相关论文: Using attention to model long-term dependencies in…
Humans and artificial agents must often learn and switch between multiple tasks in dynamic environments. Success in such settings requires cognitive flexibility: the ability to retain prior knowledge (cognitive stability) while also…
Urban systems are interdependent as individuals' daily activities engage using those urban systems at certain time of day and locations. There may exist clear spatial and temporal correlations among usage patterns across all urban systems.…
Understanding the variability of people's travel patterns is key to transport planning and policy-making. However, to what extent daily transit use displays geographic and temporal variabilities, and what are the contributing factors have…
Recommender systems are widely used for suggesting books, education materials, and products to users by exploring their behaviors. In reality, users' preferences often change over time, leading to studies on time-dependent recommender…
This report documents recent technical work on developing and validating stochastic occupancy models in commercial buildings, performed by the Pacific Northwest National Laboratory (PNNL) as part of the Sensor Impact Evaluation and…
A new generation of "behavior-aware" delay tolerant networks is emerging in what may define future mobile social networks. With the introduction of novel behavior-aware protocols, services and architectures, there is a pressing need to…
We show that energy concepts can contribute to the understanding of human travel behaviour. First, the average travel times for different modes of transportation are inversely proportional to the energy consumption rates measured for the…
As one of the important functions of the intelligent transportation system (ITS), supply-demand prediction for autonomous vehicles provides a decision basis for its control. In this paper, we present two prediction models (i.e. ARLP model…
Driven by growing concerns over air quality and energy security, electric vehicles (EVs) has experienced rapid development and are reshaping global transportation systems and lifestyle patterns. Compared to traditional gasoline-powered…
Evidence in the literature shows that automated and human driving modes demonstrate different driving characteristics, i.e., headway policy, spacing policy, reaction time, comfortable acceleration, and others. These differences alter…
Residential electrification of transport and heat is changing consumption and its characteristics significantly. Previous studies have demonstrated the impact of socio-techno-economic determinants on residential consumption. However, they…
In real-world scene perception human observers generate sequences of fixations to move image patches into the high-acuity center of the visual field. Models of visual attention developed over the last 25 years aim to predict two-dimensional…
Durable interactions are ubiquitous in social network analysis and are increasingly observed with precise time stamps. Phone and video calls, for example, are events to which a specific duration can be assigned. We term data encoding…
A consumer Behaviour model is considered in the context of a network of interacting individuals in an energy market. We propose and analyse a simple dynamical model of an ensemble of coupled active elements mimicking consumers' Behaviour,…
Human mobility plays a crucial role in transportation, urban planning, and public health. Advances in deep learning and the availability of diverse mobility data have transformed mobility modeling. However, existing deep learning models…
This article investigates a family of centrality models for urban networks that incorporate both topological and non-topological factors. Since centrality is inherently recursive, these models can be formulated as fixed-point equations,…
Load points are one of the most vital parts of power systems. Due to the new load forms and programs introduced in the demand side, the load-serving entities (LSEs) no longer deal with lump loads, but rather with more dynamic, rational and…
Nowadays, attitudes towards electricity customers have been changed, so that they are no longer considered static players. The customers behavior identification is vital for establishing modern power systems. This paper utilizes the…
In Partially Observable Markov Decision Processes, integrating an agent's history into memory poses a significant challenge for decision-making. Traditional imitation learning, relying on observation-action pairs for expert demonstrations,…
Mobility is undergoing dramatic transformations. Especially in the context of urban areas, several significant changes are underway, driven by both new mobility needs and environmental concerns. The most mature one, which still is…