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Event-triggered adaptive integral reinforcement learning method for zero-sum differential games of nonlinear systems with incomplete known dynamics
This paper designs a novel event-based adaptive learning method for solving zero-sum games (ZSGs) of nonlinear systems with incomplete known...
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Network Flow Problems with Electric Vehicles
Electric vehicle (EV) adoption in long-distance logistics faces challenges such as range anxiety and uneven distribution of charging stations. Two...
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Period Extraction for Traffic Flow Prediction
Due to the particularity of “Tourist chartered Buses, Liner Buses and Dangerous Goods Transport Vehicles” (“TLD Vehicles”), traffic accidents will...
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Computational modeling of flow-mediated angiogenesis: Stokes–Darcy flow on a growing vessel network
Tumor angiogenesis, the growth of new blood vessels towards a tumor, plays a critical role in cancer progression. Tumors release tumor angiogenic...
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Control Flow and Advanced Features
In this chapter, we will discuss the different alert boxes available. Then we will learn about the control flow aspects in Streamlit. We will also...
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Flow Control: Local Spectral Radius Regulation
The spectral radius \(R_\textrm{a}\) of a synaptic weight...
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Consistent Semantic Attacks on Optical Flow
We present a novel approach for semantically targeted adversarial attacks on Optical Flow. In such attacks the goal is to corrupt the flow...
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Flow of Control Using if Statements
In this chapter we are going to look at the if statement in Python. This statement is used to control the flow of execution within a program based on...
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Describing Motion in Computer Images’ Stream: Optical Flow
This chapter gives a review of optical flow and evaluates the performance of the benchmark optical flow techniques on both synthetic and real image...
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Optimal Traffic Flow Distributions on Dynamic Networks
In a parallel network, the Wardrop equilibrium is the optimal distribution of the given total one unit flow across alternative parallel links that...
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A Variational Optical Flow Model for Accurate Motion Estimation from Rotational Image Sequences
There are several optical flow models which aim to capture spatial characteristics of the flow such as divergence and curl. However accurate...
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Joint Controller Placement and Flow Assignment in Software-Defined Edge Networks
Software-Defined Networking (SDN) has been introduced into edge networks as a popular paradigm, leveraging its high programmability, where SDN...
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Non-local modelling of multiphase flow wetting and thermo-capillary flow using peridynamic differential operator
Interfaces in multiphase flows are affected by surface tension, and when temperature gradients occur in the flow domain, tangential surface tensions...
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RAFT-MSF: Self-Supervised Monocular Scene Flow Using Recurrent Optimizer
A popular approach to estimate scene flow is to utilize point cloud data from various Lidar scans. However, there is little attention to learning 3D...
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Attention based convolutional networks for traffic flow prediction
Real-time and accurate prediction of traffic flow plays an important role in intelligent transportation systems. However, short-term traffic flow...
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SplatFlow: Learning Multi-frame Optical Flow via Splatting
The occlusion problem remains a crucial challenge in optical flow estimation (OFE). Despite the recent significant progress brought about by deep...
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Optical flow correction network for repairing video
Some areas in the video may be defective due to storage medium damage or data transmission loss. The defective area can be repaired utilizing the...
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Multi-attention gated temporal graph convolution neural Network for traffic flow forecasting
Real-time and accurate traffic flow forecasting plays a crucial role in transportation systems and holds great significance for urban traffic...
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FeSTGCN: A frequency-enhanced spatio-temporal graph convolutional network for traffic flow prediction under adaptive signal timing
Traffic flow prediction is the fundamental cornerstone of intelligent urban transportation systems. However, existing research has predominantly...
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Sink Location Problems in Dynamic Flow Grid Networks
A dynamic flow network consists of a directed graph, where nodes called sources represent locations of evacuees, and nodes called sinks represent...