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Ayesha Ubaid, Farookh Hussain and Muhammad Saqib
Demand forecasting has a pivotal role in making informed business decisions by predicting future sales using historical data. Traditionally, demand forecasting has been widely used in the management of production, staffing and warehousing for sales and m...
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Ryo Matsuoka, Koichi Kobayashi and Yuh Yamashita
A pickup and delivery problem by multiple agents has many applications, such as food delivery service and disaster rescue. In this problem, there are cases where fuels must be considered (e.g., the case of using drones as agents). In addition, there are ...
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Anika Stelzl and Daniela Fuchs-Hanusch
Austria?s water utilities are facing new challenges due to advancing climate change. In recent years, changes in water demand have been observed. Water demand forecast models are required to assess these changes and react to them in a sustainable way. In...
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Coskun Hamzaçebi
Forecasting electricity consumption is a very important issue for governments and electricity related foundations of public sector. Recently, Grey Modelling (GM (1,1)) has been used to forecast electricity demand successfully. GM (1,1) is useful when the...
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Martin Oberascher, Lukas Schartner and Robert Sitzenfrei
The potential of water supply systems for renewable electrical energy production is frequently utilised by a small-scale hydropower unit (SHPU) that utilises the surplus water or pressure. However, fluctuating demand on an hourly and daily basis represen...
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Mehran Nasseri, Taha Falatouri, Patrick Brandtner and Farzaneh Darbanian
In the realm of retail supply chain management, accurate forecasting is paramount for informed decision making, as it directly impacts business operations and profitability. This study delves into the application of tree-based ensemble forecasting, speci...
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Moisés Cordeiro-Costas, Daniel Villanueva, Pablo Eguía-Oller, Miguel Martínez-Comesaña and Sérgio Ramos
Characterizing the electric energy curve can improve the energy efficiency of existing buildings without any structural change and is the basis for controlling and optimizing building performance. Artificial Intelligence (AI) techniques show much potenti...
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Kamal Chapagain, Samundra Gurung, Pisut Kulthanavit and Somsak Kittipiyakul
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Iffat Gheyas, Gregory Epiphaniou, Carsten Maple and Subhash Lakshminarayana
The safe and efficient function of critical national infrastructure (CNI) relies on the accurate demand forecast. Cyber-physical system-based demand forecasting systems (CDFS), typically found in CNI (such as energy, water, and transport), are highly vul...
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Ahmed Shoukry Rashad
Tourism plays an important economic role for many economies and after the COVID-19 pandemic, accurate tourism forecasting become critical for policymakers in tourism-dependent economies. This paper extends the growing literature on the use of internet se...
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Le Quyen Nguyen, Paula Odete Fernandes and João Paulo Teixeira
Vietnam has experienced a tourism expansion over the last decade, proving itself as one of the top tourist destinations in Southeast Asia. The country received more than 18 million international tourists in 2019, compared to only 1.5 million twenty-five ...
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El houssin Ouassou and Hafsa Taya
Tourism is one of the main sources of wealth for the Moroccan regions, since, in 2019, it contributed 7.1% to the total GDP. However, it is considered to be one of the sectors most vulnerable to exogenous shocks (political and social stability, currency ...
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Chandadevi Giri and Yan Chen
Compared to other industries, fashion apparel retail faces many challenges in predicting future demand for its products with a high degree of precision. Fashion products? short life cycle, insufficient historical information, highly uncertain market dema...
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Aling Luo, Boyi Shangguan, Can Yang, Fan Gao, Zhe Fang and Dayu Yu
Taxi demand forecasting plays an important role in ride-hailing services. Accurate taxi demand forecasting can assist taxi companies in pre-allocating taxis, improving vehicle utilization, reducing waiting time, and alleviating traffic congestion. It is ...
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Jo?e Ro?anec, Elena Trajkova, Inna Novalija, Patrik Zajec, Klemen Kenda, Bla? Fortuna and Dunja Mladenic
Artificial intelligence models are increasingly used in manufacturing to inform decision making. Responsible decision making requires accurate forecasts and an understanding of the models? behavior. Furthermore, the insights into the models? rationale ca...
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Matthew S. Janssen and Jon K. Miller
Breaching or overtopping of coastal dunes is associated with greater upland damages. Reliable tools are needed to efficiently assess the likelihood of dune erosion during storm events. Existing methods rely on numerical modeling (extensive investment) or...
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Amir Mousavi, Jonathan Bunker and Jinwoo (Brian) Lee
This study investigated whether indices for socioeconomic, demographic and urban form characteristics can reflect the overall effect of each category in a demand forecasting model. Regression equations were developed for trip generation of the land use o...
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Shun-Chieh Hsieh
The need for accurate tourism demand forecasting is widely recognized. The unreliability of traditional methods makes tourism demand forecasting still challenging. Using deep learning approaches, this study aims to adapt Long Short-Term Memory (LSTM), Bi...
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Daniel Jaramillo-Ramirez and Manuel Perez
The evolution of IoT has come with the challenge of connecting not only a massive number of devices, but also providing an always wider variety of services. In the next few years, a big increase in the number of connected devices is expected, together wi...
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Apostolos Ampountolas
Overnight forecasting is a crucial challenge for revenue managers because of the uncertainty associated between demand and supply. However, there is limited research that focuses on predicting daily hotel demand. Hence, this paper evaluates various model...
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