primary goal of supply chain management is to meet customer needs through the most efficient use of resources, including the allocation of capacity, inventory and workforce. In theory, the supply chain management seeks to match supply and demand and seeks to do so at minimal cost. And the main indicator of changes in the ratio of supply and demand is the change in the price of products. Trend-seasonal time series models were used to analyze the price behavior in the milk market of the Northern region of Kazakhstan.

8p longtimenosee10 26-04-2024 5 1   Download

A study of the state of the theory of fuzzy sets shows that until recently in Russia there were almost no studies in the chemical sector of the economy and finance using fuzzy analysis and forecasting, although by that time all necessary prerequisites for modeling financial systems had been created. The current situation in Russia is characterized by a high degree of science lagging behind the requests of state and commercial supply chain management.

6p longtimenosee10 26-04-2024 2 1   Download

This study will initially evaluate the skill of the IFS model for temperature forecasting in short term at all regions in Viet Nam. In addition, to determine whether the model can be applied in operational forecasting, the study will also evaluate the correct of the model following the legal documents.

13p vijaychest 24-04-2024 4 2   Download

This article uses the ARIMA model to forecast equity risk of listed telecommunications and technology companies in Vietnam, based on quarterly data of listed telecommunications technology companies in the period 2011 - 2023. The results show that the ARIMA Model (1,1,1) is the most suitable model and predicts the beta of the listed telecommunications industry. From there, the author makes comments on the beta forecast results of technology and telecommunications companies to help investors limit equity risk.

10p longtimenosee09 08-04-2024 5 2   Download

This research examines the association between entrepreneurship, two types of IT (the managerial IT resources and Technology IT resources), and performance of firm. The research supports the capabilities enabled through IT for organizations. Cross-sectional survey data has been used for testing the hypotheses and proposed research model from a sample of 203 leading firms in Thailand. The results of data analysis show that the culture of entrepreneurship is an important capability, which can forecast the market performance of a firm.

9p longtimenosee09 08-04-2024 1 0   Download

Gross Domestic Product (GDP) is the sum of income for all goods and services acquired in a given time period. This study develops a model of GDP data for the state of Johor between 2005-2016 using the Logistic Growth model. Long-term GDP equilibrium values are predicted using non-linear equations and tested with different parameters. Forecasts of GDP in the near future are also presented using the appropriate parameters.

4p longtimenosee09 08-04-2024 1 0   Download

The research subject is the process of economic and mathematical modelling of time series characterizing the bitcoin exchange rate volatility, based on the use of artificial neural networks. The purpose of the work is to search and scientifically substantiate the tools and mechanisms for developing prognostic estimates of the crypto currency market development. The paper considers the task of financial time series trend forecasting using the LSTM neural network for supply chain strategies.

5p longtimenosee09 08-04-2024 5 1   Download

Electricity is an important energy source in each country. It is also important for the development of a university. The monthly expense for the electricity bill is different as the activities in the university would affect it. Electricity tariff also changes from time to time, thus, studies regarding electricity consumption are more representative. Therefore, the objective for this study is to evaluate the performance of several forecasting models by using the four error measures to then forecast the monthly electricity consumption.

6p longtimenosee09 08-04-2024 4 1   Download

The core idea behind this research is to examine the significance of financial ratios taken from the financial reports or statements to forecast trend in stock price. For this purpose financial ratios have been taken to forecast stock returns from 2008 to 2018. Thus to predict the future price of stock four financial ratios have been taken, “price to book ratio (P/B), price to earnings ratio (P/E), dividend per share (DPS) and firm sizes”.

8p longtimenosee09 08-04-2024 3 1   Download