As product variety is an important feature for modern enterprises, multi-product demand forecasting is essential to support order decision-making and inventory management. However, these well-established forecasting approaches for multi-dimensional t...
Sales forecasting for new products is significantly important for fashion retailer companies because prediction with high accuracy helps the company improve management efficiency and customer satisfaction. The low inventory strategy of fashion produc...
Accurate sales forecasting for new products is critical in industries characterized by intense competition, rapid innovation, and short product life cycles, such as the smartphone market. This study proposes a data-driven framework that enhances pred...
Floods, storms and hurricanes are devastating for human life and agricultural cropland. Near-real-time (NRT) discharge estimation is crucial to avoid the damages from flood disasters. The key input for the discharge estimation is precipitation. Direc...
Owing to changes in consumer attitudes, the beauty consumer population is growing rapidly and the demands of beauty consumers are variable. With a wide range of beauty products and exaggerated product promotions, consumers rely more on online reviews...
In Romania, natural gas production is concentrated in two large producers, OMV Petrom and Romgaz. However, there are also smaller companies in the natural gas production area. In these companies, the deposits are mostly mature, or new deposits have l...
Agricultural price prediction is a hot research topic in the field of agriculture, and accurate prediction of agricultural prices is crucial to realize the sustainable and healthy development of agriculture. It explores traditional forecasting method...
Hydropower is the largest source of renewable energy in the world and currently dominates flexible electricity production capacity. However, climate variations remain major challenges for efficient production planning, especially the annual forecasti...
Machine learning models that only use data for training and forecasting oilfield production have a sense of disconnection from the physical background, while embedding development patterns in them can enhance interpretability and even improve accurac...
Traditional product demand forecasting has typically been modeled as a single time series problem relying exclusively on temporal information. However, temporal features alone are insufficient to capture complex demand dynamics in modern, interconnec...
This research delineates a pivotal advancement in the domain of sustainable energy systems, with a focused emphasis on the integration of renewable energy sources—predominantly wind and solar power—into the hydrogen production paradigm. A...
Understanding the long-term dynamics of global tea production is essential for assessing supply stability, climate sensitivity, and producer competitiveness. This study examines annual tea production data for major producing countries—China, In...
Accurate prediction of crop production is essential in effectively managing the food security and economic resilience of agricultural countries. This study evaluates the performance of statistical and machine learning-based methods for large-scale cr...
Green energy is very important for developing new cities with high energy consumption, in addition to helping environment preservation. Integrating solar energy into a grid is very challenging and requires precise forecasting of energy production. Re...
Accurate oil production forecasting is essential for optimizing field development and supporting efficient decision-making. However, traditional methods often struggle to capture the complex dynamics of reservoirs, and existing machine learning model...
Accurately forecasting the daily production of coalbed methane (CBM) is important forformulating associated drainage parameters and evaluating the economic benefit of CBM mining. Daily production of CBM depends on many factors, making it difficult to...
Ocean primary productivity generated by phytoplankton is critical for ocean ecosystems and the global carbon cycle. Accurate ocean primary productivity forecasting months in advance is beneficial for marine management. Previous persistence-based pred...
This study reviews the extant literature on hydrogen production cost forecasts to identify and analyze the historical trend of such forecasts in order to explore the feasibility of wider adoption. Hydrogen is an important energy source that can be us...
Quantitative precipitation forecast (QPF) verification stands out as one of the most formidable endeavors in the realm of forecast verification. Traditional verification methods are not suitable for high-resolution forecasting products in some cases....
The operation of microalgal cultivation systems, such as culture dilution associated with harvests, affects biomass productivity. However, the constantly changing incident light and ambient temperature in the outdoor environment make it difficult to...
Shale gas production is governed by complex geological and engineering factors, and its production dynamics are often highly variable. Conventional methods, which can incorporate only a limited number of production-related variables, often struggle t...
A vast number of studies are devoted to the short-term forecasting of agricultural production and market. However, those results are more helpful for market traders than producers and agricultural policy regulators because any structural change in th...
In this paper, we address whether using a disaggregated series or combining an aggregated and disaggregated series improves the forecasting of the aggregated series compared to using the aggregated series alone. We used econometric techniques, such a...
Cold supply chains (CSCs) are critical for preserving the quality and safety of perishable products like milk, which plays a vital role in the daily lives of a vast population, especially in countries like India. This research centers on sustainable...
13 October 2020
The project CLIM2POWER aims at developing a climate service including state-of-the art seasonal climate forecasts in the planning of the operation of the power systems. This work presents part of the project, addressing the forecasting of the hydropo...
Reliable forecasting of unconventional oil and gas well production has consistently been a hot and challenging issue. Most existing data-driven production forecasting models rely solely on a single methodology, with the application effects of other m...
Renewable sources of energy production are some of the main targets today to protect the environment through reduced fossil fuel consumption and CO2 emissions. Alongside wind, solar, marine, biomass and nuclear sources, hydropower is among the oldest...
Accurate short-term oil production forecasting is critical for national energy security and strategic resource planning. However, in practice, the prevalent reliance on extensive daily production histories for training sophisticated models are often...
This paper will discuss the dynamics of steel production in Poland in light of the forecasts of tendencies under conditions of decarbonization. The research presented will be an attempt, using data from 2006 to 2023, to create econometric models and...
Research on forecasting the seasonality and growth trend of natural gas (NG) production and consumption will help organize an analysis base for NG inspection and development, social issues, and allow industrials elements to operate effectively and re...
Wholesale market prices of agricultural products, being essential to the daily lives of consumers, are closely tied to living standards and the overall stability of the agricultural market. The use of a single model to predict nonlinear and dynamic a...
The Brazilian craft beer market has experienced continuous growth, increasing operational challenges for small- and medium-sized breweries that frequently rely on empirical and spreadsheet-based production routines. These practices often lead to inef...
Pakistan’s economy is largely driven by agriculture, and wheat, mostly, stands out as its second most produced crop every year. On the other hand, the average consumption of wheat is steadily increasing as well, due to which its exports are not...
Normally, econometric models that forecast the Italian Industrial Production Index do not exploit information already available at time t + 1 for their own main industry groupings. The new strategy proposed here uses state–space models and aggregates...
Hydraulic fracturing is a critical technology for developing shale gas reservoirs, which are typical natural nanoporous media. However, the complex two−phase flow induced by fracturing fluid retention and the strong interference among hydraulic...
In this paper, we investigate price and order strategies for innovative green products using demand forecasting and sharing. We formulate the problem using a Stackelberg game and propose a dynamic contract that specifies an initial wholesale price, a...
Well-production forecasting plays a crucial role in oil and gas development. Traditional methods, such as numerical simulations, require substantial computational effort, while empirical models tend to exhibit poor accuracy. To address these issues,...
Short-cycle agricultural product sales forecasting significantly reduces food waste by accurately predicting demand, ensuring producers match supply with consumer needs. However, the forecasting is often subject to uncertain factors, resulting in hig...
Developing a forecasting model for oilfield well production plays a significant role in managing mature oilfields as it can help to identify production loss earlier. It is very common that mature fields need more frequent production measurements to d...
The existing trend towards increased penetration of renewable energies in the traditional grid, and the intermittent nature of the weather conditions on which these energy sources depend, make the development of tools for the forecasting of renewable...
This paper analyzes long-term trends in the apparent consumption and external deficit of wood and wood-derived products in Tunisia using annual data covering the period of 1975–2024. Tunisia’s limited forest resources and increasing domes...
Oil production forecasting is one of the essential processes for organizations and governments to make necessary economic plans. This paper proposes a novel hybrid intelligence time series model to forecast oil production from two different oil field...
In today’s competitive market, sales forecasting of newly released and short-term products is an important challenge because there is not enough sales data. To address these challenges, we propose a sales forecasting model for new-released and...
Background: Inventory management for perishable products is challenging because demand variability, forecast reliability, shelf life, and batch constraints must be considered jointly. This study develops a data-driven decision-support framework for a...
This study applies ARIMA models to forecast scientific production trends among G7 (Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States) and BRICS (Brazil, Russia, India, China, and South Africa) countries using Scopus dat...
Biofuel production in China suffers from many uncertainties due to concerns about the government’s support policy and supply of biofuel raw material. Predicting biofuel production is critical to the development of this energy industry. Depending on t...
Changes in the consumption price of aquatic products will affect demand and fishermen’s income. The accurate prediction of consumer price index provides important information regarding the aquatic product market. Based on the non-linear and non...
In recent times, renewable energy sources have gained considerable vitality due to their inexhaustible resources and the detrimental effects of fossil fuels, such as the impact of greenhouse gases on the planet. This article aims to be a supportive t...
Accurate oil and gas production forecasting is essential for optimizing field development and operational efficiency. Steady-state capacity prediction models based on machine learning techniques, such as Linear Regression, Support Vector Machines, Ra...
This paper presents a system for supporting hydropower production on mountainous areas. The system couples the outputs of a numerical weather prediction model and a snow melting and accumulation temperature-based model. Several procedures are present...
of 76