Demand patterns
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Autonomous Vehicle Fleet Sizes Required to Serve Different Levels of Demand Open
Automated vehicles (AVs) promise many benefits for future mobility. One of them is a reduction of the required total vehicle fleet size, especially if AVs are used predominantly as shared vehicles. This paper presents research on this pote…
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Predicting origin-destination ride-sourcing demand with a\n spatio-temporal encoder-decoder residual multi-graph convolutional network Open
With the rapid development of mobile-internet technologies, on-demand\nride-sourcing services have become increasingly popular and largely reshaped\nthe way people travel. Demand prediction is one of the most fundamental\ncomponents in sup…
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Quantifying the impact of the COVID-19 lockdown on household water consumption patterns in England Open
The COVID-19 lockdown has instigated significant changes in household behaviours across a variety of categories including water consumption, which in the south and east regions of England is at an all-time high. We analysed water consumpti…
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Performance analysis and fleet requirements of automated demand-responsive transport systems as an urban public transport service Open
The introduction of public transport services by fully automated vehicles can potentially change the way public transit services will be operated, as they allow shifting from rigid scheduled and route-bound services towards flexible, deman…
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Agent-Based Modeling for Scale Evolution of Plug-in Electric Vehicles and Charging Demand Open
Scale evolution pattern recognition of plug-in electric vehicles (PEVs) and charging demand modeling are essential for various involved sectors to promote PEV proliferation and integration into power systems. Considering that the market pe…
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An Insight of Deep Learning Based Demand Forecasting in Smart Grids Open
Smart grids are able to forecast customers’ consumption patterns, i.e., their energy demand, and consequently electricity can be transmitted after taking into account the expected demand. To face today’s demand forecasting challenges, wher…
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Coupling trade-offs and supply-demand of ecosystem services (ES): A new opportunity for ES management Open
The trade-offs and supply-demand relations of ecosystem services (ES) are at the frontier of geographical and ecological studies. However, previous studies have focused on either trade-offs or the supply-demand aspects, while ES conflicts …
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Evaluation of deep learning with long short-term memory networks for time series forecasting in supply chain management Open
Performance analysis and forecasting the evolution of complex systems are two challenging tasks in manufacturing. Time series data from complex systems capture the dynamic behaviors of the underlying processes. However, non-linear and non-…
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Building demand response and control methods for smart grids: A review Open
Demand response provides a solution to the grid imbalance problems which restrict the use of renewable energy. Since buildings possess a high amount of flexible load, they could contribute to smart grid stability and achieve cost savings f…
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Another look at estimators for intermittent demand Open
In this paper we focus on forecasting for intermittent demand data. We propose a new aggregation framework for intermittent demand forecasting that performs aggregation over the demand vol- umes, in contrast to the standard framework that …
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Bike-Sharing Demand Prediction at Community Level under COVID-19 Using Deep Learning Open
An important question in planning and designing bike-sharing services is to support the user’s travel demand by allocating bikes at the stations in an efficient and reliable manner which may require accurate short-time demand prediction. T…
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Ultimate Enterprise Value Creation Using Demand Based Management Open
The 70’s has often been viewed as the decade of quality improvement, during which companies began to invest heavily in quality improvements, and Total Quality Management became a buzzword. In the 80’s, with quality a given, the competitive…
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Fixed-Route vs. Demand-Responsive Transport Feeder Services: An Exploratory Study Using an Agent-Based Model Open
Feeder transport services are fundamental as first and last-mile connectors of mass rapid transit (MRT). They are especially beneficial in low-demand areas where private transport is usually the main transport mode. Besides, the rapid spre…
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Review of barriers to the introduction of residential demand response: a case study in the Netherlands Open
Demand response, defined as the shifting of electricity demand, is generally believed to have value both for the grid and for the market: by matching demand more closely to supply, consumers could profit from lower prices, while in a smart…
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Potential Roles for Demand Response in High-Growth Electric Systems with Increasing Shares of Renewable Generation Open
Many countries around the world are experiencing rapid economic development while simultaneously deploying more wind and solar generators. This report explores potential roles for demand response - the modification of electricity load oper…
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Recreating passenger mode choice-sets for transport simulation: A case study of London, UK Open
Urban transport infrastructure is under increasing pressure from rising travel demand in many cities worldwide. It is no longer sustainable or even economically viable to cope with increased demand by continually adding capacity to transpo…
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The demands they are a-changin’ Open
Smooth operators such as time trends are often applied to deal with unidentified demand shifters. However, if unknown factors affect demand irregularly, a time trend fails to capture the variation. We present an index approach for estimati…
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Short-Term Electricity Demand Forecasting Using a Functional State Space Model Open
In the past several years, the liberalization of the electricity supply, the increase in variability of electric appliances and their use, and the need to respond to the electricity demand in real time has made electricity demand forecasti…
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Teleworking and Online Shopping: Socio-Economic Factors Affecting Their Impact on Transport Demand Open
Teleworking and online shopping became commonplace during the COVID-19 pandemic and can be expected to maintain a strong presence in the foreseeable future. They can lead to significant changes in mobility patterns and transport demand. It…
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Cluster-based demand forecasting using Bayesian model averaging: An ensemble learning approach Open
Demand forecasting is an important aspect in supply chain management that could contribute to enhancing the profit and increasing the efficiency by aligning the supply channels with anticipated demand. In the retail industry, customers and…
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Incorporating Graph Attention and Recurrent Architectures for City-Wide Taxi Demand Prediction Open
Taxi demand prediction is one of the key factors in making online taxi hailing services more successful and more popular. Accurate taxi demand prediction can bring various advantages including, but not limited to, enhancing user experience…
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Bridging the gap between weak-demand areas and public transport using an ant-colony simulation-based optimization Open
This paper presents the first results of an agent-based model aimed at designing feeder bus routes able to cover the gap between public transport coverage and ridership in weak demand areas. The optimized design of feeder bus routes has be…
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Explaining shifts in UK electricity demand using time use data from 1974 to 2014 Open
Peaks in electricity demand generate significant negative environmental and economic impacts. As a result, recent policy and research attention has focused on the potential for temporal flexibility of demand, especially in the context of i…
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A General Framework for Unmet Demand Prediction in On-Demand Transport Services Open
Emerging on-demand transport services, such as Uber and GoGoVan, usually face the dilemma of demand supply imbalance, meaning that the spatial distributions of orders and drivers are imbalanced. Due to such imbalance, much supply resource …
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Managing Healthcare Product Demand Effectively in The Post-Covid-19 Environment: Navigating Demand Variability and Forecasting Complexities Open
Managing the demand for healthcare products is a complex problem requiring in-depth knowledge of epidemiological trends, supply chain dynamics, and regulatory considerations. The intricate management of healthcare product demand in the pos…
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Demand response in commercial buildings with an Assessable impact on occupant comfort Open
Electricity grids are facing challenges due to peak consumption and renewable electricity generation. In this context, demand response offers a solution to many of the challenges, by enabling the integration of consumer side flexibility in…
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Reframing Demand Forecasting: A Two-Fold Approach for Lumpy and Intermittent Demand Open
Demand forecasting is a crucial component of demand management. While shortening the forecasting horizon allows for more recent data and less uncertainty, this frequently means lower data aggregation levels and a more significant data spar…
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City Scale Demand Side Management in Three Different-Sized District Heating Systems Open
Demand side management can add flexibility to a district heating (DH) system by balancing the customer’s hourly fluctuating heat demand. The aim of this study is to analyze how different demand side management control strategies, implement…
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Modeling lot-size with time-dependent demand based on stochastic programming and case study of drug supply in Chile Open
The objective of this paper is to propose a lot-sizing methodology for an inventory system that faces time-dependent random demands and that seeks to minimize total cost as a function of order, purchase, holding and shortage costs. A two-s…
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Assessing cultural ecosystem services supply–demand balance of urban parks in the context of old and new urban districts Open
Rapid urbanization and people's growing spiritual demand make urban spaces face the problem of green space allocation, especially the mismatch between the supply and demand of cultural ecosystem services (CES). The matching degree of suppl…