Qi Zhang

China Academy of Railway Sciences

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Trends

Author Order

Document Type

Co-Authors

Shujin Qin

Shangqiu Normal University

Shixin Liu

Northeastern University

Xiwang Guo

Liaoning Shihua University

Jiacun Wang

Monmouth University

Rui Lin

Tongji University

Xianghuan Cui

Tongji University

Liang Qi

University of Michigan–Ann Arbor

Xuanfeng Qin

Huashan Hospital

Zhiming Yuan

China Academy of Railway Sciences

Meiqing Lou

Shanghai First People's Hospital

Cooperative Institutions

Tongji University

Shanghai Tenth People's Hospital

Northeastern University

Chinese Academy of Sciences

State Key Laboratory of Synthetical Automation for Process Industries

Shandong University

University of Chinese Academy of Sciences

Ministry of Education of the People's Republic of China

Huazhong University of Science and Technology

Peking University

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Field

An efficient evolutionary algorithm for high-speed train rescheduling under a partial station blockage

Applied Soft Computing (2023)

Rongsheng Wang Qi Zhang Xuewu Dai Zhiming Yuan Tao Zhang

Initialization

Sequence (biology)

Heuristics

Benchmark (surveying)

10.1016/j.asoc.2023.110590

Cite

Citations (6)

The traveling salesman problem with profits considering time-dependent cost and multi-trip mode

Shujin Qin Shixin Liu Qi Zhang

The study extends the traveling salesman problem with profits by considering time-dependent cost and multi-trip mode. Based on the introduction of alternative arcs, a network flow model is established and an exact label setting approach is designed. Upper bound of the partial label is put forward to accelerate the approach. Computational results show the effectiveness of the proposed approach.

Traveling purchaser problem

Mode (computer interface)

10.23919/chicc.2017.8027805

Cite

Citations (2)

Uncertainty-guided Optimal Transport in Depth Supervised Sparse-View 3D Gaussian

arXiv (Cornell University) (2024)

Wei Sun Qi Zhang Yanzhao Zhou Qixiang Ye Jianbin Jiao

3D Gaussian splatting has demonstrated impressive performance in real-time novel view synthesis. However, achieving successful reconstruction from RGB images generally requires multiple input views captured under static conditions. To address the challenge of sparse input views, previous approaches have incorporated depth supervision into the training of 3D Gaussians to mitigate overfitting, using dense predictions from pretrained depth networks as pseudo-ground truth. Nevertheless, depth predictions from monocular depth estimation models inherently exhibit significant uncertainty in specific areas. Relying solely on pixel-wise L2 loss may inadvertently incorporate detrimental noise from these uncertain areas. In this work, we introduce a novel method to supervise the depth distribution of 3D Gaussians, utilizing depth priors with integrated uncertainty estimates. To address these localized errors in depth predictions, we integrate a patch-wise optimal transport strategy to complement traditional L2 loss in depth supervision. Extensive experiments conducted on the LLFF, DTU, and Blender datasets demonstrate that our approach, UGOT, achieves superior novel view synthesis and consistently outperforms state-of-the-art methods.

10.48550/arxiv.2405.19657

Cite

Citations (0)

Performance-Based Design Optimization of Steel Braced Frame Using an Efficient Discrete Algorithm

Mechanisms and machine science (2019)

X. Wang Qi Zhang Xianrong Qin Yuan Sun

Braced frame

10.1007/978-3-030-27053-7_49

Cite

Citations (0)

Process development and surface characterisation on liquid crystalline polymer substrate based system on package with chip embedded for electronic application

Qi Zhang Zonghe Lai Urban Jevelstam Göran Fritz Zhaonian Cheng

Source

Cite

Citations (3)

Model-Based Rolling Matching Strategy for Crowdsourced Drivers and Delivery Tasks Considering Uncertain Transportation Duration

Transportation Research Record Journal of the Transportation Research Board (2020)

Qi Zhang Yang Liu Zhi‐Ping Fan Zonglin Li

The matching of crowdsourced drivers and delivery tasks is an important decision problem for the crowdsourced delivery platform. Although the existence of uncertainty of transportation duration in logistics delivery has been verified, uncertain transportation duration has not been considered in previous studies on the matching of crowdsourced drivers and delivery tasks. This would lead to the limitation that the results of the existing methods cannot meet the time requirements of senders. In this case, the profit and customer satisfaction of the crowdsourced delivery platform would decrease. In this paper, a model-based rolling matching strategy to match crowdsourced drivers and delivery tasks considering uncertain transportation duration is proposed. In addition, it is assumed that the crowdsourced delivery platform also has some dedicated drivers to implement the delivery tasks that cannot be implemented by crowdsourced drivers. First, a simpler problem is described, which is to match crowdsourced drivers and delivery tasks considering uncertain transportation duration in a static data environment. Then, a model is proposed to solve the above problem. Based on the proposed model, this paper further proposes a rolling procedure to solve the problem in a data refreshing environment. Moreover, a heuristic algorithm is presented for combining multiple delivery tasks to solve the one-to-many matching. Finally, a case study and comparison are given to illustrate the validity and the contribution of the proposed matching strategy. The results show that the proposed matching strategy has a distinct advantage of cost savings.

Crowdsourcing

10.1177/0361198120974364

Cite

Citations (6)

Improved ethanol production of a newly isolated thermotolerant Saccharomyces cerevisiae strain after high-energy-pulse-electron beam

Journal of Applied Microbiology (2011)

Qi Zhang Yue Fu Y. Wang Jun Han Jing Lv

To isolate thermotolerant Saccharomyces cerevisiae with high-energy-pulse-electron (HEPE) beam, to optimize the mutation strain fermentation conditions for ethanol production and to conduct a preliminary investigation into the thermotolerant mechanisms.After HEPE beam radiation, the thermotolerant S. cerevisiae strain Y43 was obtained at 45°C. Moreover, the fermentation conditions of mutant Y43 were optimized by L3(3) orthogonal experiment. The optimal glucose content and initial pH for fermentation were 20% g l(-1) and 4·5, respectively; peptone content was the most neglected important factor. Under this condition, ethanol production of Y43 was 83·1 g l(-1) after fermentation for 48 h at 43°C, and ethanol yield was 0·42 g g(-1), which was about 81·5% of the theoretical yield. The results also showed that the trehalose content and the expression of the genes MSN2, SSA3 and TPS1 in Y43 were higher than those in the original strain (YE0) under the same stress conditions.A genetically stable mutant strain with high ethanol yield under heat stress was obtained using HEPE. This mutant may be a suitable candidate for the industrial-scale ethanol production.High-energy-pulse-electron radiation is a new efficient technology in breeding micro-organisms. The mutant obtained in this work has the advantages in industrial ethanol production under thermostress.

Strain (injury)

10.1111/j.1365-2672.2011.05209.x

Cite

Citations (13)

An Improved PageRank Algorithm for Critical Nodes Identification in Railway Timetable with Disturbances by Multilayer Complex Networks

2021 China Automation Congress (CAC) (2021)

Jingyi Ge Zhiming Yuan Qi Zhang

This paper studies the railway timetable from a network science perspective. A multilayer model, consisting of different layers of trains, is proposed to describe the activities (i.e., arrival, departure, and pass through) within and among trains in the railway timetable as a railway timetable network (RTN). A new node centrality measure, called improved PageRank (i-PR), is introduced to determine the set of critical nodes which have a significant effect on the train delay caused by the disturbances in RTN. This measure will be higher when fewer time supplements in sections/stations or buffer time between trains. We analyze the performance of RTN by simulating the possible delay propagation under a FSFS (first-scheduled-firstserved) policy. The results provide an assessment of the delay in the railway system, which helps the railway dispatcher find the critical nodes in the timetable and improve the operation of the trains.

PageRank

Identification

10.1109/cac53003.2021.9727570

Cite

Citations (0)

An Improved Adaptive Genetic Algorithm for U-shaped Disassembly Line Balancing Problem Subject to Area Resource Constraint

JOURNAL OF Cyber-Physical-Social Intelligence (2022)

Xiwang Guo Shujin Qin Liang Qi Qi Zhang Weishuang Bai

The disassembly, recovery, and reuse of waste products are attracting more and more attention. It not only saves resources and protects the environment but also promotes economic development. In a disassembly process, the disassembly line balancing problem is one of the most important problems.At present, the consideration of the space area of workstations is relatively small, and the relatively large use of the area of workstations can also better reduce costs. Aiming at the balancing problem of u-shaped disassembly line, a single-objective optimization mathematical model with area constraints is established with the goal of maximizing proﬁts. In order to solve this problem, we refer to Adaptive Genetic Algorithm and improve its crossover and mutation operator. We adopt elite strategy to avoid premature convergence and improve the global search ability. Its effectiveness is proved by comparison with the optimization results of CPLEX. Experimental results also verify the feasibility of the proposed model and the superiority of the improved Adaptive Genetic Algorithm when solving large-scale instances over another algorithm. At the same time, the experimental results also verify the superiority and effectiveness of the improved Adaptive Genetic Algorithm algorithm by comparing with Random Search.

Workstation

Premature convergence

10.61702/vlzk2105

Cite

Citations (0)

Accurate solution of combined field integral equation for electromagnetic scattering by composite bodies

Mei Song Tong Yuan Zhang Qi Zhang Kun Yang

The Nyström method is used to solve for electromagnetic scattering by three-dimensional composite bodies based on combined field integral equation. In the method of moments solution, one may hesitate on how to represent the magnetic current density using an appropriate basis function if the electric current density is represented by Rao-Wilton-Glisson (RWG) basis function. Using the RWG again, or n̂ × RWG and dual basis function to represent the magnetic current density will have an instability, fictitious charge, or high cost problem, respectively. The Nyström method is simpler to implement and it can also remove all those problems. Numerical examples show that the Nyström method is stable and efficient even for solving composite-body problems.

Basis function

Basis (linear algebra)

10.1109/mape.2015.7510440

Cite

Citations (0)