Digital transformation can improve supply chain sensing, but recovery depends on whether reliable information is converted into coordinated operational action. This study develops a simulation-based case study that integrates data-quality-adjusted in...
Under the guidance of the “dual carbon” goals, building energy efficiency policies are currently in a critical phase of transitioning from “dual controls on energy consumption” to “dual controls on carbon emissions.&rdqu...
The optimal predictive, preventive, corrective and opportunistic maintenance policies play an important role in the success of sustainable maintenance operations. This study discusses a new energy efficiency-related maintenance policy optimization me...
In this paper, we study the problem of optimal routing for the pair of two-server heterogeneous queues operating in parallel and subsequent optimal allocation of customers between the servers in each queue. Heterogeneity implies different servers in...
To address the shortcomings of previous autonomous decision models, which often overlook the personalized features of users, this paper proposes a personalized decision control algorithm for autonomous vehicles based on RLHF (reinforcement learning f...
Multi-agent decision-making faces many challenges such as non-stationarity and sparse rewards, while the complexity and randomness of the real environment further complicate policy development. This paper addresses the high-dimensional policy optimiz...
This paper integrates intelligent reflecting surfaces (IRS) with unmanned aerial vehicles (UAV) to enhance the transmission performance of the Internet of Vehicles (IoV) through non-orthogonal multiple access (NOMA). It focuses on strengthening the s...
In the past few decades, drones have become lighter, with longer hang times, and exhibit more agile performance. To maximize their capabilities during flights in complex environments, researchers have proposed various model-based perception, planning...
Autonomous learning of robotic skills seems to be more natural and more practical than engineered skills, analogous to the learning process of human individuals. Policy gradient methods are a type of reinforcement learning technique which have great...
The N policy is a buffer and transmission management scheme proposed for nodes in wireless sensor networks to save energy. It exploits the concept that the output radio of a node is initially switched off until a critical queue of packets is built up...
Background: The management of inventory under realistic supply chain disruptions, which are often non-exponential, challenges classical control theory. This study addresses the critical question of whether the optimality of simple base-stock policies...
China’s FIT policies for PV and wind power are leading policies to promote the low-carbon transformation of the power system. We design composite models based on real options and the cost–benefit analysis, using the Evaluation Model of Im...
This paper investigates a novel recurrent neural network (NN)-based vector control approach for single-phase grid-connected converters (GCCs) with L (inductor), LC (inductor-capacitor) and LCL (inductor-capacitor-inductor) filters and provides their...
This paper proposes Hermes, a container-based preemptive GPU scheduling framework for accelerating hyper-parameter optimization in deep learning (DL) clusters. Hermes accelerates hyper-parameter optimization by time-sharing between DL jobs and priori...
As an emerging technology, Reconfigurable Intelligent Surfaces (RIS) offers an efficient communication performance optimization solution for the complex and spatially constrained environment of coal mines by effectively controlling signal-propagation...
This paper designs a statistical channel state information-based pinching antenna system for short-packet communication (SPC). To maximize the average maximal achievable rate (MAR) under physical collision-avoidance constraints, we formulate a highly...
The application of space robotic manipulators and heightened autonomy for In-Orbit Servicing (IOS) represents a paramount pursuit for leading space agencies, given the substantial threat posed by space debris to operational satellites and forthcoming...
17 September 2018
In order to cut the costs of third-party logistics companies and respond to the Chinese government’s low-carbon economy plans, this paper studies the more practical and complex open vehicle routing problem, which considers low-carbon trading po...
A wireless communication intelligent anti-jamming decision algorithm based on Deep Reinforcement Learning (DRL) can gradually optimize communication anti-jamming strategies without prior knowledge by continuously interacting with the jamming environm...
In cities today, the digitalization of mobility is one of the most crucial tools that link each single mobility service providers (e.g., ride sharing, public transportation, air travel, etc.) to users. Based on the smart pedestrian network model, the...
The strictest water resources management policy plays a critical role in response to the challenge of water shortage, water security, and sustainable water development in China. Despite the varied analyses of the strictest water resources management...
As renewable energy sources become more integrated into the power grid, traditional virtual synchronous generator (VSG) control strategies have become inadequate for the current low-damping, low-inertia power systems. Therefore, this paper proposes a...
Reconfigurable intelligent surface (RIS)-assisted unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) has become an effective architecture for supporting computation-intensive and latency-sensitive applications by enabling flexible depl...
Multi-asset portfolio optimization under non-stationary financial markets requires robust state representations across market phase transitions. This paper proposes distribution-robust graph representation learning for portfolio optimization (DR-GRL-...
Large CO2 emissions constitute a significant problem today due to their effect on climate change, and the need to design appropriate energy policies to mitigate their consequences and reduce emissions requires a detailed analysis of one of the main s...
In this paper, we study a reconfigurable intelligent surface (RIS)-aided multiuser MISO system with imperfect hardware, where the transceiver design is based on the statistical channel state information (CSI). Considering the transceiver hardware imp...
Path planning in multi-agent UAV swarms is a crucial issue that involves avoiding collisions in dynamic, obstacle-filled environments while consuming the least amount of time and energy possible. This work comprehensively evaluates reinforcement lear...
Mine Internet of Things (MIoT) devices in intelligent mines often face substantial signal attenuation due to challenging operating conditions. The openness of wireless communication also makes it susceptible to smart attackers, such as active eavesdr...
In China, scenic and historic areas are protected areas which are highly integrated with natural and cultural resources. The study analyzed policies based on the theory of policy instruments using content analyses. The results demonstrated that China...
In mobile multi-agent systems (MASs), achieving effective leader–follower coordination under unknown dynamics poses significant challenges. This study proposes a two-stage cooperative strategy that integrates Gaussian Processes (GPs) for modeli...
Non-orthogonal multiple access (NOMA) and reconfigurable intelligent surfaces (RISs) are recognized as key technologies for beyond 5G and 6G wireless communications. To address the high computational complexity and non-convex optimization challenges,...
This paper proposes an optimal-sliding-mode-based adaptive dynamic programming (ADP) master–slave synchronous control strategy for the actuator saturation and performance constraints that AUVs face in dynamic recovery. First, by introducing the...
Analyzing the evolution of cultivated land quality protection policy in China is crucial for refining its frameworks and constructing a “trinity” system integrating quantity, quality, and ecological sustainability. This study employs cont...
The current European policy roadmap aims at forcing the TSOs to coordinate remedial actions used for relieving the congestions in the synchronous power system. In this paper, an optimization problem for coordinated congestion management is described...
Urban logistics serves as a cornerstone for efficient freight transport and sustainable city development, particularly in contexts challenged by congestion and environmental pressures. This research examines the restructuring of the urban logistics s...
The shortage of interdisciplinary talent is a critical bottleneck constraining the development of smart agriculture. Taking Jiangsu Province as a case study, this research constructs and empirically validates an ecosystem model for cultivating interd...
With the rollout of the carbon peak and neutrality targets, conventional coal-fired power plants will gradually be phased down in China’s power system in an orderly manner. The economic and social impact of the energy transition is a vital topi...
To advance its green and low-carbon transition, China has implemented the Low-Carbon City Pilot Policy (LCCPP) as a strategic initiative. A critical question remains unanswered on whether this policy effectively improves urban carbon productivity and...
We investigate a control problem leading to the optimal payment of dividends in a Cramér-Lundberg-type insurance model in which capital injections incur proportional cost, and may be used or not, the latter resulting in bankruptcy. For general claims...
In recent years, research on attribute-based encryption (ABE) has expanded into the quantum domain. Because a traditional single authority can cause the potential single point of failure, an improved lattice-based quantum-resistant identity authentic...
Wireless sensor networks (WSNs) are considerably used for various environmental sensing applications. The architecture and internal specifications of WSNs have been chosen based on the requirements of particular applications. On this basis, WSNs cons...
Wargames are essential simulators for various war scenarios. However, the increasing pace of warfare has rendered traditional wargame decision-making methods inadequate. To address this challenge, wargame-assisted decision-making methods that leverag...
Earth observation satellite task scheduling research plays a key role in space-based remote sensing services. An effective task scheduling strategy can maximize the utilization of satellite resources and obtain larger objective observation profits. I...
Phase-asymmetric electric vehicle (EV) charging can aggravate voltage unbalance in radial distribution feeders, while a smart-inverter battery energy storage system (BESS) can provide both energy shifting and fast reactive-power support. This study d...
Microrobotics has opened new horizons for various applications, especially in medicine. However, it also witnessed challenges in achieving maximum optimal performance. One key challenge is the intelligent, autonomous, and precise navigation control o...
Curling presents a challenging continuous-control problem in which shot outcomes depend on long-horizon interactions between complex physical dynamics, strategic intent, and opponent responses. Despite recent progress in applying reinforcement learni...
This study presents a reinforcement learning–based approach to optimize replenishment policies in the presence of uncertainty, with the objective of minimizing total costs, including inventory holding, shortage, and ordering costs. The focus is...
As the dynamicity of the traffic increases, the need for self-network operation becomes more evident. One of the solutions that might bring cost savings to network operators is the dynamic capacity management of large packet flows, especially in the...
Aiming to address the issue of multi-user dynamic spectrum access in an opportunistic mode in cognitive radio networks leading to low sum throughput, we propose a multi-user opportunistic spectrum access method based on multi-head self-attention and...
This paper studies the secure transmission challenge confronted with future communication systems. In our considered model, the confidential communication between legitimate users is strengthened by an aerial intelligent reflecting surface (AIRS) dep...
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